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<div class="section" id="pyfts-models-incremental-package">
<h1>pyFTS.models.incremental package<a class="headerlink" href="#pyfts-models-incremental-package" title="Permalink to this headline"></a></h1>
<div class="section" id="module-pyFTS.models.incremental">
<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-pyFTS.models.incremental" title="Permalink to this headline"></a></h2>
<p>FTS methods with incremental/online learning</p>
</div>
<div class="section" id="submodules">
<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this headline"></a></h2>
</div>
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<div class="section" id="module-pyFTS.models.incremental.TimeVariant">
<span id="pyfts-models-incremental-timevariant-module"></span><h2>pyFTS.models.incremental.TimeVariant module<a class="headerlink" href="#module-pyFTS.models.incremental.TimeVariant" title="Permalink to this headline"></a></h2>
<p>Meta model that wraps another FTS method and continously retrain it using a data window with
the most recent data</p>
<dl class="py class">
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<dt class="sig sig-object py" id="pyFTS.models.incremental.TimeVariant.Retrainer">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.incremental.TimeVariant.</span></span><span class="sig-name descname"><span class="pre">Retrainer</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/incremental/TimeVariant.html#Retrainer"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.incremental.TimeVariant.Retrainer" 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>Meta model for incremental/online learning that retrain its internal model after
data windows controlled by the parameter ‘batch_size’, using as the training data a
window of recent lags, whose size is controlled by the parameter ‘window_length’.</p>
<dl class="py attribute">
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<dt class="sig sig-object py" id="pyFTS.models.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.auto_update" title="Permalink to this definition"></a></dt>
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<dd><p>If true the model is updated at each time and not recreated</p>
</dd></dl>
<dl class="py attribute">
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<dt class="sig sig-object py" id="pyFTS.models.incremental.TimeVariant.Retrainer.batch_size">
<span class="sig-name descname"><span class="pre">batch_size</span></span><a class="headerlink" href="#pyFTS.models.incremental.TimeVariant.Retrainer.batch_size" title="Permalink to this definition"></a></dt>
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<dd><p>The batch interval between each retraining</p>
</dd></dl>
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<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.dump" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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/incremental/TimeVariant.html#Retrainer.forecast"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.incremental.TimeVariant.Retrainer.forecast" title="Permalink to this definition"></a></dt>
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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">
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<dt class="sig sig-object py" id="pyFTS.models.incremental.TimeVariant.Retrainer.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/incremental/TimeVariant.html#Retrainer.forecast_ahead"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.incremental.TimeVariant.Retrainer.forecast_ahead" title="Permalink to this definition"></a></dt>
Documentation update
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<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 attribute">
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<dt class="sig sig-object py" id="pyFTS.models.incremental.TimeVariant.Retrainer.fts_method">
<span class="sig-name descname"><span class="pre">fts_method</span></span><a class="headerlink" href="#pyFTS.models.incremental.TimeVariant.Retrainer.fts_method" title="Permalink to this definition"></a></dt>
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<dd><p>The FTS method to be called when a new model is build</p>
</dd></dl>
<dl class="py attribute">
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<dt class="sig sig-object py" id="pyFTS.models.incremental.TimeVariant.Retrainer.fts_params">
<span class="sig-name descname"><span class="pre">fts_params</span></span><a class="headerlink" href="#pyFTS.models.incremental.TimeVariant.Retrainer.fts_params" title="Permalink to this definition"></a></dt>
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<dd><p>The FTS method specific parameters</p>
</dd></dl>
<dl class="py attribute">
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<dt class="sig sig-object py" id="pyFTS.models.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.log" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.model">
<span class="sig-name descname"><span class="pre">model</span></span><a class="headerlink" href="#pyFTS.models.incremental.TimeVariant.Retrainer.model" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>The most recent trained model</p>
</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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.incremental.TimeVariant.Retrainer.offset">
<span class="sig-name descname"><span class="pre">offset</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/incremental/TimeVariant.html#Retrainer.offset"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.incremental.TimeVariant.Retrainer.offset" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>Returns the number of lags to skip in the input test data in order to synchronize it with
the forecasted values given by the predict function. This is necessary due to the order of the
model, among other parameters.</p>
<dl class="field-list simple">
<dt class="field-odd">Returns</dt>
<dd class="field-odd"><p>An integer with the number of lags to skip</p>
</dd>
</dl>
</dd></dl>
<dl class="py attribute">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.partitioner" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>The most recent trained partitioner</p>
</dd></dl>
<dl class="py attribute">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.incremental.TimeVariant.Retrainer.partitioner_method">
<span class="sig-name descname"><span class="pre">partitioner_method</span></span><a class="headerlink" href="#pyFTS.models.incremental.TimeVariant.Retrainer.partitioner_method" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>The partitioner method to be called when a new model is build</p>
</dd></dl>
<dl class="py attribute">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.incremental.TimeVariant.Retrainer.partitioner_params">
<span class="sig-name descname"><span class="pre">partitioner_params</span></span><a class="headerlink" href="#pyFTS.models.incremental.TimeVariant.Retrainer.partitioner_params" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>The partitioner method parameters</p>
</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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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/incremental/TimeVariant.html#Retrainer.train"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.incremental.TimeVariant.Retrainer.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>
<dl class="py attribute">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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.incremental.TimeVariant.Retrainer.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>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.incremental.TimeVariant.Retrainer.window_length">
<span class="sig-name descname"><span class="pre">window_length</span></span><a class="headerlink" href="#pyFTS.models.incremental.TimeVariant.Retrainer.window_length" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>The memory window length</p>
</dd></dl>
</dd></dl>
Updating the documentation
2019-02-21 19:00:09 +04:00
</div>
Documentation update
2021-01-13 01:04:42 +04:00
<div class="section" id="module-pyFTS.models.incremental.IncrementalEnsemble">
<span id="pyfts-models-incremental-incrementalensemble-module"></span><h2>pyFTS.models.incremental.IncrementalEnsemble module<a class="headerlink" href="#module-pyFTS.models.incremental.IncrementalEnsemble" title="Permalink to this headline"></a></h2>
<p>Time Variant/Incremental Ensemble of FTS methods</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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.incremental.IncrementalEnsemble.</span></span><span class="sig-name descname"><span class="pre">IncrementalEnsembleFTS</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/incremental/IncrementalEnsemble.html#IncrementalEnsembleFTS"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS" 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.ensemble.html#pyFTS.models.ensemble.ensemble.EnsembleFTS" title="pyFTS.models.ensemble.ensemble.EnsembleFTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.models.ensemble.ensemble.EnsembleFTS</span></code></a></p>
<p>Time Variant/Incremental Ensemble of FTS methods</p>
<dl class="py attribute">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.batch_size">
<span class="sig-name descname"><span class="pre">batch_size</span></span><a class="headerlink" href="#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.batch_size" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>The batch interval between each retraining</p>
</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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.dump" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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/incremental/IncrementalEnsemble.html#IncrementalEnsembleFTS.forecast"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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/incremental/IncrementalEnsemble.html#IncrementalEnsembleFTS.forecast_ahead"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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 attribute">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.fts_method">
<span class="sig-name descname"><span class="pre">fts_method</span></span><a class="headerlink" href="#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.fts_method" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>The FTS method to be called when a new model is build</p>
</dd></dl>
<dl class="py attribute">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.fts_params">
<span class="sig-name descname"><span class="pre">fts_params</span></span><a class="headerlink" href="#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.fts_params" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>The FTS method specific parameters</p>
</dd></dl>
<dl class="py attribute">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.log" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.num_models">
<span class="sig-name descname"><span class="pre">num_models</span></span><a class="headerlink" href="#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.num_models" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>The number of models to hold in the ensemble</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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.offset">
<span class="sig-name descname"><span class="pre">offset</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/incremental/IncrementalEnsemble.html#IncrementalEnsembleFTS.offset"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.offset" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>Returns the number of lags to skip in the input test data in order to synchronize it with
the forecasted values given by the predict function. This is necessary due to the order of the
model, among other parameters.</p>
<dl class="field-list simple">
<dt class="field-odd">Returns</dt>
<dd class="field-odd"><p>An integer with the number of lags to skip</p>
</dd>
</dl>
</dd></dl>
<dl class="py attribute">
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<dt class="sig sig-object py" id="pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.partitioner_method">
<span class="sig-name descname"><span class="pre">partitioner_method</span></span><a class="headerlink" href="#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.partitioner_method" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>The partitioner method to be called when a new model is build</p>
</dd></dl>
<dl class="py attribute">
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<dt class="sig sig-object py" id="pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.partitioner_params">
<span class="sig-name descname"><span class="pre">partitioner_params</span></span><a class="headerlink" href="#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.partitioner_params" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>The partitioner method parameters</p>
</dd></dl>
Fixing documentation and type hints
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<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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/incremental/IncrementalEnsemble.html#IncrementalEnsembleFTS.train"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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>
<dl class="py attribute">
Fixing documentation and type hints
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<dt class="sig sig-object py" id="pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.window_length">
<span class="sig-name descname"><span class="pre">window_length</span></span><a class="headerlink" href="#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.window_length" title="Permalink to this definition"></a></dt>
Documentation update
2021-01-13 01:04:42 +04:00
<dd><p>The memory window length</p>
</dd></dl>
</dd></dl>
Incremental module
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Documentation update
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<li><a class="reference internal" href="#">pyFTS.models.incremental package</a><ul>
<li><a class="reference internal" href="#module-pyFTS.models.incremental">Module contents</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.incremental.TimeVariant">pyFTS.models.incremental.TimeVariant module</a></li>
<li><a class="reference internal" href="#module-pyFTS.models.incremental.IncrementalEnsemble">pyFTS.models.incremental.IncrementalEnsemble module</a></li>
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Incremental module
2018-11-01 18:11:20 +04:00
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