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<h1>pyFTS.models package<a class="headerlink" href="#pyfts-models-package" title="Permalink to this headline"></a></h1>
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<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-pyFTS.models" title="Permalink to this headline"></a></h2>
<p>Fuzzy Time Series methods</p>
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<div class="section" id="module-pyFTS.models.song">
<span id="pyfts-models-song-module"></span><h2>pyFTS.models.song module<a class="headerlink" href="#module-pyFTS.models.song" title="Permalink to this headline"></a></h2>
<p>First Order Traditional Fuzzy Time Series method by Song &amp; Chissom (1993)</p>
<ol class="upperalpha simple" start="17">
<li><p>Song and B. S. Chissom, “Fuzzy time series and its models,” Fuzzy Sets Syst., vol. 54, no. 3, pp. 269–277, 1993.</p></li>
</ol>
<dl class="py class">
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<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.song.</span></span><span class="sig-name descname"><span class="pre">ConventionalFTS</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/song.html#ConventionalFTS"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS" title="Permalink to this definition"></a></dt>
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<dd><p>Bases: <a class="reference internal" href="pyFTS.common.html#pyFTS.common.fts.FTS" title="pyFTS.common.fts.FTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.fts.FTS</span></code></a></p>
<p>Traditional Fuzzy Time Series</p>
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<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.alpha_cut">
<span class="sig-name descname"><span class="pre">alpha_cut</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.alpha_cut" title="Permalink to this definition"></a></dt>
<dd><p>A float with the minimal membership to be considered on fuzzyfication process</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.auto_update">
<span class="sig-name descname"><span class="pre">auto_update</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.auto_update" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating that model is incremental</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.benchmark_only">
<span class="sig-name descname"><span class="pre">benchmark_only</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.benchmark_only" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating a façade for external (non-FTS) model used on benchmarks or ensembles.</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.detail">
<span class="sig-name descname"><span class="pre">detail</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.detail" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model detailed information</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.dump">
<span class="sig-name descname"><span class="pre">dump</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.dump" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
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<dl class="py method">
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<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.flr_membership_matrix">
<span class="sig-name descname"><span class="pre">flr_membership_matrix</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">flr</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/song.html#ConventionalFTS.flr_membership_matrix"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.flr_membership_matrix" title="Permalink to this definition"></a></dt>
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<dd></dd></dl>
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<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.flrgs">
<span class="sig-name descname"><span class="pre">flrgs</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.10)"><span class="pre">dict</span></a></em><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.flrgs" title="Permalink to this definition"></a></dt>
<dd><p>The list of Fuzzy Logical Relationship Groups - FLRG</p>
</dd></dl>
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<dl class="py method">
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<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.forecast">
<span class="sig-name descname"><span class="pre">forecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ndata</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/song.html#ConventionalFTS.forecast"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.forecast" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>Point forecast one step ahead</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</p></li>
<li><p><strong>kwargs</strong> – model specific parameters</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a list with the forecasted values</p>
</dd>
</dl>
</dd></dl>
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<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.has_interval_forecasting">
<span class="sig-name descname"><span class="pre">has_interval_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.has_interval_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports interval forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.has_point_forecasting">
<span class="sig-name descname"><span class="pre">has_point_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.has_point_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports point forecasting, default: True</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.has_probability_forecasting">
<span class="sig-name descname"><span class="pre">has_probability_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.has_probability_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support probabilistic forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.has_seasonality">
<span class="sig-name descname"><span class="pre">has_seasonality</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.has_seasonality" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports seasonal indexers, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.is_clustered">
<span class="sig-name descname"><span class="pre">is_clustered</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.is_clustered" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), but works like
a monovariate method, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.is_high_order">
<span class="sig-name descname"><span class="pre">is_high_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.is_high_order" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support orders greater than 1, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.is_multivariate">
<span class="sig-name descname"><span class="pre">is_multivariate</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.is_multivariate" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.is_time_variant">
<span class="sig-name descname"><span class="pre">is_time_variant</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.is_time_variant" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if this model is time variant</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.is_wrapper">
<span class="sig-name descname"><span class="pre">is_wrapper</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.is_wrapper" title="Permalink to this definition"></a></dt>
<dd><p>Indicates that this model is a wrapper for other(s) method(s)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.lags">
<span class="sig-name descname"><span class="pre">lags</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.lags" title="Permalink to this definition"></a></dt>
<dd><p>The list of lag indexes for high order models</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.log">
<span class="sig-name descname"><span class="pre">log</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">pd.DataFrame</span></em><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.log" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.max_lag">
<span class="sig-name descname"><span class="pre">max_lag</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.max_lag" title="Permalink to this definition"></a></dt>
<dd><p>A integer indicating the largest lag used by the model. This value also indicates the minimum number of past lags
needed to forecast a single step ahead</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.min_order">
<span class="sig-name descname"><span class="pre">min_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.min_order" title="Permalink to this definition"></a></dt>
<dd><p>In high order models, this integer value indicates the minimal order supported for the model, default: 1</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.name">
<span class="sig-name descname"><span class="pre">name</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.name" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model name</p>
</dd></dl>
Documentation update
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<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.operation_matrix">
<span class="sig-name descname"><span class="pre">operation_matrix</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">flrs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/song.html#ConventionalFTS.operation_matrix"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.operation_matrix" title="Permalink to this definition"></a></dt>
Documentation update
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<dd></dd></dl>
Fixing documentation and type hints
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<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.order">
<span class="sig-name descname"><span class="pre">order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.order" title="Permalink to this definition"></a></dt>
<dd><p>A integer with the model order (number of past lags are used on forecasting)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.original_max">
<span class="sig-name descname"><span class="pre">original_max</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.original_max" title="Permalink to this definition"></a></dt>
<dd><p>A float with the upper limit of the Universe of Discourse, the maximal value found on training data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.original_min">
<span class="sig-name descname"><span class="pre">original_min</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.original_min" title="Permalink to this definition"></a></dt>
<dd><p>A float with the lower limit of the Universe of Discourse, the minimal value found on training data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.partitioner">
<span class="sig-name descname"><span class="pre">partitioner</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference internal" href="pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner" title="pyFTS.partitioners.partitioner.Partitioner"><span class="pre">partitioner.Partitioner</span></a></em><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.partitioner" title="Permalink to this definition"></a></dt>
<dd><p>A pyFTS.partitioners.Partitioner object with the Universe of Discourse partitioner used on the model. This is a mandatory dependecy.</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.shortname">
<span class="sig-name descname"><span class="pre">shortname</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.shortname" title="Permalink to this definition"></a></dt>
<dd><p>A string with a short name or alias for the model</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.standard_horizon">
<span class="sig-name descname"><span class="pre">standard_horizon</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.standard_horizon" title="Permalink to this definition"></a></dt>
<dd><p>Standard forecasting horizon (Default: 1)</p>
</dd></dl>
Documentation update
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<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.train">
<span class="sig-name descname"><span class="pre">train</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/song.html#ConventionalFTS.train"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.train" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>Method specific parameter fitting</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – training time series data</p></li>
<li><p><strong>kwargs</strong> – Method specific parameters</p></li>
</ul>
</dd>
</dl>
</dd></dl>
Fixing documentation and type hints
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<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.transformations">
<span class="sig-name descname"><span class="pre">transformations</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference internal" href="pyFTS.common.transformations.html#pyFTS.common.transformations.transformation.Transformation" title="pyFTS.common.transformations.transformation.Transformation"><span class="pre">transformation.Transformation</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.transformations" title="Permalink to this definition"></a></dt>
<dd><p>A list with the data transformations (common.Transformations) applied on model pre and post processing, default: []</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.transformations_param">
<span class="sig-name descname"><span class="pre">transformations_param</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a></em><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.transformations_param" title="Permalink to this definition"></a></dt>
<dd><p>A list with the specific parameters for each data transformation</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.song.ConventionalFTS.uod_clip">
<span class="sig-name descname"><span class="pre">uod_clip</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.uod_clip" title="Permalink to this definition"></a></dt>
<dd><p>Flag indicating if the test data will be clipped inside the training Universe of Discourse</p>
</dd></dl>
Documentation update
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</dd></dl>
Sphinx documentation for ReadTheDocs site
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</div>
Documentation update
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<div class="section" id="module-pyFTS.models.chen">
<span id="pyfts-models-chen-module"></span><h2>pyFTS.models.chen module<a class="headerlink" href="#module-pyFTS.models.chen" title="Permalink to this headline"></a></h2>
<p>First Order Conventional Fuzzy Time Series by Chen (1996)</p>
<p>S.-M. Chen, “Forecasting enrollments based on fuzzy time series,” Fuzzy Sets Syst., vol. 81, no. 3, pp. 311–319, 1996.</p>
<dl class="py class">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFLRG">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.chen.</span></span><span class="sig-name descname"><span class="pre">ConventionalFLRG</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">LHS</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/chen.html#ConventionalFLRG"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.chen.ConventionalFLRG" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>Bases: <a class="reference internal" href="pyFTS.common.html#pyFTS.common.flrg.FLRG" title="pyFTS.common.flrg.FLRG"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.flrg.FLRG</span></code></a></p>
<p>First Order Conventional Fuzzy Logical Relationship Group</p>
<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFLRG.append_rhs">
<span class="sig-name descname"><span class="pre">append_rhs</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">c</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/chen.html#ConventionalFLRG.append_rhs"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.chen.ConventionalFLRG.append_rhs" title="Permalink to this definition"></a></dt>
Documentation update
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<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFLRG.get_key">
<span class="sig-name descname"><span class="pre">get_key</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sets</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/chen.html#ConventionalFLRG.get_key"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.chen.ConventionalFLRG.get_key" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>Returns a unique identifier for this FLRG</p>
</dd></dl>
</dd></dl>
<dl class="py class">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.chen.</span></span><span class="sig-name descname"><span class="pre">ConventionalFTS</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/chen.html#ConventionalFTS"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>Bases: <a class="reference internal" href="pyFTS.common.html#pyFTS.common.fts.FTS" title="pyFTS.common.fts.FTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.fts.FTS</span></code></a></p>
<p>Conventional Fuzzy Time Series</p>
Fixing documentation and type hints
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<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.alpha_cut">
<span class="sig-name descname"><span class="pre">alpha_cut</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.alpha_cut" title="Permalink to this definition"></a></dt>
<dd><p>A float with the minimal membership to be considered on fuzzyfication process</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.auto_update">
<span class="sig-name descname"><span class="pre">auto_update</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.auto_update" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating that model is incremental</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.benchmark_only">
<span class="sig-name descname"><span class="pre">benchmark_only</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.benchmark_only" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating a façade for external (non-FTS) model used on benchmarks or ensembles.</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.detail">
<span class="sig-name descname"><span class="pre">detail</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.detail" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model detailed information</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.dump">
<span class="sig-name descname"><span class="pre">dump</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.dump" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.flrgs">
<span class="sig-name descname"><span class="pre">flrgs</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.10)"><span class="pre">dict</span></a></em><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.flrgs" title="Permalink to this definition"></a></dt>
<dd><p>The list of Fuzzy Logical Relationship Groups - FLRG</p>
</dd></dl>
Documentation update
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<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.forecast">
<span class="sig-name descname"><span class="pre">forecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ndata</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/chen.html#ConventionalFTS.forecast"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.forecast" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>Point forecast one step ahead</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</p></li>
<li><p><strong>kwargs</strong> – model specific parameters</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a list with the forecasted values</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.generate_flrg">
<span class="sig-name descname"><span class="pre">generate_flrg</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">flrs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/chen.html#ConventionalFTS.generate_flrg"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.generate_flrg" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
Fixing documentation and type hints
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<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.has_interval_forecasting">
<span class="sig-name descname"><span class="pre">has_interval_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.has_interval_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports interval forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.has_point_forecasting">
<span class="sig-name descname"><span class="pre">has_point_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.has_point_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports point forecasting, default: True</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.has_probability_forecasting">
<span class="sig-name descname"><span class="pre">has_probability_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.has_probability_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support probabilistic forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.has_seasonality">
<span class="sig-name descname"><span class="pre">has_seasonality</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.has_seasonality" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports seasonal indexers, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.is_clustered">
<span class="sig-name descname"><span class="pre">is_clustered</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.is_clustered" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), but works like
a monovariate method, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.is_high_order">
<span class="sig-name descname"><span class="pre">is_high_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.is_high_order" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support orders greater than 1, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.is_multivariate">
<span class="sig-name descname"><span class="pre">is_multivariate</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.is_multivariate" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.is_time_variant">
<span class="sig-name descname"><span class="pre">is_time_variant</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.is_time_variant" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if this model is time variant</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.is_wrapper">
<span class="sig-name descname"><span class="pre">is_wrapper</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.is_wrapper" title="Permalink to this definition"></a></dt>
<dd><p>Indicates that this model is a wrapper for other(s) method(s)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.lags">
<span class="sig-name descname"><span class="pre">lags</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.lags" title="Permalink to this definition"></a></dt>
<dd><p>The list of lag indexes for high order models</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.log">
<span class="sig-name descname"><span class="pre">log</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">pd.DataFrame</span></em><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.log" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.max_lag">
<span class="sig-name descname"><span class="pre">max_lag</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.max_lag" title="Permalink to this definition"></a></dt>
<dd><p>A integer indicating the largest lag used by the model. This value also indicates the minimum number of past lags
needed to forecast a single step ahead</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.min_order">
<span class="sig-name descname"><span class="pre">min_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.min_order" title="Permalink to this definition"></a></dt>
<dd><p>In high order models, this integer value indicates the minimal order supported for the model, default: 1</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.name">
<span class="sig-name descname"><span class="pre">name</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.name" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model name</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.order">
<span class="sig-name descname"><span class="pre">order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.order" title="Permalink to this definition"></a></dt>
<dd><p>A integer with the model order (number of past lags are used on forecasting)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.original_max">
<span class="sig-name descname"><span class="pre">original_max</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.original_max" title="Permalink to this definition"></a></dt>
<dd><p>A float with the upper limit of the Universe of Discourse, the maximal value found on training data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.original_min">
<span class="sig-name descname"><span class="pre">original_min</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.original_min" title="Permalink to this definition"></a></dt>
<dd><p>A float with the lower limit of the Universe of Discourse, the minimal value found on training data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.partitioner">
<span class="sig-name descname"><span class="pre">partitioner</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference internal" href="pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner" title="pyFTS.partitioners.partitioner.Partitioner"><span class="pre">partitioner.Partitioner</span></a></em><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.partitioner" title="Permalink to this definition"></a></dt>
<dd><p>A pyFTS.partitioners.Partitioner object with the Universe of Discourse partitioner used on the model. This is a mandatory dependecy.</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.shortname">
<span class="sig-name descname"><span class="pre">shortname</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.shortname" title="Permalink to this definition"></a></dt>
<dd><p>A string with a short name or alias for the model</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.standard_horizon">
<span class="sig-name descname"><span class="pre">standard_horizon</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.standard_horizon" title="Permalink to this definition"></a></dt>
<dd><p>Standard forecasting horizon (Default: 1)</p>
</dd></dl>
Documentation update
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<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.train">
<span class="sig-name descname"><span class="pre">train</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/chen.html#ConventionalFTS.train"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.train" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>Method specific parameter fitting</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – training time series data</p></li>
<li><p><strong>kwargs</strong> – Method specific parameters</p></li>
</ul>
</dd>
</dl>
</dd></dl>
Fixing documentation and type hints
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<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.transformations">
<span class="sig-name descname"><span class="pre">transformations</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference internal" href="pyFTS.common.transformations.html#pyFTS.common.transformations.transformation.Transformation" title="pyFTS.common.transformations.transformation.Transformation"><span class="pre">transformation.Transformation</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.transformations" title="Permalink to this definition"></a></dt>
<dd><p>A list with the data transformations (common.Transformations) applied on model pre and post processing, default: []</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.transformations_param">
<span class="sig-name descname"><span class="pre">transformations_param</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a></em><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.transformations_param" title="Permalink to this definition"></a></dt>
<dd><p>A list with the specific parameters for each data transformation</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.chen.ConventionalFTS.uod_clip">
<span class="sig-name descname"><span class="pre">uod_clip</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.uod_clip" title="Permalink to this definition"></a></dt>
<dd><p>Flag indicating if the test data will be clipped inside the training Universe of Discourse</p>
</dd></dl>
Documentation update
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</dd></dl>
Updating the documentation
2018-08-30 23:04:52 +04:00
</div>
Documentation update
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<div class="section" id="module-pyFTS.models.yu">
<span id="pyfts-models-yu-module"></span><h2>pyFTS.models.yu module<a class="headerlink" href="#module-pyFTS.models.yu" title="Permalink to this headline"></a></h2>
<p>First Order Weighted Fuzzy Time Series by Yu(2005)</p>
<p>H.-K. Yu, “Weighted fuzzy time series models for TAIEX forecasting,”
Phys. A Stat. Mech. its Appl., vol. 349, no. 3, pp. 609–624, 2005.</p>
<dl class="py class">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFLRG">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.yu.</span></span><span class="sig-name descname"><span class="pre">WeightedFLRG</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">LHS</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/yu.html#WeightedFLRG"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.yu.WeightedFLRG" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>Bases: <a class="reference internal" href="pyFTS.common.html#pyFTS.common.flrg.FLRG" title="pyFTS.common.flrg.FLRG"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.flrg.FLRG</span></code></a></p>
<p>First Order Weighted Fuzzy Logical Relationship Group</p>
<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFLRG.append_rhs">
<span class="sig-name descname"><span class="pre">append_rhs</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">c</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/yu.html#WeightedFLRG.append_rhs"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.yu.WeightedFLRG.append_rhs" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFLRG.weights">
<span class="sig-name descname"><span class="pre">weights</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sets</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/yu.html#WeightedFLRG.weights"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.yu.WeightedFLRG.weights" title="Permalink to this definition"></a></dt>
Documentation update
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<dd></dd></dl>
</dd></dl>
<dl class="py class">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.yu.</span></span><span class="sig-name descname"><span class="pre">WeightedFTS</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/yu.html#WeightedFTS"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>Bases: <a class="reference internal" href="pyFTS.common.html#pyFTS.common.fts.FTS" title="pyFTS.common.fts.FTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.fts.FTS</span></code></a></p>
<p>First Order Weighted Fuzzy Time Series</p>
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.alpha_cut">
<span class="sig-name descname"><span class="pre">alpha_cut</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.alpha_cut" title="Permalink to this definition"></a></dt>
<dd><p>A float with the minimal membership to be considered on fuzzyfication process</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.auto_update">
<span class="sig-name descname"><span class="pre">auto_update</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.auto_update" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating that model is incremental</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.benchmark_only">
<span class="sig-name descname"><span class="pre">benchmark_only</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.benchmark_only" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating a façade for external (non-FTS) model used on benchmarks or ensembles.</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.detail">
<span class="sig-name descname"><span class="pre">detail</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.detail" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model detailed information</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.dump">
<span class="sig-name descname"><span class="pre">dump</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.dump" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.flrgs">
<span class="sig-name descname"><span class="pre">flrgs</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.10)"><span class="pre">dict</span></a></em><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.flrgs" title="Permalink to this definition"></a></dt>
<dd><p>The list of Fuzzy Logical Relationship Groups - FLRG</p>
</dd></dl>
Documentation update
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<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.forecast">
<span class="sig-name descname"><span class="pre">forecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ndata</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/yu.html#WeightedFTS.forecast"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.forecast" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>Point forecast one step ahead</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</p></li>
<li><p><strong>kwargs</strong> – model specific parameters</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a list with the forecasted values</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.generate_FLRG">
<span class="sig-name descname"><span class="pre">generate_FLRG</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">flrs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/yu.html#WeightedFTS.generate_FLRG"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.generate_FLRG" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.has_interval_forecasting">
<span class="sig-name descname"><span class="pre">has_interval_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.has_interval_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports interval forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.has_point_forecasting">
<span class="sig-name descname"><span class="pre">has_point_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.has_point_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports point forecasting, default: True</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.has_probability_forecasting">
<span class="sig-name descname"><span class="pre">has_probability_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.has_probability_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support probabilistic forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.has_seasonality">
<span class="sig-name descname"><span class="pre">has_seasonality</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.has_seasonality" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports seasonal indexers, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.is_clustered">
<span class="sig-name descname"><span class="pre">is_clustered</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.is_clustered" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), but works like
a monovariate method, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.is_high_order">
<span class="sig-name descname"><span class="pre">is_high_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.is_high_order" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support orders greater than 1, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.is_multivariate">
<span class="sig-name descname"><span class="pre">is_multivariate</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.is_multivariate" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.is_time_variant">
<span class="sig-name descname"><span class="pre">is_time_variant</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.is_time_variant" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if this model is time variant</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.is_wrapper">
<span class="sig-name descname"><span class="pre">is_wrapper</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.is_wrapper" title="Permalink to this definition"></a></dt>
<dd><p>Indicates that this model is a wrapper for other(s) method(s)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.lags">
<span class="sig-name descname"><span class="pre">lags</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.lags" title="Permalink to this definition"></a></dt>
<dd><p>The list of lag indexes for high order models</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.log">
<span class="sig-name descname"><span class="pre">log</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">pd.DataFrame</span></em><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.log" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.max_lag">
<span class="sig-name descname"><span class="pre">max_lag</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.max_lag" title="Permalink to this definition"></a></dt>
<dd><p>A integer indicating the largest lag used by the model. This value also indicates the minimum number of past lags
needed to forecast a single step ahead</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.min_order">
<span class="sig-name descname"><span class="pre">min_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.min_order" title="Permalink to this definition"></a></dt>
<dd><p>In high order models, this integer value indicates the minimal order supported for the model, default: 1</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.name">
<span class="sig-name descname"><span class="pre">name</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.name" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model name</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.order">
<span class="sig-name descname"><span class="pre">order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.order" title="Permalink to this definition"></a></dt>
<dd><p>A integer with the model order (number of past lags are used on forecasting)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.original_max">
<span class="sig-name descname"><span class="pre">original_max</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.original_max" title="Permalink to this definition"></a></dt>
<dd><p>A float with the upper limit of the Universe of Discourse, the maximal value found on training data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.original_min">
<span class="sig-name descname"><span class="pre">original_min</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.original_min" title="Permalink to this definition"></a></dt>
<dd><p>A float with the lower limit of the Universe of Discourse, the minimal value found on training data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.partitioner">
<span class="sig-name descname"><span class="pre">partitioner</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference internal" href="pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner" title="pyFTS.partitioners.partitioner.Partitioner"><span class="pre">partitioner.Partitioner</span></a></em><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.partitioner" title="Permalink to this definition"></a></dt>
<dd><p>A pyFTS.partitioners.Partitioner object with the Universe of Discourse partitioner used on the model. This is a mandatory dependecy.</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.shortname">
<span class="sig-name descname"><span class="pre">shortname</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.shortname" title="Permalink to this definition"></a></dt>
<dd><p>A string with a short name or alias for the model</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.standard_horizon">
<span class="sig-name descname"><span class="pre">standard_horizon</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.standard_horizon" title="Permalink to this definition"></a></dt>
<dd><p>Standard forecasting horizon (Default: 1)</p>
</dd></dl>
Documentation update
2021-01-13 01:04:42 +04:00
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.train">
<span class="sig-name descname"><span class="pre">train</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ndata</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/yu.html#WeightedFTS.train"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.train" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>Method specific parameter fitting</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – training time series data</p></li>
<li><p><strong>kwargs</strong> – Method specific parameters</p></li>
</ul>
</dd>
</dl>
</dd></dl>
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.transformations">
<span class="sig-name descname"><span class="pre">transformations</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference internal" href="pyFTS.common.transformations.html#pyFTS.common.transformations.transformation.Transformation" title="pyFTS.common.transformations.transformation.Transformation"><span class="pre">transformation.Transformation</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.transformations" title="Permalink to this definition"></a></dt>
<dd><p>A list with the data transformations (common.Transformations) applied on model pre and post processing, default: []</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.transformations_param">
<span class="sig-name descname"><span class="pre">transformations_param</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a></em><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.transformations_param" title="Permalink to this definition"></a></dt>
<dd><p>A list with the specific parameters for each data transformation</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.yu.WeightedFTS.uod_clip">
<span class="sig-name descname"><span class="pre">uod_clip</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.uod_clip" title="Permalink to this definition"></a></dt>
<dd><p>Flag indicating if the test data will be clipped inside the training Universe of Discourse</p>
</dd></dl>
Documentation update
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</dd></dl>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
</div>
Documentation update
2021-01-13 01:04:42 +04:00
<div class="section" id="module-pyFTS.models.cheng">
<span id="pyfts-models-cheng-module"></span><h2>pyFTS.models.cheng module<a class="headerlink" href="#module-pyFTS.models.cheng" title="Permalink to this headline"></a></h2>
<p>Trend Weighted Fuzzy Time Series by Cheng, Chen and Wu (2009)</p>
<p>C.-H. Cheng, Y.-S. Chen, and Y.-L. Wu, “Forecasting innovation diffusion of products using trend-weighted fuzzy time-series model,”
Expert Syst. Appl., vol. 36, no. 2, pp. 1826–1832, 2009.</p>
<dl class="py class">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFLRG">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.cheng.</span></span><span class="sig-name descname"><span class="pre">TrendWeightedFLRG</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">LHS</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/cheng.html#TrendWeightedFLRG"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFLRG" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>Bases: <a class="reference internal" href="#pyFTS.models.yu.WeightedFLRG" title="pyFTS.models.yu.WeightedFLRG"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.models.yu.WeightedFLRG</span></code></a></p>
<p>First Order Trend Weighted Fuzzy Logical Relationship Group</p>
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFLRG.weights">
<span class="sig-name descname"><span class="pre">weights</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sets</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/cheng.html#TrendWeightedFLRG.weights"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFLRG.weights" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
</dd></dl>
<dl class="py class">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFTS">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.cheng.</span></span><span class="sig-name descname"><span class="pre">TrendWeightedFTS</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/cheng.html#TrendWeightedFTS"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>Bases: <a class="reference internal" href="#pyFTS.models.yu.WeightedFTS" title="pyFTS.models.yu.WeightedFTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.models.yu.WeightedFTS</span></code></a></p>
<p>First Order Trend Weighted Fuzzy Time Series</p>
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFTS.alpha_cut">
<span class="sig-name descname"><span class="pre">alpha_cut</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS.alpha_cut" title="Permalink to this definition"></a></dt>
<dd><p>A float with the minimal membership to be considered on fuzzyfication process</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFTS.auto_update">
<span class="sig-name descname"><span class="pre">auto_update</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS.auto_update" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating that model is incremental</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFTS.benchmark_only">
<span class="sig-name descname"><span class="pre">benchmark_only</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS.benchmark_only" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating a façade for external (non-FTS) model used on benchmarks or ensembles.</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFTS.detail">
<span class="sig-name descname"><span class="pre">detail</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS.detail" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model detailed information</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFTS.dump">
<span class="sig-name descname"><span class="pre">dump</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS.dump" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFTS.flrgs">
<span class="sig-name descname"><span class="pre">flrgs</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.10)"><span class="pre">dict</span></a></em><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS.flrgs" title="Permalink to this definition"></a></dt>
<dd><p>The list of Fuzzy Logical Relationship Groups - FLRG</p>
</dd></dl>
Documentation update
2021-01-13 01:04:42 +04:00
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFTS.generate_FLRG">
<span class="sig-name descname"><span class="pre">generate_FLRG</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">flrs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/cheng.html#TrendWeightedFTS.generate_FLRG"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS.generate_FLRG" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFTS.has_interval_forecasting">
<span class="sig-name descname"><span class="pre">has_interval_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS.has_interval_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports interval forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFTS.has_point_forecasting">
<span class="sig-name descname"><span class="pre">has_point_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS.has_point_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports point forecasting, default: True</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFTS.has_probability_forecasting">
<span class="sig-name descname"><span class="pre">has_probability_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS.has_probability_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support probabilistic forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFTS.has_seasonality">
<span class="sig-name descname"><span class="pre">has_seasonality</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS.has_seasonality" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports seasonal indexers, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFTS.is_clustered">
<span class="sig-name descname"><span class="pre">is_clustered</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS.is_clustered" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), but works like
a monovariate method, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFTS.is_high_order">
<span class="sig-name descname"><span class="pre">is_high_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS.is_high_order" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support orders greater than 1, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFTS.is_multivariate">
<span class="sig-name descname"><span class="pre">is_multivariate</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS.is_multivariate" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFTS.is_time_variant">
<span class="sig-name descname"><span class="pre">is_time_variant</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS.is_time_variant" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if this model is time variant</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFTS.is_wrapper">
<span class="sig-name descname"><span class="pre">is_wrapper</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS.is_wrapper" title="Permalink to this definition"></a></dt>
<dd><p>Indicates that this model is a wrapper for other(s) method(s)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFTS.lags">
<span class="sig-name descname"><span class="pre">lags</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS.lags" title="Permalink to this definition"></a></dt>
<dd><p>The list of lag indexes for high order models</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFTS.log">
<span class="sig-name descname"><span class="pre">log</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">pd.DataFrame</span></em><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS.log" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFTS.max_lag">
<span class="sig-name descname"><span class="pre">max_lag</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS.max_lag" title="Permalink to this definition"></a></dt>
<dd><p>A integer indicating the largest lag used by the model. This value also indicates the minimum number of past lags
needed to forecast a single step ahead</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFTS.min_order">
<span class="sig-name descname"><span class="pre">min_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS.min_order" title="Permalink to this definition"></a></dt>
<dd><p>In high order models, this integer value indicates the minimal order supported for the model, default: 1</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFTS.name">
<span class="sig-name descname"><span class="pre">name</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS.name" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model name</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFTS.order">
<span class="sig-name descname"><span class="pre">order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS.order" title="Permalink to this definition"></a></dt>
<dd><p>A integer with the model order (number of past lags are used on forecasting)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFTS.original_max">
<span class="sig-name descname"><span class="pre">original_max</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS.original_max" title="Permalink to this definition"></a></dt>
<dd><p>A float with the upper limit of the Universe of Discourse, the maximal value found on training data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFTS.original_min">
<span class="sig-name descname"><span class="pre">original_min</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS.original_min" title="Permalink to this definition"></a></dt>
<dd><p>A float with the lower limit of the Universe of Discourse, the minimal value found on training data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFTS.partitioner">
<span class="sig-name descname"><span class="pre">partitioner</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference internal" href="pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner" title="pyFTS.partitioners.partitioner.Partitioner"><span class="pre">partitioner.Partitioner</span></a></em><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS.partitioner" title="Permalink to this definition"></a></dt>
<dd><p>A pyFTS.partitioners.Partitioner object with the Universe of Discourse partitioner used on the model. This is a mandatory dependecy.</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFTS.shortname">
<span class="sig-name descname"><span class="pre">shortname</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS.shortname" title="Permalink to this definition"></a></dt>
<dd><p>A string with a short name or alias for the model</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFTS.standard_horizon">
<span class="sig-name descname"><span class="pre">standard_horizon</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS.standard_horizon" title="Permalink to this definition"></a></dt>
<dd><p>Standard forecasting horizon (Default: 1)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFTS.transformations">
<span class="sig-name descname"><span class="pre">transformations</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference internal" href="pyFTS.common.transformations.html#pyFTS.common.transformations.transformation.Transformation" title="pyFTS.common.transformations.transformation.Transformation"><span class="pre">transformation.Transformation</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS.transformations" title="Permalink to this definition"></a></dt>
<dd><p>A list with the data transformations (common.Transformations) applied on model pre and post processing, default: []</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFTS.transformations_param">
<span class="sig-name descname"><span class="pre">transformations_param</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a></em><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS.transformations_param" title="Permalink to this definition"></a></dt>
<dd><p>A list with the specific parameters for each data transformation</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.cheng.TrendWeightedFTS.uod_clip">
<span class="sig-name descname"><span class="pre">uod_clip</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS.uod_clip" title="Permalink to this definition"></a></dt>
<dd><p>Flag indicating if the test data will be clipped inside the training Universe of Discourse</p>
</dd></dl>
Documentation update
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</dd></dl>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
</div>
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<div class="section" id="module-pyFTS.models.hofts">
<span id="pyfts-models-hofts-module"></span><h2>pyFTS.models.hofts module<a class="headerlink" href="#module-pyFTS.models.hofts" title="Permalink to this headline"></a></h2>
<p>High Order FTS</p>
<p>Severiano, S. A. Jr; Silva, P. C. L.; Sadaei, H. J.; Guimarães, F. G. Very Short-term Solar Forecasting
using Fuzzy Time Series. 2017 IEEE International Conference on Fuzzy Systems. DOI10.1109/FUZZ-IEEE.2017.8015732</p>
<dl class="py class">
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<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFLRG">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.hofts.</span></span><span class="sig-name descname"><span class="pre">HighOrderFLRG</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">order</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#HighOrderFLRG"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFLRG" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>Bases: <a class="reference internal" href="pyFTS.common.html#pyFTS.common.flrg.FLRG" title="pyFTS.common.flrg.FLRG"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.flrg.FLRG</span></code></a></p>
<p>Conventional High Order Fuzzy Logical Relationship Group</p>
<dl class="py method">
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<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFLRG.append_lhs">
<span class="sig-name descname"><span class="pre">append_lhs</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">c</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#HighOrderFLRG.append_lhs"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFLRG.append_lhs" title="Permalink to this definition"></a></dt>
Documentation update
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<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFLRG.append_rhs">
<span class="sig-name descname"><span class="pre">append_rhs</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">c</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#HighOrderFLRG.append_rhs"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFLRG.append_rhs" title="Permalink to this definition"></a></dt>
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<dd></dd></dl>
</dd></dl>
<dl class="py class">
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<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.hofts.</span></span><span class="sig-name descname"><span class="pre">HighOrderFTS</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#HighOrderFTS"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>Bases: <a class="reference internal" href="pyFTS.common.html#pyFTS.common.fts.FTS" title="pyFTS.common.fts.FTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.fts.FTS</span></code></a></p>
<p>Conventional High Order Fuzzy Time Series</p>
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<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.alpha_cut">
<span class="sig-name descname"><span class="pre">alpha_cut</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.alpha_cut" title="Permalink to this definition"></a></dt>
<dd><p>A float with the minimal membership to be considered on fuzzyfication process</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.auto_update">
<span class="sig-name descname"><span class="pre">auto_update</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.auto_update" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating that model is incremental</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.benchmark_only">
<span class="sig-name descname"><span class="pre">benchmark_only</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.benchmark_only" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating a façade for external (non-FTS) model used on benchmarks or ensembles.</p>
</dd></dl>
Documentation update
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<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.configure_lags">
<span class="sig-name descname"><span class="pre">configure_lags</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#HighOrderFTS.configure_lags"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.configure_lags" title="Permalink to this definition"></a></dt>
Documentation update
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<dd></dd></dl>
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<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.detail">
<span class="sig-name descname"><span class="pre">detail</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.detail" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model detailed information</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.dump">
<span class="sig-name descname"><span class="pre">dump</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.dump" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.flrgs">
<span class="sig-name descname"><span class="pre">flrgs</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.10)"><span class="pre">dict</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.flrgs" title="Permalink to this definition"></a></dt>
<dd><p>The list of Fuzzy Logical Relationship Groups - FLRG</p>
</dd></dl>
Documentation update
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<dl class="py method">
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<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.forecast">
<span class="sig-name descname"><span class="pre">forecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ndata</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#HighOrderFTS.forecast"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.forecast" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>Point forecast one step ahead</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</p></li>
<li><p><strong>kwargs</strong> – model specific parameters</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a list with the forecasted values</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.generate_flrg">
<span class="sig-name descname"><span class="pre">generate_flrg</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#HighOrderFTS.generate_flrg"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.generate_flrg" title="Permalink to this definition"></a></dt>
Documentation update
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<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.generate_flrg_fuzzyfied">
<span class="sig-name descname"><span class="pre">generate_flrg_fuzzyfied</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#HighOrderFTS.generate_flrg_fuzzyfied"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.generate_flrg_fuzzyfied" title="Permalink to this definition"></a></dt>
Documentation update
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<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.generate_lhs_flrg">
<span class="sig-name descname"><span class="pre">generate_lhs_flrg</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sample</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">explain</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#HighOrderFTS.generate_lhs_flrg"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.generate_lhs_flrg" title="Permalink to this definition"></a></dt>
Documentation update
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<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.generate_lhs_flrg_fuzzyfied">
<span class="sig-name descname"><span class="pre">generate_lhs_flrg_fuzzyfied</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sample</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">explain</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#HighOrderFTS.generate_lhs_flrg_fuzzyfied"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.generate_lhs_flrg_fuzzyfied" title="Permalink to this definition"></a></dt>
Documentation update
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<dd></dd></dl>
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<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.has_interval_forecasting">
<span class="sig-name descname"><span class="pre">has_interval_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.has_interval_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports interval forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.has_point_forecasting">
<span class="sig-name descname"><span class="pre">has_point_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.has_point_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports point forecasting, default: True</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.has_probability_forecasting">
<span class="sig-name descname"><span class="pre">has_probability_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.has_probability_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support probabilistic forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.has_seasonality">
<span class="sig-name descname"><span class="pre">has_seasonality</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.has_seasonality" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports seasonal indexers, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.is_clustered">
<span class="sig-name descname"><span class="pre">is_clustered</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.is_clustered" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), but works like
a monovariate method, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.is_high_order">
<span class="sig-name descname"><span class="pre">is_high_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.is_high_order" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support orders greater than 1, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.is_multivariate">
<span class="sig-name descname"><span class="pre">is_multivariate</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.is_multivariate" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.is_time_variant">
<span class="sig-name descname"><span class="pre">is_time_variant</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.is_time_variant" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if this model is time variant</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.is_wrapper">
<span class="sig-name descname"><span class="pre">is_wrapper</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.is_wrapper" title="Permalink to this definition"></a></dt>
<dd><p>Indicates that this model is a wrapper for other(s) method(s)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.lags">
<span class="sig-name descname"><span class="pre">lags</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.lags" title="Permalink to this definition"></a></dt>
<dd><p>The list of lag indexes for high order models</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.log">
<span class="sig-name descname"><span class="pre">log</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">pd.DataFrame</span></em><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.log" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.max_lag">
<span class="sig-name descname"><span class="pre">max_lag</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.max_lag" title="Permalink to this definition"></a></dt>
<dd><p>A integer indicating the largest lag used by the model. This value also indicates the minimum number of past lags
needed to forecast a single step ahead</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.min_order">
<span class="sig-name descname"><span class="pre">min_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.min_order" title="Permalink to this definition"></a></dt>
<dd><p>In high order models, this integer value indicates the minimal order supported for the model, default: 1</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.name">
<span class="sig-name descname"><span class="pre">name</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.name" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model name</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.order">
<span class="sig-name descname"><span class="pre">order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.order" title="Permalink to this definition"></a></dt>
<dd><p>A integer with the model order (number of past lags are used on forecasting)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.original_max">
<span class="sig-name descname"><span class="pre">original_max</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.original_max" title="Permalink to this definition"></a></dt>
<dd><p>A float with the upper limit of the Universe of Discourse, the maximal value found on training data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.original_min">
<span class="sig-name descname"><span class="pre">original_min</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.original_min" title="Permalink to this definition"></a></dt>
<dd><p>A float with the lower limit of the Universe of Discourse, the minimal value found on training data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.partitioner">
<span class="sig-name descname"><span class="pre">partitioner</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference internal" href="pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner" title="pyFTS.partitioners.partitioner.Partitioner"><span class="pre">partitioner.Partitioner</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.partitioner" title="Permalink to this definition"></a></dt>
<dd><p>A pyFTS.partitioners.Partitioner object with the Universe of Discourse partitioner used on the model. This is a mandatory dependecy.</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.shortname">
<span class="sig-name descname"><span class="pre">shortname</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.shortname" title="Permalink to this definition"></a></dt>
<dd><p>A string with a short name or alias for the model</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.standard_horizon">
<span class="sig-name descname"><span class="pre">standard_horizon</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.standard_horizon" title="Permalink to this definition"></a></dt>
<dd><p>Standard forecasting horizon (Default: 1)</p>
</dd></dl>
Documentation update
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<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.train">
<span class="sig-name descname"><span class="pre">train</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#HighOrderFTS.train"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.train" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>Method specific parameter fitting</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – training time series data</p></li>
<li><p><strong>kwargs</strong> – Method specific parameters</p></li>
</ul>
</dd>
</dl>
</dd></dl>
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<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.transformations">
<span class="sig-name descname"><span class="pre">transformations</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference internal" href="pyFTS.common.transformations.html#pyFTS.common.transformations.transformation.Transformation" title="pyFTS.common.transformations.transformation.Transformation"><span class="pre">transformation.Transformation</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.transformations" title="Permalink to this definition"></a></dt>
<dd><p>A list with the data transformations (common.Transformations) applied on model pre and post processing, default: []</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.transformations_param">
<span class="sig-name descname"><span class="pre">transformations_param</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.transformations_param" title="Permalink to this definition"></a></dt>
<dd><p>A list with the specific parameters for each data transformation</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.HighOrderFTS.uod_clip">
<span class="sig-name descname"><span class="pre">uod_clip</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.uod_clip" title="Permalink to this definition"></a></dt>
<dd><p>Flag indicating if the test data will be clipped inside the training Universe of Discourse</p>
</dd></dl>
Documentation update
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</dd></dl>
<dl class="py class">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFLRG">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.hofts.</span></span><span class="sig-name descname"><span class="pre">WeightedHighOrderFLRG</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">order</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#WeightedHighOrderFLRG"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFLRG" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>Bases: <a class="reference internal" href="pyFTS.common.html#pyFTS.common.flrg.FLRG" title="pyFTS.common.flrg.FLRG"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.flrg.FLRG</span></code></a></p>
<p>Weighted High Order Fuzzy Logical Relationship Group</p>
<dl class="py method">
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<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFLRG.append_lhs">
<span class="sig-name descname"><span class="pre">append_lhs</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">c</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#WeightedHighOrderFLRG.append_lhs"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFLRG.append_lhs" title="Permalink to this definition"></a></dt>
Documentation update
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<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFLRG.append_rhs">
<span class="sig-name descname"><span class="pre">append_rhs</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">fset</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#WeightedHighOrderFLRG.append_rhs"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFLRG.append_rhs" title="Permalink to this definition"></a></dt>
Documentation update
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<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFLRG.get_lower">
<span class="sig-name descname"><span class="pre">get_lower</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sets</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#WeightedHighOrderFLRG.get_lower"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFLRG.get_lower" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>Returns the lower bound value for the RHS fuzzy sets</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>sets</strong> – fuzzy sets</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>lower bound value</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFLRG.get_midpoint">
<span class="sig-name descname"><span class="pre">get_midpoint</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sets</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#WeightedHighOrderFLRG.get_midpoint"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFLRG.get_midpoint" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>Returns the midpoint value for the RHS fuzzy sets</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>sets</strong> – fuzzy sets</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>the midpoint value</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFLRG.get_upper">
<span class="sig-name descname"><span class="pre">get_upper</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sets</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#WeightedHighOrderFLRG.get_upper"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFLRG.get_upper" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>Returns the upper bound value for the RHS fuzzy sets</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>sets</strong> – fuzzy sets</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>upper bound value</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFLRG.weights">
<span class="sig-name descname"><span class="pre">weights</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#WeightedHighOrderFLRG.weights"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFLRG.weights" title="Permalink to this definition"></a></dt>
Documentation update
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<dd></dd></dl>
</dd></dl>
<dl class="py class">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFTS">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.hofts.</span></span><span class="sig-name descname"><span class="pre">WeightedHighOrderFTS</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#WeightedHighOrderFTS"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>Bases: <a class="reference internal" href="#pyFTS.models.hofts.HighOrderFTS" title="pyFTS.models.hofts.HighOrderFTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.models.hofts.HighOrderFTS</span></code></a></p>
<p>Weighted High Order Fuzzy Time Series</p>
Fixing documentation and type hints
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<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFTS.alpha_cut">
<span class="sig-name descname"><span class="pre">alpha_cut</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS.alpha_cut" title="Permalink to this definition"></a></dt>
<dd><p>A float with the minimal membership to be considered on fuzzyfication process</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFTS.auto_update">
<span class="sig-name descname"><span class="pre">auto_update</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS.auto_update" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating that model is incremental</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFTS.benchmark_only">
<span class="sig-name descname"><span class="pre">benchmark_only</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS.benchmark_only" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating a façade for external (non-FTS) model used on benchmarks or ensembles.</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFTS.detail">
<span class="sig-name descname"><span class="pre">detail</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS.detail" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model detailed information</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFTS.dump">
<span class="sig-name descname"><span class="pre">dump</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS.dump" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFTS.flrgs">
<span class="sig-name descname"><span class="pre">flrgs</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.10)"><span class="pre">dict</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS.flrgs" title="Permalink to this definition"></a></dt>
<dd><p>The list of Fuzzy Logical Relationship Groups - FLRG</p>
</dd></dl>
Documentation update
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<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFTS.generate_lhs_flrg_fuzzyfied">
<span class="sig-name descname"><span class="pre">generate_lhs_flrg_fuzzyfied</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sample</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">explain</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#WeightedHighOrderFTS.generate_lhs_flrg_fuzzyfied"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS.generate_lhs_flrg_fuzzyfied" title="Permalink to this definition"></a></dt>
Documentation update
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<dd></dd></dl>
Fixing documentation and type hints
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<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFTS.has_interval_forecasting">
<span class="sig-name descname"><span class="pre">has_interval_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS.has_interval_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports interval forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFTS.has_point_forecasting">
<span class="sig-name descname"><span class="pre">has_point_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS.has_point_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports point forecasting, default: True</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFTS.has_probability_forecasting">
<span class="sig-name descname"><span class="pre">has_probability_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS.has_probability_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support probabilistic forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFTS.has_seasonality">
<span class="sig-name descname"><span class="pre">has_seasonality</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS.has_seasonality" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports seasonal indexers, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFTS.is_clustered">
<span class="sig-name descname"><span class="pre">is_clustered</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS.is_clustered" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), but works like
a monovariate method, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFTS.is_high_order">
<span class="sig-name descname"><span class="pre">is_high_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS.is_high_order" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support orders greater than 1, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFTS.is_multivariate">
<span class="sig-name descname"><span class="pre">is_multivariate</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS.is_multivariate" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFTS.is_time_variant">
<span class="sig-name descname"><span class="pre">is_time_variant</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS.is_time_variant" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if this model is time variant</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFTS.is_wrapper">
<span class="sig-name descname"><span class="pre">is_wrapper</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS.is_wrapper" title="Permalink to this definition"></a></dt>
<dd><p>Indicates that this model is a wrapper for other(s) method(s)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFTS.lags">
<span class="sig-name descname"><span class="pre">lags</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS.lags" title="Permalink to this definition"></a></dt>
<dd><p>The list of lag indexes for high order models</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFTS.log">
<span class="sig-name descname"><span class="pre">log</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">pd.DataFrame</span></em><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS.log" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFTS.max_lag">
<span class="sig-name descname"><span class="pre">max_lag</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS.max_lag" title="Permalink to this definition"></a></dt>
<dd><p>A integer indicating the largest lag used by the model. This value also indicates the minimum number of past lags
needed to forecast a single step ahead</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFTS.min_order">
<span class="sig-name descname"><span class="pre">min_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS.min_order" title="Permalink to this definition"></a></dt>
<dd><p>In high order models, this integer value indicates the minimal order supported for the model, default: 1</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFTS.name">
<span class="sig-name descname"><span class="pre">name</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS.name" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model name</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFTS.order">
<span class="sig-name descname"><span class="pre">order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS.order" title="Permalink to this definition"></a></dt>
<dd><p>A integer with the model order (number of past lags are used on forecasting)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFTS.original_max">
<span class="sig-name descname"><span class="pre">original_max</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS.original_max" title="Permalink to this definition"></a></dt>
<dd><p>A float with the upper limit of the Universe of Discourse, the maximal value found on training data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFTS.original_min">
<span class="sig-name descname"><span class="pre">original_min</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS.original_min" title="Permalink to this definition"></a></dt>
<dd><p>A float with the lower limit of the Universe of Discourse, the minimal value found on training data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFTS.partitioner">
<span class="sig-name descname"><span class="pre">partitioner</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference internal" href="pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner" title="pyFTS.partitioners.partitioner.Partitioner"><span class="pre">partitioner.Partitioner</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS.partitioner" title="Permalink to this definition"></a></dt>
<dd><p>A pyFTS.partitioners.Partitioner object with the Universe of Discourse partitioner used on the model. This is a mandatory dependecy.</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFTS.shortname">
<span class="sig-name descname"><span class="pre">shortname</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS.shortname" title="Permalink to this definition"></a></dt>
<dd><p>A string with a short name or alias for the model</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFTS.standard_horizon">
<span class="sig-name descname"><span class="pre">standard_horizon</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS.standard_horizon" title="Permalink to this definition"></a></dt>
<dd><p>Standard forecasting horizon (Default: 1)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFTS.transformations">
<span class="sig-name descname"><span class="pre">transformations</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference internal" href="pyFTS.common.transformations.html#pyFTS.common.transformations.transformation.Transformation" title="pyFTS.common.transformations.transformation.Transformation"><span class="pre">transformation.Transformation</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS.transformations" title="Permalink to this definition"></a></dt>
<dd><p>A list with the data transformations (common.Transformations) applied on model pre and post processing, default: []</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFTS.transformations_param">
<span class="sig-name descname"><span class="pre">transformations_param</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS.transformations_param" title="Permalink to this definition"></a></dt>
<dd><p>A list with the specific parameters for each data transformation</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hofts.WeightedHighOrderFTS.uod_clip">
<span class="sig-name descname"><span class="pre">uod_clip</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS.uod_clip" title="Permalink to this definition"></a></dt>
<dd><p>Flag indicating if the test data will be clipped inside the training Universe of Discourse</p>
</dd></dl>
Documentation update
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</dd></dl>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
</div>
Documentation update
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<div class="section" id="module-pyFTS.models.hwang">
<span id="pyfts-models-hwang-module"></span><h2>pyFTS.models.hwang module<a class="headerlink" href="#module-pyFTS.models.hwang" title="Permalink to this headline"></a></h2>
<p>High Order Fuzzy Time Series by Hwang, Chen and Lee (1998)</p>
<p>Jeng-Ren Hwang, Shyi-Ming Chen, and Chia-Hoang Lee, “Handling forecasting problems using fuzzy time series,”
Fuzzy Sets Syst., no. 100, pp. 217–228, 1998.</p>
<dl class="py class">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.hwang.</span></span><span class="sig-name descname"><span class="pre">HighOrderFTS</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hwang.html#HighOrderFTS"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>Bases: <a class="reference internal" href="pyFTS.common.html#pyFTS.common.fts.FTS" title="pyFTS.common.fts.FTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.fts.FTS</span></code></a></p>
Fixing documentation and type hints
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<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.alpha_cut">
<span class="sig-name descname"><span class="pre">alpha_cut</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.alpha_cut" title="Permalink to this definition"></a></dt>
<dd><p>A float with the minimal membership to be considered on fuzzyfication process</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.auto_update">
<span class="sig-name descname"><span class="pre">auto_update</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.auto_update" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating that model is incremental</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.benchmark_only">
<span class="sig-name descname"><span class="pre">benchmark_only</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.benchmark_only" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating a façade for external (non-FTS) model used on benchmarks or ensembles.</p>
</dd></dl>
Documentation update
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<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.configure_lags">
<span class="sig-name descname"><span class="pre">configure_lags</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hwang.html#HighOrderFTS.configure_lags"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.configure_lags" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
Fixing documentation and type hints
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<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.detail">
<span class="sig-name descname"><span class="pre">detail</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.detail" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model detailed information</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.dump">
<span class="sig-name descname"><span class="pre">dump</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.dump" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.flrgs">
<span class="sig-name descname"><span class="pre">flrgs</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.10)"><span class="pre">dict</span></a></em><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.flrgs" title="Permalink to this definition"></a></dt>
<dd><p>The list of Fuzzy Logical Relationship Groups - FLRG</p>
</dd></dl>
Documentation update
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<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.forecast">
<span class="sig-name descname"><span class="pre">forecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ndata</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hwang.html#HighOrderFTS.forecast"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.forecast" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>Point forecast one step ahead</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</p></li>
<li><p><strong>kwargs</strong> – model specific parameters</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a list with the forecasted values</p>
</dd>
</dl>
</dd></dl>
Fixing documentation and type hints
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<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.has_interval_forecasting">
<span class="sig-name descname"><span class="pre">has_interval_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.has_interval_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports interval forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.has_point_forecasting">
<span class="sig-name descname"><span class="pre">has_point_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.has_point_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports point forecasting, default: True</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.has_probability_forecasting">
<span class="sig-name descname"><span class="pre">has_probability_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.has_probability_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support probabilistic forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.has_seasonality">
<span class="sig-name descname"><span class="pre">has_seasonality</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.has_seasonality" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports seasonal indexers, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.is_clustered">
<span class="sig-name descname"><span class="pre">is_clustered</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.is_clustered" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), but works like
a monovariate method, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.is_high_order">
<span class="sig-name descname"><span class="pre">is_high_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.is_high_order" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support orders greater than 1, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.is_multivariate">
<span class="sig-name descname"><span class="pre">is_multivariate</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.is_multivariate" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.is_time_variant">
<span class="sig-name descname"><span class="pre">is_time_variant</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.is_time_variant" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if this model is time variant</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.is_wrapper">
<span class="sig-name descname"><span class="pre">is_wrapper</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.is_wrapper" title="Permalink to this definition"></a></dt>
<dd><p>Indicates that this model is a wrapper for other(s) method(s)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.lags">
<span class="sig-name descname"><span class="pre">lags</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.lags" title="Permalink to this definition"></a></dt>
<dd><p>The list of lag indexes for high order models</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.log">
<span class="sig-name descname"><span class="pre">log</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">pd.DataFrame</span></em><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.log" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.max_lag">
<span class="sig-name descname"><span class="pre">max_lag</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.max_lag" title="Permalink to this definition"></a></dt>
<dd><p>A integer indicating the largest lag used by the model. This value also indicates the minimum number of past lags
needed to forecast a single step ahead</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.min_order">
<span class="sig-name descname"><span class="pre">min_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.min_order" title="Permalink to this definition"></a></dt>
<dd><p>In high order models, this integer value indicates the minimal order supported for the model, default: 1</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.name">
<span class="sig-name descname"><span class="pre">name</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.name" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model name</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.order">
<span class="sig-name descname"><span class="pre">order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.order" title="Permalink to this definition"></a></dt>
<dd><p>A integer with the model order (number of past lags are used on forecasting)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.original_max">
<span class="sig-name descname"><span class="pre">original_max</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.original_max" title="Permalink to this definition"></a></dt>
<dd><p>A float with the upper limit of the Universe of Discourse, the maximal value found on training data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.original_min">
<span class="sig-name descname"><span class="pre">original_min</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.original_min" title="Permalink to this definition"></a></dt>
<dd><p>A float with the lower limit of the Universe of Discourse, the minimal value found on training data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.partitioner">
<span class="sig-name descname"><span class="pre">partitioner</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference internal" href="pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner" title="pyFTS.partitioners.partitioner.Partitioner"><span class="pre">partitioner.Partitioner</span></a></em><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.partitioner" title="Permalink to this definition"></a></dt>
<dd><p>A pyFTS.partitioners.Partitioner object with the Universe of Discourse partitioner used on the model. This is a mandatory dependecy.</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.shortname">
<span class="sig-name descname"><span class="pre">shortname</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.shortname" title="Permalink to this definition"></a></dt>
<dd><p>A string with a short name or alias for the model</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.standard_horizon">
<span class="sig-name descname"><span class="pre">standard_horizon</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.standard_horizon" title="Permalink to this definition"></a></dt>
<dd><p>Standard forecasting horizon (Default: 1)</p>
</dd></dl>
Documentation update
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<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.train">
<span class="sig-name descname"><span class="pre">train</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hwang.html#HighOrderFTS.train"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.train" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>Method specific parameter fitting</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – training time series data</p></li>
<li><p><strong>kwargs</strong> – Method specific parameters</p></li>
</ul>
</dd>
</dl>
</dd></dl>
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<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.transformations">
<span class="sig-name descname"><span class="pre">transformations</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference internal" href="pyFTS.common.transformations.html#pyFTS.common.transformations.transformation.Transformation" title="pyFTS.common.transformations.transformation.Transformation"><span class="pre">transformation.Transformation</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.transformations" title="Permalink to this definition"></a></dt>
<dd><p>A list with the data transformations (common.Transformations) applied on model pre and post processing, default: []</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.transformations_param">
<span class="sig-name descname"><span class="pre">transformations_param</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a></em><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.transformations_param" title="Permalink to this definition"></a></dt>
<dd><p>A list with the specific parameters for each data transformation</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.hwang.HighOrderFTS.uod_clip">
<span class="sig-name descname"><span class="pre">uod_clip</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.uod_clip" title="Permalink to this definition"></a></dt>
<dd><p>Flag indicating if the test data will be clipped inside the training Universe of Discourse</p>
</dd></dl>
Documentation update
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</dd></dl>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
</div>
Documentation update
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<div class="section" id="module-pyFTS.models.ifts">
<span id="pyfts-models-ifts-module"></span><h2>pyFTS.models.ifts module<a class="headerlink" href="#module-pyFTS.models.ifts" title="Permalink to this headline"></a></h2>
<p>High Order Interval Fuzzy Time Series</p>
<p>SILVA, Petrônio CL; SADAEI, Hossein Javedani; GUIMARÃES, Frederico Gadelha. Interval Forecasting with Fuzzy Time Series.
In: Computational Intelligence (SSCI), 2016 IEEE Symposium Series on. IEEE, 2016. p. 1-8.</p>
<dl class="py class">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.ifts.</span></span><span class="sig-name descname"><span class="pre">IntervalFTS</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ifts.html#IntervalFTS"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>Bases: <a class="reference internal" href="#pyFTS.models.hofts.HighOrderFTS" title="pyFTS.models.hofts.HighOrderFTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.models.hofts.HighOrderFTS</span></code></a></p>
<p>High Order Interval Fuzzy Time Series</p>
Fixing documentation and type hints
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<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.alpha_cut">
<span class="sig-name descname"><span class="pre">alpha_cut</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.alpha_cut" title="Permalink to this definition"></a></dt>
<dd><p>A float with the minimal membership to be considered on fuzzyfication process</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.auto_update">
<span class="sig-name descname"><span class="pre">auto_update</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.auto_update" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating that model is incremental</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.benchmark_only">
<span class="sig-name descname"><span class="pre">benchmark_only</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.benchmark_only" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating a façade for external (non-FTS) model used on benchmarks or ensembles.</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.detail">
<span class="sig-name descname"><span class="pre">detail</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.detail" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model detailed information</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.dump">
<span class="sig-name descname"><span class="pre">dump</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.dump" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.flrgs">
<span class="sig-name descname"><span class="pre">flrgs</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.10)"><span class="pre">dict</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.flrgs" title="Permalink to this definition"></a></dt>
<dd><p>The list of Fuzzy Logical Relationship Groups - FLRG</p>
</dd></dl>
Documentation update
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<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.forecast_ahead_interval">
<span class="sig-name descname"><span class="pre">forecast_ahead_interval</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">steps</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ifts.html#IntervalFTS.forecast_ahead_interval"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.forecast_ahead_interval" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>Interval forecast from 1 to H steps ahead, where H is given by the steps parameter</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</p></li>
<li><p><strong>steps</strong> – the number of steps ahead to forecast</p></li>
<li><p><strong>start_at</strong> – in the multi step forecasting, the index of the data where to start forecasting (default: 0)</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a list with the forecasted intervals</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.forecast_interval">
<span class="sig-name descname"><span class="pre">forecast_interval</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ndata</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ifts.html#IntervalFTS.forecast_interval"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.forecast_interval" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>Interval forecast one step ahead</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</p></li>
<li><p><strong>kwargs</strong> – model specific parameters</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a list with the prediction intervals</p>
</dd>
</dl>
</dd></dl>
Fixing documentation and type hints
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<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.get_lower">
<span class="sig-name descname"><span class="pre">get_lower</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">flrg</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ifts.html#IntervalFTS.get_lower"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.get_lower" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.get_sequence_membership">
<span class="sig-name descname"><span class="pre">get_sequence_membership</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fuzzySets</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ifts.html#IntervalFTS.get_sequence_membership"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.get_sequence_membership" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.get_upper">
<span class="sig-name descname"><span class="pre">get_upper</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">flrg</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ifts.html#IntervalFTS.get_upper"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.get_upper" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.has_interval_forecasting">
<span class="sig-name descname"><span class="pre">has_interval_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.has_interval_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports interval forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.has_point_forecasting">
<span class="sig-name descname"><span class="pre">has_point_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.has_point_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports point forecasting, default: True</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.has_probability_forecasting">
<span class="sig-name descname"><span class="pre">has_probability_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.has_probability_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support probabilistic forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.has_seasonality">
<span class="sig-name descname"><span class="pre">has_seasonality</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.has_seasonality" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports seasonal indexers, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.is_clustered">
<span class="sig-name descname"><span class="pre">is_clustered</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.is_clustered" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), but works like
a monovariate method, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.is_high_order">
<span class="sig-name descname"><span class="pre">is_high_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.is_high_order" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support orders greater than 1, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.is_multivariate">
<span class="sig-name descname"><span class="pre">is_multivariate</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.is_multivariate" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.is_time_variant">
<span class="sig-name descname"><span class="pre">is_time_variant</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.is_time_variant" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if this model is time variant</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.is_wrapper">
<span class="sig-name descname"><span class="pre">is_wrapper</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.is_wrapper" title="Permalink to this definition"></a></dt>
<dd><p>Indicates that this model is a wrapper for other(s) method(s)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.lags">
<span class="sig-name descname"><span class="pre">lags</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.lags" title="Permalink to this definition"></a></dt>
<dd><p>The list of lag indexes for high order models</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.log">
<span class="sig-name descname"><span class="pre">log</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">pd.DataFrame</span></em><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.log" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.max_lag">
<span class="sig-name descname"><span class="pre">max_lag</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.max_lag" title="Permalink to this definition"></a></dt>
<dd><p>A integer indicating the largest lag used by the model. This value also indicates the minimum number of past lags
needed to forecast a single step ahead</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.min_order">
<span class="sig-name descname"><span class="pre">min_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.min_order" title="Permalink to this definition"></a></dt>
<dd><p>In high order models, this integer value indicates the minimal order supported for the model, default: 1</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.name">
<span class="sig-name descname"><span class="pre">name</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.name" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model name</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.order">
<span class="sig-name descname"><span class="pre">order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.order" title="Permalink to this definition"></a></dt>
<dd><p>A integer with the model order (number of past lags are used on forecasting)</p>
</dd></dl>
Documentation update
2021-01-13 01:04:42 +04:00
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.original_max">
<span class="sig-name descname"><span class="pre">original_max</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.original_max" title="Permalink to this definition"></a></dt>
<dd><p>A float with the upper limit of the Universe of Discourse, the maximal value found on training data</p>
</dd></dl>
Documentation update
2021-01-13 01:04:42 +04:00
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.original_min">
<span class="sig-name descname"><span class="pre">original_min</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.original_min" title="Permalink to this definition"></a></dt>
<dd><p>A float with the lower limit of the Universe of Discourse, the minimal value found on training data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.partitioner">
<span class="sig-name descname"><span class="pre">partitioner</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference internal" href="pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner" title="pyFTS.partitioners.partitioner.Partitioner"><span class="pre">partitioner.Partitioner</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.partitioner" title="Permalink to this definition"></a></dt>
<dd><p>A pyFTS.partitioners.Partitioner object with the Universe of Discourse partitioner used on the model. This is a mandatory dependecy.</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.shortname">
<span class="sig-name descname"><span class="pre">shortname</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.shortname" title="Permalink to this definition"></a></dt>
<dd><p>A string with a short name or alias for the model</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.standard_horizon">
<span class="sig-name descname"><span class="pre">standard_horizon</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.standard_horizon" title="Permalink to this definition"></a></dt>
<dd><p>Standard forecasting horizon (Default: 1)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.transformations">
<span class="sig-name descname"><span class="pre">transformations</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference internal" href="pyFTS.common.transformations.html#pyFTS.common.transformations.transformation.Transformation" title="pyFTS.common.transformations.transformation.Transformation"><span class="pre">transformation.Transformation</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.transformations" title="Permalink to this definition"></a></dt>
<dd><p>A list with the data transformations (common.Transformations) applied on model pre and post processing, default: []</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.transformations_param">
<span class="sig-name descname"><span class="pre">transformations_param</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.transformations_param" title="Permalink to this definition"></a></dt>
<dd><p>A list with the specific parameters for each data transformation</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.IntervalFTS.uod_clip">
<span class="sig-name descname"><span class="pre">uod_clip</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.uod_clip" title="Permalink to this definition"></a></dt>
<dd><p>Flag indicating if the test data will be clipped inside the training Universe of Discourse</p>
</dd></dl>
Documentation update
2021-01-13 01:04:42 +04:00
</dd></dl>
<dl class="py class">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.ifts.</span></span><span class="sig-name descname"><span class="pre">WeightedIntervalFTS</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ifts.html#WeightedIntervalFTS"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>Bases: <a class="reference internal" href="#pyFTS.models.hofts.WeightedHighOrderFTS" title="pyFTS.models.hofts.WeightedHighOrderFTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.models.hofts.WeightedHighOrderFTS</span></code></a></p>
<p>Weighted High Order Interval Fuzzy Time Series</p>
Fixing documentation and type hints
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<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.alpha_cut">
<span class="sig-name descname"><span class="pre">alpha_cut</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.alpha_cut" title="Permalink to this definition"></a></dt>
<dd><p>A float with the minimal membership to be considered on fuzzyfication process</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.auto_update">
<span class="sig-name descname"><span class="pre">auto_update</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.auto_update" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating that model is incremental</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.benchmark_only">
<span class="sig-name descname"><span class="pre">benchmark_only</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.benchmark_only" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating a façade for external (non-FTS) model used on benchmarks or ensembles.</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.detail">
<span class="sig-name descname"><span class="pre">detail</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.detail" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model detailed information</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.dump">
<span class="sig-name descname"><span class="pre">dump</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.dump" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.flrgs">
<span class="sig-name descname"><span class="pre">flrgs</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.10)"><span class="pre">dict</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.flrgs" title="Permalink to this definition"></a></dt>
<dd><p>The list of Fuzzy Logical Relationship Groups - FLRG</p>
</dd></dl>
Documentation update
2021-01-13 01:04:42 +04:00
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.forecast_ahead_interval">
<span class="sig-name descname"><span class="pre">forecast_ahead_interval</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">steps</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ifts.html#WeightedIntervalFTS.forecast_ahead_interval"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.forecast_ahead_interval" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>Interval forecast from 1 to H steps ahead, where H is given by the steps parameter</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</p></li>
<li><p><strong>steps</strong> – the number of steps ahead to forecast</p></li>
<li><p><strong>start_at</strong> – in the multi step forecasting, the index of the data where to start forecasting (default: 0)</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a list with the forecasted intervals</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.forecast_interval">
<span class="sig-name descname"><span class="pre">forecast_interval</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ndata</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ifts.html#WeightedIntervalFTS.forecast_interval"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.forecast_interval" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>Interval forecast one step ahead</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</p></li>
<li><p><strong>kwargs</strong> – model specific parameters</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a list with the prediction intervals</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.get_lower">
<span class="sig-name descname"><span class="pre">get_lower</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">flrg</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ifts.html#WeightedIntervalFTS.get_lower"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.get_lower" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.get_sequence_membership">
<span class="sig-name descname"><span class="pre">get_sequence_membership</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fuzzySets</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ifts.html#WeightedIntervalFTS.get_sequence_membership"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.get_sequence_membership" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.get_upper">
<span class="sig-name descname"><span class="pre">get_upper</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">flrg</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ifts.html#WeightedIntervalFTS.get_upper"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.get_upper" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.has_interval_forecasting">
<span class="sig-name descname"><span class="pre">has_interval_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.has_interval_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports interval forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.has_point_forecasting">
<span class="sig-name descname"><span class="pre">has_point_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.has_point_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports point forecasting, default: True</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.has_probability_forecasting">
<span class="sig-name descname"><span class="pre">has_probability_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.has_probability_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support probabilistic forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.has_seasonality">
<span class="sig-name descname"><span class="pre">has_seasonality</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.has_seasonality" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports seasonal indexers, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.is_clustered">
<span class="sig-name descname"><span class="pre">is_clustered</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.is_clustered" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), but works like
a monovariate method, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.is_high_order">
<span class="sig-name descname"><span class="pre">is_high_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.is_high_order" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support orders greater than 1, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.is_multivariate">
<span class="sig-name descname"><span class="pre">is_multivariate</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.is_multivariate" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.is_time_variant">
<span class="sig-name descname"><span class="pre">is_time_variant</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.is_time_variant" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if this model is time variant</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.is_wrapper">
<span class="sig-name descname"><span class="pre">is_wrapper</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.is_wrapper" title="Permalink to this definition"></a></dt>
<dd><p>Indicates that this model is a wrapper for other(s) method(s)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.lags">
<span class="sig-name descname"><span class="pre">lags</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.lags" title="Permalink to this definition"></a></dt>
<dd><p>The list of lag indexes for high order models</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.log">
<span class="sig-name descname"><span class="pre">log</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">pd.DataFrame</span></em><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.log" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.max_lag">
<span class="sig-name descname"><span class="pre">max_lag</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.max_lag" title="Permalink to this definition"></a></dt>
<dd><p>A integer indicating the largest lag used by the model. This value also indicates the minimum number of past lags
needed to forecast a single step ahead</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.min_order">
<span class="sig-name descname"><span class="pre">min_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.min_order" title="Permalink to this definition"></a></dt>
<dd><p>In high order models, this integer value indicates the minimal order supported for the model, default: 1</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.name">
<span class="sig-name descname"><span class="pre">name</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.name" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model name</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.order">
<span class="sig-name descname"><span class="pre">order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.order" title="Permalink to this definition"></a></dt>
<dd><p>A integer with the model order (number of past lags are used on forecasting)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.original_max">
<span class="sig-name descname"><span class="pre">original_max</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.original_max" title="Permalink to this definition"></a></dt>
<dd><p>A float with the upper limit of the Universe of Discourse, the maximal value found on training data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.original_min">
<span class="sig-name descname"><span class="pre">original_min</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.original_min" title="Permalink to this definition"></a></dt>
<dd><p>A float with the lower limit of the Universe of Discourse, the minimal value found on training data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.partitioner">
<span class="sig-name descname"><span class="pre">partitioner</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference internal" href="pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner" title="pyFTS.partitioners.partitioner.Partitioner"><span class="pre">partitioner.Partitioner</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.partitioner" title="Permalink to this definition"></a></dt>
<dd><p>A pyFTS.partitioners.Partitioner object with the Universe of Discourse partitioner used on the model. This is a mandatory dependecy.</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.shortname">
<span class="sig-name descname"><span class="pre">shortname</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.shortname" title="Permalink to this definition"></a></dt>
<dd><p>A string with a short name or alias for the model</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.standard_horizon">
<span class="sig-name descname"><span class="pre">standard_horizon</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.standard_horizon" title="Permalink to this definition"></a></dt>
<dd><p>Standard forecasting horizon (Default: 1)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.transformations">
<span class="sig-name descname"><span class="pre">transformations</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference internal" href="pyFTS.common.transformations.html#pyFTS.common.transformations.transformation.Transformation" title="pyFTS.common.transformations.transformation.Transformation"><span class="pre">transformation.Transformation</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.transformations" title="Permalink to this definition"></a></dt>
<dd><p>A list with the data transformations (common.Transformations) applied on model pre and post processing, default: []</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.transformations_param">
<span class="sig-name descname"><span class="pre">transformations_param</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.transformations_param" title="Permalink to this definition"></a></dt>
<dd><p>A list with the specific parameters for each data transformation</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ifts.WeightedIntervalFTS.uod_clip">
<span class="sig-name descname"><span class="pre">uod_clip</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ifts.WeightedIntervalFTS.uod_clip" title="Permalink to this definition"></a></dt>
<dd><p>Flag indicating if the test data will be clipped inside the training Universe of Discourse</p>
</dd></dl>
Documentation update
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</dd></dl>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
</div>
Documentation update
2021-01-13 01:04:42 +04:00
<div class="section" id="module-pyFTS.models.ismailefendi">
<span id="pyfts-models-ismailefendi-module"></span><h2>pyFTS.models.ismailefendi module<a class="headerlink" href="#module-pyFTS.models.ismailefendi" title="Permalink to this headline"></a></h2>
<p>First Order Improved Weighted Fuzzy Time Series by Efendi, Ismail and Deris (2013)</p>
<p>R. Efendi, Z. Ismail, and M. M. Deris, “Improved weight Fuzzy Time Series as used in the exchange rates forecasting of
US Dollar to Ringgit Malaysia,” Int. J. Comput. Intell. Appl., vol. 12, no. 1, p. 1350005, 2013.</p>
<dl class="py class">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFLRG">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.ismailefendi.</span></span><span class="sig-name descname"><span class="pre">ImprovedWeightedFLRG</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">LHS</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ismailefendi.html#ImprovedWeightedFLRG"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFLRG" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>Bases: <a class="reference internal" href="pyFTS.common.html#pyFTS.common.flrg.FLRG" title="pyFTS.common.flrg.FLRG"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.flrg.FLRG</span></code></a></p>
<p>First Order Improved Weighted Fuzzy Logical Relationship Group</p>
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFLRG.append_rhs">
<span class="sig-name descname"><span class="pre">append_rhs</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">c</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ismailefendi.html#ImprovedWeightedFLRG.append_rhs"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFLRG.append_rhs" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFLRG.weights">
<span class="sig-name descname"><span class="pre">weights</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ismailefendi.html#ImprovedWeightedFLRG.weights"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFLRG.weights" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
</dd></dl>
<dl class="py class">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.ismailefendi.</span></span><span class="sig-name descname"><span class="pre">ImprovedWeightedFTS</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ismailefendi.html#ImprovedWeightedFTS"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>Bases: <a class="reference internal" href="pyFTS.common.html#pyFTS.common.fts.FTS" title="pyFTS.common.fts.FTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.fts.FTS</span></code></a></p>
<p>First Order Improved Weighted Fuzzy Time Series</p>
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.alpha_cut">
<span class="sig-name descname"><span class="pre">alpha_cut</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.alpha_cut" title="Permalink to this definition"></a></dt>
<dd><p>A float with the minimal membership to be considered on fuzzyfication process</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.auto_update">
<span class="sig-name descname"><span class="pre">auto_update</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.auto_update" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating that model is incremental</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.benchmark_only">
<span class="sig-name descname"><span class="pre">benchmark_only</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.benchmark_only" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating a façade for external (non-FTS) model used on benchmarks or ensembles.</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.detail">
<span class="sig-name descname"><span class="pre">detail</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.detail" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model detailed information</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.dump">
<span class="sig-name descname"><span class="pre">dump</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.dump" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.flrgs">
<span class="sig-name descname"><span class="pre">flrgs</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.10)"><span class="pre">dict</span></a></em><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.flrgs" title="Permalink to this definition"></a></dt>
<dd><p>The list of Fuzzy Logical Relationship Groups - FLRG</p>
</dd></dl>
Documentation update
2021-01-13 01:04:42 +04:00
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.forecast">
<span class="sig-name descname"><span class="pre">forecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ndata</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ismailefendi.html#ImprovedWeightedFTS.forecast"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.forecast" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>Point forecast one step ahead</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</p></li>
<li><p><strong>kwargs</strong> – model specific parameters</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a list with the forecasted values</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.generate_flrg">
<span class="sig-name descname"><span class="pre">generate_flrg</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">flrs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ismailefendi.html#ImprovedWeightedFTS.generate_flrg"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.generate_flrg" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.has_interval_forecasting">
<span class="sig-name descname"><span class="pre">has_interval_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.has_interval_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports interval forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.has_point_forecasting">
<span class="sig-name descname"><span class="pre">has_point_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.has_point_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports point forecasting, default: True</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.has_probability_forecasting">
<span class="sig-name descname"><span class="pre">has_probability_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.has_probability_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support probabilistic forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.has_seasonality">
<span class="sig-name descname"><span class="pre">has_seasonality</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.has_seasonality" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports seasonal indexers, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.is_clustered">
<span class="sig-name descname"><span class="pre">is_clustered</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.is_clustered" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), but works like
a monovariate method, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.is_high_order">
<span class="sig-name descname"><span class="pre">is_high_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.is_high_order" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support orders greater than 1, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.is_multivariate">
<span class="sig-name descname"><span class="pre">is_multivariate</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.is_multivariate" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.is_time_variant">
<span class="sig-name descname"><span class="pre">is_time_variant</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.is_time_variant" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if this model is time variant</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.is_wrapper">
<span class="sig-name descname"><span class="pre">is_wrapper</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.is_wrapper" title="Permalink to this definition"></a></dt>
<dd><p>Indicates that this model is a wrapper for other(s) method(s)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.lags">
<span class="sig-name descname"><span class="pre">lags</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.lags" title="Permalink to this definition"></a></dt>
<dd><p>The list of lag indexes for high order models</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.log">
<span class="sig-name descname"><span class="pre">log</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">pd.DataFrame</span></em><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.log" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.max_lag">
<span class="sig-name descname"><span class="pre">max_lag</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.max_lag" title="Permalink to this definition"></a></dt>
<dd><p>A integer indicating the largest lag used by the model. This value also indicates the minimum number of past lags
needed to forecast a single step ahead</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.min_order">
<span class="sig-name descname"><span class="pre">min_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.min_order" title="Permalink to this definition"></a></dt>
<dd><p>In high order models, this integer value indicates the minimal order supported for the model, default: 1</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.name">
<span class="sig-name descname"><span class="pre">name</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.name" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model name</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.order">
<span class="sig-name descname"><span class="pre">order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.order" title="Permalink to this definition"></a></dt>
<dd><p>A integer with the model order (number of past lags are used on forecasting)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.original_max">
<span class="sig-name descname"><span class="pre">original_max</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.original_max" title="Permalink to this definition"></a></dt>
<dd><p>A float with the upper limit of the Universe of Discourse, the maximal value found on training data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.original_min">
<span class="sig-name descname"><span class="pre">original_min</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.original_min" title="Permalink to this definition"></a></dt>
<dd><p>A float with the lower limit of the Universe of Discourse, the minimal value found on training data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.partitioner">
<span class="sig-name descname"><span class="pre">partitioner</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference internal" href="pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner" title="pyFTS.partitioners.partitioner.Partitioner"><span class="pre">partitioner.Partitioner</span></a></em><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.partitioner" title="Permalink to this definition"></a></dt>
<dd><p>A pyFTS.partitioners.Partitioner object with the Universe of Discourse partitioner used on the model. This is a mandatory dependecy.</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.shortname">
<span class="sig-name descname"><span class="pre">shortname</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.shortname" title="Permalink to this definition"></a></dt>
<dd><p>A string with a short name or alias for the model</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.standard_horizon">
<span class="sig-name descname"><span class="pre">standard_horizon</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.standard_horizon" title="Permalink to this definition"></a></dt>
<dd><p>Standard forecasting horizon (Default: 1)</p>
</dd></dl>
Documentation update
2021-01-13 01:04:42 +04:00
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.train">
<span class="sig-name descname"><span class="pre">train</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ndata</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ismailefendi.html#ImprovedWeightedFTS.train"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.train" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>Method specific parameter fitting</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – training time series data</p></li>
<li><p><strong>kwargs</strong> – Method specific parameters</p></li>
</ul>
</dd>
</dl>
</dd></dl>
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.transformations">
<span class="sig-name descname"><span class="pre">transformations</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference internal" href="pyFTS.common.transformations.html#pyFTS.common.transformations.transformation.Transformation" title="pyFTS.common.transformations.transformation.Transformation"><span class="pre">transformation.Transformation</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.transformations" title="Permalink to this definition"></a></dt>
<dd><p>A list with the data transformations (common.Transformations) applied on model pre and post processing, default: []</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.transformations_param">
<span class="sig-name descname"><span class="pre">transformations_param</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a></em><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.transformations_param" title="Permalink to this definition"></a></dt>
<dd><p>A list with the specific parameters for each data transformation</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.uod_clip">
<span class="sig-name descname"><span class="pre">uod_clip</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.uod_clip" title="Permalink to this definition"></a></dt>
<dd><p>Flag indicating if the test data will be clipped inside the training Universe of Discourse</p>
</dd></dl>
Documentation update
2021-01-13 01:04:42 +04:00
</dd></dl>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
</div>
Documentation update
2021-01-13 01:04:42 +04:00
<div class="section" id="module-pyFTS.models.pwfts">
<span id="pyfts-models-pwfts-module"></span><h2>pyFTS.models.pwfts module<a class="headerlink" href="#module-pyFTS.models.pwfts" title="Permalink to this headline"></a></h2>
<dl class="py class">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFLRG">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.pwfts.</span></span><span class="sig-name descname"><span class="pre">ProbabilisticWeightedFLRG</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">order</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFLRG"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFLRG" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>Bases: <a class="reference internal" href="#pyFTS.models.hofts.HighOrderFLRG" title="pyFTS.models.hofts.HighOrderFLRG"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.models.hofts.HighOrderFLRG</span></code></a></p>
<p>High Order Probabilistic Weighted Fuzzy Logical Relationship Group</p>
<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFLRG.append_rhs">
<span class="sig-name descname"><span class="pre">append_rhs</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">c</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFLRG.append_rhs"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.append_rhs" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFLRG.get_lower">
<span class="sig-name descname"><span class="pre">get_lower</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sets</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFLRG.get_lower"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.get_lower" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>Returns the lower bound value for the RHS fuzzy sets</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>sets</strong> – fuzzy sets</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>lower bound value</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFLRG.get_membership">
<span class="sig-name descname"><span class="pre">get_membership</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sets</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFLRG.get_membership"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.get_membership" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>Returns the membership value of the FLRG for the input data</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – input data</p></li>
<li><p><strong>sets</strong> – fuzzy sets</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>the membership value</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFLRG.get_midpoint">
<span class="sig-name descname"><span class="pre">get_midpoint</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sets</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFLRG.get_midpoint"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.get_midpoint" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>Return the expectation of the PWFLRG, the weighted sum</p>
</dd></dl>
<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFLRG.get_upper">
<span class="sig-name descname"><span class="pre">get_upper</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sets</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFLRG.get_upper"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.get_upper" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>Returns the upper bound value for the RHS fuzzy sets</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>sets</strong> – fuzzy sets</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>upper bound value</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFLRG.lhs_conditional_probability">
<span class="sig-name descname"><span class="pre">lhs_conditional_probability</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sets</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">norm</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">uod</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nbins</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFLRG.lhs_conditional_probability"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.lhs_conditional_probability" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFLRG.lhs_conditional_probability_fuzzyfied">
<span class="sig-name descname"><span class="pre">lhs_conditional_probability_fuzzyfied</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">lhs_mv</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sets</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">norm</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">uod</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nbins</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFLRG.lhs_conditional_probability_fuzzyfied"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.lhs_conditional_probability_fuzzyfied" title="Permalink to this definition"></a></dt>
Documentation update
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<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFLRG.partition_function">
<span class="sig-name descname"><span class="pre">partition_function</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sets</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">uod</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nbins</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">100</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFLRG.partition_function"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.partition_function" title="Permalink to this definition"></a></dt>
Documentation update
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<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFLRG.rhs_conditional_probability">
<span class="sig-name descname"><span class="pre">rhs_conditional_probability</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sets</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">uod</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nbins</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFLRG.rhs_conditional_probability"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.rhs_conditional_probability" title="Permalink to this definition"></a></dt>
Documentation update
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<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFLRG.rhs_unconditional_probability">
<span class="sig-name descname"><span class="pre">rhs_unconditional_probability</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">c</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFLRG.rhs_unconditional_probability"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.rhs_unconditional_probability" title="Permalink to this definition"></a></dt>
Documentation update
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<dd></dd></dl>
</dd></dl>
<dl class="py class">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.pwfts.</span></span><span class="sig-name descname"><span class="pre">ProbabilisticWeightedFTS</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>Bases: <a class="reference internal" href="#pyFTS.models.ifts.IntervalFTS" title="pyFTS.models.ifts.IntervalFTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.models.ifts.IntervalFTS</span></code></a></p>
<p>High Order Probabilistic Weighted Fuzzy Time Series</p>
<dl class="py method">
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<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.add_new_PWFLGR">
<span class="sig-name descname"><span class="pre">add_new_PWFLGR</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">flrg</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.add_new_PWFLGR"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.add_new_PWFLGR" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.alpha_cut">
<span class="sig-name descname"><span class="pre">alpha_cut</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.alpha_cut" title="Permalink to this definition"></a></dt>
<dd><p>A float with the minimal membership to be considered on fuzzyfication process</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.auto_update">
<span class="sig-name descname"><span class="pre">auto_update</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.auto_update" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating that model is incremental</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.benchmark_only">
<span class="sig-name descname"><span class="pre">benchmark_only</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.benchmark_only" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating a façade for external (non-FTS) model used on benchmarks or ensembles.</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.detail">
<span class="sig-name descname"><span class="pre">detail</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.detail" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model detailed information</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.dump">
<span class="sig-name descname"><span class="pre">dump</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.dump" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.flrg_lhs_conditional_probability">
<span class="sig-name descname"><span class="pre">flrg_lhs_conditional_probability</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">flrg</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.flrg_lhs_conditional_probability"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.flrg_lhs_conditional_probability" title="Permalink to this definition"></a></dt>
Documentation update
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<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.flrg_lhs_conditional_probability_fuzzyfied">
<span class="sig-name descname"><span class="pre">flrg_lhs_conditional_probability_fuzzyfied</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">flrg</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.flrg_lhs_conditional_probability_fuzzyfied"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.flrg_lhs_conditional_probability_fuzzyfied" title="Permalink to this definition"></a></dt>
Documentation update
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<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.flrg_lhs_unconditional_probability">
<span class="sig-name descname"><span class="pre">flrg_lhs_unconditional_probability</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">flrg</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.flrg_lhs_unconditional_probability"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.flrg_lhs_unconditional_probability" title="Permalink to this definition"></a></dt>
Documentation update
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<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.flrg_rhs_conditional_probability">
<span class="sig-name descname"><span class="pre">flrg_rhs_conditional_probability</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">flrg</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.flrg_rhs_conditional_probability"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.flrg_rhs_conditional_probability" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.flrgs">
<span class="sig-name descname"><span class="pre">flrgs</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.10)"><span class="pre">dict</span></a></em><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.flrgs" title="Permalink to this definition"></a></dt>
<dd><p>The list of Fuzzy Logical Relationship Groups - FLRG</p>
</dd></dl>
Documentation update
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<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast">
<span class="sig-name descname"><span class="pre">forecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.forecast"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>Point forecast one step ahead</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</p></li>
<li><p><strong>kwargs</strong> – model specific parameters</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a list with the forecasted values</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast_ahead">
<span class="sig-name descname"><span class="pre">forecast_ahead</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">steps</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.forecast_ahead"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast_ahead" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>Point forecast from 1 to H steps ahead, where H is given by the steps parameter</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</p></li>
<li><p><strong>steps</strong> – the number of steps ahead to forecast (default: 1)</p></li>
<li><p><strong>start_at</strong> – in the multi step forecasting, the index of the data where to start forecasting (default: 0)</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a list with the forecasted values</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast_ahead_distribution">
<span class="sig-name descname"><span class="pre">forecast_ahead_distribution</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ndata</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">steps</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.forecast_ahead_distribution"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast_ahead_distribution" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>Probabilistic forecast from 1 to H steps ahead, where H is given by the steps parameter</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</p></li>
<li><p><strong>steps</strong> – the number of steps ahead to forecast</p></li>
<li><p><strong>start_at</strong> – in the multi step forecasting, the index of the data where to start forecasting (default: 0)</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a list with the forecasted Probability Distributions</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast_ahead_interval">
<span class="sig-name descname"><span class="pre">forecast_ahead_interval</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">steps</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.forecast_ahead_interval"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast_ahead_interval" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>Interval forecast from 1 to H steps ahead, where H is given by the steps parameter</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</p></li>
<li><p><strong>steps</strong> – the number of steps ahead to forecast</p></li>
<li><p><strong>start_at</strong> – in the multi step forecasting, the index of the data where to start forecasting (default: 0)</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a list with the forecasted intervals</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast_distribution">
<span class="sig-name descname"><span class="pre">forecast_distribution</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ndata</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.forecast_distribution"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast_distribution" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>Probabilistic forecast one step ahead</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</p></li>
<li><p><strong>kwargs</strong> – model specific parameters</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a list with probabilistic.ProbabilityDistribution objects representing the forecasted Probability Distributions</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast_distribution_from_distribution">
<span class="sig-name descname"><span class="pre">forecast_distribution_from_distribution</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">previous_dist</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">smooth</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">uod</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bins</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.forecast_distribution_from_distribution"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast_distribution_from_distribution" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast_interval">
<span class="sig-name descname"><span class="pre">forecast_interval</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ndata</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.forecast_interval"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast_interval" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>Interval forecast one step ahead</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</p></li>
<li><p><strong>kwargs</strong> – model specific parameters</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a list with the prediction intervals</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.generate_flrg">
<span class="sig-name descname"><span class="pre">generate_flrg</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.generate_flrg"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.generate_flrg" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.generate_flrg2">
<span class="sig-name descname"><span class="pre">generate_flrg2</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.generate_flrg2"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.generate_flrg2" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.generate_flrg_fuzzyfied">
<span class="sig-name descname"><span class="pre">generate_flrg_fuzzyfied</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.generate_flrg_fuzzyfied"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.generate_flrg_fuzzyfied" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.generate_lhs_flrg">
<span class="sig-name descname"><span class="pre">generate_lhs_flrg</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sample</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">explain</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.generate_lhs_flrg"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.generate_lhs_flrg" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.generate_lhs_flrg_fuzzyfied">
<span class="sig-name descname"><span class="pre">generate_lhs_flrg_fuzzyfied</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sample</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">explain</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.generate_lhs_flrg_fuzzyfied"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.generate_lhs_flrg_fuzzyfied" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.get_lower">
<span class="sig-name descname"><span class="pre">get_lower</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">flrg</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.get_lower"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.get_lower" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.get_midpoint">
<span class="sig-name descname"><span class="pre">get_midpoint</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">flrg</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.get_midpoint"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.get_midpoint" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.get_sets_from_both_fuzzyfication">
<span class="sig-name descname"><span class="pre">get_sets_from_both_fuzzyfication</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sample</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.get_sets_from_both_fuzzyfication"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.get_sets_from_both_fuzzyfication" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.get_upper">
<span class="sig-name descname"><span class="pre">get_upper</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">flrg</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.get_upper"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.get_upper" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.has_interval_forecasting">
<span class="sig-name descname"><span class="pre">has_interval_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.has_interval_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports interval forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.has_point_forecasting">
<span class="sig-name descname"><span class="pre">has_point_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.has_point_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports point forecasting, default: True</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.has_probability_forecasting">
<span class="sig-name descname"><span class="pre">has_probability_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.has_probability_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support probabilistic forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.has_seasonality">
<span class="sig-name descname"><span class="pre">has_seasonality</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.has_seasonality" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports seasonal indexers, default: False</p>
</dd></dl>
Documentation update
2021-01-13 01:04:42 +04:00
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.interval_heuristic">
<span class="sig-name descname"><span class="pre">interval_heuristic</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sample</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.interval_heuristic"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.interval_heuristic" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.interval_quantile">
<span class="sig-name descname"><span class="pre">interval_quantile</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ndata</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.interval_quantile"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.interval_quantile" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.is_clustered">
<span class="sig-name descname"><span class="pre">is_clustered</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.is_clustered" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), but works like
a monovariate method, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.is_high_order">
<span class="sig-name descname"><span class="pre">is_high_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.is_high_order" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support orders greater than 1, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.is_multivariate">
<span class="sig-name descname"><span class="pre">is_multivariate</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.is_multivariate" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.is_time_variant">
<span class="sig-name descname"><span class="pre">is_time_variant</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.is_time_variant" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if this model is time variant</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.is_wrapper">
<span class="sig-name descname"><span class="pre">is_wrapper</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.is_wrapper" title="Permalink to this definition"></a></dt>
<dd><p>Indicates that this model is a wrapper for other(s) method(s)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.lags">
<span class="sig-name descname"><span class="pre">lags</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.lags" title="Permalink to this definition"></a></dt>
<dd><p>The list of lag indexes for high order models</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.log">
<span class="sig-name descname"><span class="pre">log</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">pd.DataFrame</span></em><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.log" title="Permalink to this definition"></a></dt>
Documentation update
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<dd></dd></dl>
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.max_lag">
<span class="sig-name descname"><span class="pre">max_lag</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.max_lag" title="Permalink to this definition"></a></dt>
<dd><p>A integer indicating the largest lag used by the model. This value also indicates the minimum number of past lags
needed to forecast a single step ahead</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.min_order">
<span class="sig-name descname"><span class="pre">min_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.min_order" title="Permalink to this definition"></a></dt>
<dd><p>In high order models, this integer value indicates the minimal order supported for the model, default: 1</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.name">
<span class="sig-name descname"><span class="pre">name</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.name" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model name</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.order">
<span class="sig-name descname"><span class="pre">order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.order" title="Permalink to this definition"></a></dt>
<dd><p>A integer with the model order (number of past lags are used on forecasting)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.original_max">
<span class="sig-name descname"><span class="pre">original_max</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.original_max" title="Permalink to this definition"></a></dt>
<dd><p>A float with the upper limit of the Universe of Discourse, the maximal value found on training data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.original_min">
<span class="sig-name descname"><span class="pre">original_min</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.original_min" title="Permalink to this definition"></a></dt>
<dd><p>A float with the lower limit of the Universe of Discourse, the minimal value found on training data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.partitioner">
<span class="sig-name descname"><span class="pre">partitioner</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference internal" href="pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner" title="pyFTS.partitioners.partitioner.Partitioner"><span class="pre">partitioner.Partitioner</span></a></em><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.partitioner" title="Permalink to this definition"></a></dt>
<dd><p>A pyFTS.partitioners.Partitioner object with the Universe of Discourse partitioner used on the model. This is a mandatory dependecy.</p>
</dd></dl>
Documentation update
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<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.point_expected_value">
<span class="sig-name descname"><span class="pre">point_expected_value</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sample</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.point_expected_value"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.point_expected_value" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.point_heuristic">
<span class="sig-name descname"><span class="pre">point_heuristic</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sample</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.point_heuristic"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.point_heuristic" title="Permalink to this definition"></a></dt>
Documentation update
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<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.pwflrg_lhs_memberhip_fuzzyfied">
<span class="sig-name descname"><span class="pre">pwflrg_lhs_memberhip_fuzzyfied</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">flrg</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sample</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.pwflrg_lhs_memberhip_fuzzyfied"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.pwflrg_lhs_memberhip_fuzzyfied" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.shortname">
<span class="sig-name descname"><span class="pre">shortname</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.shortname" title="Permalink to this definition"></a></dt>
<dd><p>A string with a short name or alias for the model</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.standard_horizon">
<span class="sig-name descname"><span class="pre">standard_horizon</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.standard_horizon" title="Permalink to this definition"></a></dt>
<dd><p>Standard forecasting horizon (Default: 1)</p>
</dd></dl>
Documentation update
2021-01-13 01:04:42 +04:00
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.train">
<span class="sig-name descname"><span class="pre">train</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.train"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.train" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>Method specific parameter fitting</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – training time series data</p></li>
<li><p><strong>kwargs</strong> – Method specific parameters</p></li>
</ul>
</dd>
</dl>
</dd></dl>
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.transformations">
<span class="sig-name descname"><span class="pre">transformations</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference internal" href="pyFTS.common.transformations.html#pyFTS.common.transformations.transformation.Transformation" title="pyFTS.common.transformations.transformation.Transformation"><span class="pre">transformation.Transformation</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.transformations" title="Permalink to this definition"></a></dt>
<dd><p>A list with the data transformations (common.Transformations) applied on model pre and post processing, default: []</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.transformations_param">
<span class="sig-name descname"><span class="pre">transformations_param</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a></em><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.transformations_param" title="Permalink to this definition"></a></dt>
<dd><p>A list with the specific parameters for each data transformation</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.uod_clip">
<span class="sig-name descname"><span class="pre">uod_clip</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.uod_clip" title="Permalink to this definition"></a></dt>
<dd><p>Flag indicating if the test data will be clipped inside the training Universe of Discourse</p>
</dd></dl>
Documentation update
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<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.update_model">
<span class="sig-name descname"><span class="pre">update_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.update_model"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.update_model" title="Permalink to this definition"></a></dt>
Documentation update
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<dd></dd></dl>
</dd></dl>
<dl class="py function">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.pwfts.highorder_fuzzy_markov_chain">
<span class="sig-prename descclassname"><span class="pre">pyFTS.models.pwfts.</span></span><span class="sig-name descname"><span class="pre">highorder_fuzzy_markov_chain</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#highorder_fuzzy_markov_chain"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.highorder_fuzzy_markov_chain" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="pyFTS.models.pwfts.visualize_distributions">
<span class="sig-prename descclassname"><span class="pre">pyFTS.models.pwfts.</span></span><span class="sig-name descname"><span class="pre">visualize_distributions</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#visualize_distributions"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.pwfts.visualize_distributions" title="Permalink to this definition"></a></dt>
Documentation update
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<dd></dd></dl>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
</div>
Documentation update
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<div class="section" id="module-pyFTS.models.sadaei">
<span id="pyfts-models-sadaei-module"></span><h2>pyFTS.models.sadaei module<a class="headerlink" href="#module-pyFTS.models.sadaei" title="Permalink to this headline"></a></h2>
<p>First Order Exponentialy Weighted Fuzzy Time Series by Sadaei et al. (2013)</p>
<p>H. J. Sadaei, R. Enayatifar, A. H. Abdullah, and A. Gani, “Short-term load forecasting using a hybrid model with a
refined exponentially weighted fuzzy time series and an improved harmony search,” Int. J. Electr. Power Energy Syst., vol. 62, no. from 2005, pp. 118–129, 2014.</p>
<dl class="py class">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFLRG">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.sadaei.</span></span><span class="sig-name descname"><span class="pre">ExponentialyWeightedFLRG</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">LHS</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/sadaei.html#ExponentialyWeightedFLRG"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFLRG" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>Bases: <a class="reference internal" href="pyFTS.common.html#pyFTS.common.flrg.FLRG" title="pyFTS.common.flrg.FLRG"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.flrg.FLRG</span></code></a></p>
<p>First Order Exponentialy Weighted Fuzzy Logical Relationship Group</p>
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFLRG.append_rhs">
<span class="sig-name descname"><span class="pre">append_rhs</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">c</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/sadaei.html#ExponentialyWeightedFLRG.append_rhs"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFLRG.append_rhs" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFLRG.weights">
<span class="sig-name descname"><span class="pre">weights</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/sadaei.html#ExponentialyWeightedFLRG.weights"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFLRG.weights" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
</dd></dl>
<dl class="py class">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.sadaei.</span></span><span class="sig-name descname"><span class="pre">ExponentialyWeightedFTS</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/sadaei.html#ExponentialyWeightedFTS"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>Bases: <a class="reference internal" href="pyFTS.common.html#pyFTS.common.fts.FTS" title="pyFTS.common.fts.FTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.fts.FTS</span></code></a></p>
<p>First Order Exponentialy Weighted Fuzzy Time Series</p>
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.alpha_cut">
<span class="sig-name descname"><span class="pre">alpha_cut</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.alpha_cut" title="Permalink to this definition"></a></dt>
<dd><p>A float with the minimal membership to be considered on fuzzyfication process</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.auto_update">
<span class="sig-name descname"><span class="pre">auto_update</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.auto_update" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating that model is incremental</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.benchmark_only">
<span class="sig-name descname"><span class="pre">benchmark_only</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.benchmark_only" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating a façade for external (non-FTS) model used on benchmarks or ensembles.</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.detail">
<span class="sig-name descname"><span class="pre">detail</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.detail" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model detailed information</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.dump">
<span class="sig-name descname"><span class="pre">dump</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.dump" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.flrgs">
<span class="sig-name descname"><span class="pre">flrgs</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.10)"><span class="pre">dict</span></a></em><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.flrgs" title="Permalink to this definition"></a></dt>
<dd><p>The list of Fuzzy Logical Relationship Groups - FLRG</p>
</dd></dl>
Documentation update
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<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.forecast">
<span class="sig-name descname"><span class="pre">forecast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ndata</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/sadaei.html#ExponentialyWeightedFTS.forecast"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.forecast" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>Point forecast one step ahead</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</p></li>
<li><p><strong>kwargs</strong> – model specific parameters</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a list with the forecasted values</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.generate_flrg">
<span class="sig-name descname"><span class="pre">generate_flrg</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">flrs</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">c</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/sadaei.html#ExponentialyWeightedFTS.generate_flrg"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.generate_flrg" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.has_interval_forecasting">
<span class="sig-name descname"><span class="pre">has_interval_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.has_interval_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports interval forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.has_point_forecasting">
<span class="sig-name descname"><span class="pre">has_point_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.has_point_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports point forecasting, default: True</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.has_probability_forecasting">
<span class="sig-name descname"><span class="pre">has_probability_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.has_probability_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support probabilistic forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.has_seasonality">
<span class="sig-name descname"><span class="pre">has_seasonality</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.has_seasonality" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports seasonal indexers, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.is_clustered">
<span class="sig-name descname"><span class="pre">is_clustered</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.is_clustered" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), but works like
a monovariate method, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.is_high_order">
<span class="sig-name descname"><span class="pre">is_high_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.is_high_order" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support orders greater than 1, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.is_multivariate">
<span class="sig-name descname"><span class="pre">is_multivariate</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.is_multivariate" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.is_time_variant">
<span class="sig-name descname"><span class="pre">is_time_variant</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.is_time_variant" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if this model is time variant</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.is_wrapper">
<span class="sig-name descname"><span class="pre">is_wrapper</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.is_wrapper" title="Permalink to this definition"></a></dt>
<dd><p>Indicates that this model is a wrapper for other(s) method(s)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.lags">
<span class="sig-name descname"><span class="pre">lags</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.lags" title="Permalink to this definition"></a></dt>
<dd><p>The list of lag indexes for high order models</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.log">
<span class="sig-name descname"><span class="pre">log</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">pd.DataFrame</span></em><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.log" title="Permalink to this definition"></a></dt>
Documentation update
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<dd></dd></dl>
Fixing documentation and type hints
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<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.max_lag">
<span class="sig-name descname"><span class="pre">max_lag</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.max_lag" title="Permalink to this definition"></a></dt>
<dd><p>A integer indicating the largest lag used by the model. This value also indicates the minimum number of past lags
needed to forecast a single step ahead</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.min_order">
<span class="sig-name descname"><span class="pre">min_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.min_order" title="Permalink to this definition"></a></dt>
<dd><p>In high order models, this integer value indicates the minimal order supported for the model, default: 1</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.name">
<span class="sig-name descname"><span class="pre">name</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.name" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model name</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.order">
<span class="sig-name descname"><span class="pre">order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.order" title="Permalink to this definition"></a></dt>
<dd><p>A integer with the model order (number of past lags are used on forecasting)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.original_max">
<span class="sig-name descname"><span class="pre">original_max</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.original_max" title="Permalink to this definition"></a></dt>
<dd><p>A float with the upper limit of the Universe of Discourse, the maximal value found on training data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.original_min">
<span class="sig-name descname"><span class="pre">original_min</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.original_min" title="Permalink to this definition"></a></dt>
<dd><p>A float with the lower limit of the Universe of Discourse, the minimal value found on training data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.partitioner">
<span class="sig-name descname"><span class="pre">partitioner</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference internal" href="pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner" title="pyFTS.partitioners.partitioner.Partitioner"><span class="pre">partitioner.Partitioner</span></a></em><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.partitioner" title="Permalink to this definition"></a></dt>
<dd><p>A pyFTS.partitioners.Partitioner object with the Universe of Discourse partitioner used on the model. This is a mandatory dependecy.</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.shortname">
<span class="sig-name descname"><span class="pre">shortname</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.shortname" title="Permalink to this definition"></a></dt>
<dd><p>A string with a short name or alias for the model</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.standard_horizon">
<span class="sig-name descname"><span class="pre">standard_horizon</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.standard_horizon" title="Permalink to this definition"></a></dt>
<dd><p>Standard forecasting horizon (Default: 1)</p>
</dd></dl>
Documentation update
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<dl class="py method">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.train">
<span class="sig-name descname"><span class="pre">train</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/sadaei.html#ExponentialyWeightedFTS.train"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.train" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>Method specific parameter fitting</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – training time series data</p></li>
<li><p><strong>kwargs</strong> – Method specific parameters</p></li>
</ul>
</dd>
</dl>
</dd></dl>
Fixing documentation and type hints
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<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.transformations">
<span class="sig-name descname"><span class="pre">transformations</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference internal" href="pyFTS.common.transformations.html#pyFTS.common.transformations.transformation.Transformation" title="pyFTS.common.transformations.transformation.Transformation"><span class="pre">transformation.Transformation</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.transformations" title="Permalink to this definition"></a></dt>
<dd><p>A list with the data transformations (common.Transformations) applied on model pre and post processing, default: []</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.transformations_param">
<span class="sig-name descname"><span class="pre">transformations_param</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a></em><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.transformations_param" title="Permalink to this definition"></a></dt>
<dd><p>A list with the specific parameters for each data transformation</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.sadaei.ExponentialyWeightedFTS.uod_clip">
<span class="sig-name descname"><span class="pre">uod_clip</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.uod_clip" title="Permalink to this definition"></a></dt>
<dd><p>Flag indicating if the test data will be clipped inside the training Universe of Discourse</p>
</dd></dl>
Documentation update
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</dd></dl>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
</div>
</div>
Documentation update
2020-08-19 00:06:41 +04:00
<div class="clearer"></div>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
</div>
</div>
</div>
Documentation update
2020-08-19 00:06:41 +04:00
<div class="sphinxsidebar" role="navigation" aria-label="main navigation">
<div class="sphinxsidebarwrapper">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<div>
<h3><a href="index.html">Table of Contents</a></h3>
<ul>
Documentation update
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<li><a class="reference internal" href="#">pyFTS.models package</a><ul>
<li><a class="reference internal" href="#module-pyFTS.models">Module contents</a></li>
<li><a class="reference internal" href="#subpackages">Subpackages</a></li>
<li><a class="reference internal" href="#submodules">Submodules</a></li>
Documentation update
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<li><a class="reference internal" href="#module-pyFTS.models.song">pyFTS.models.song module</a></li>
<li><a class="reference internal" href="#module-pyFTS.models.chen">pyFTS.models.chen module</a></li>
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