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<div class="section" id="pyfts-models-ensemble-package">
<h1>pyFTS.models.ensemble package<a class="headerlink" href="#pyfts-models-ensemble-package" title="Permalink to this headline"></a></h1>
<div class="section" id="submodules">
<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this headline"></a></h2>
</div>
2021-01-13 01:04:42 +04:00
<div class="section" id="module-pyFTS.models.ensemble.ensemble">
<span id="pyfts-models-ensemble-ensemble-module"></span><h2>pyFTS.models.ensemble.ensemble module<a class="headerlink" href="#module-pyFTS.models.ensemble.ensemble" title="Permalink to this headline"></a></h2>
<p>EnsembleFTS wraps several FTS methods to ensemble their forecasts, providing point,
interval and probabilistic forecasting.</p>
<p>Silva, P. C. L et al. Probabilistic Forecasting with Seasonal Ensemble Fuzzy Time-Series
XIII Brazilian Congress on Computational Intelligence, 2017. Rio de Janeiro, Brazil.</p>
<dl class="py class">
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<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.AllMethodEnsembleFTS">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.ensemble.ensemble.</span></span><span class="sig-name descname"><span class="pre">AllMethodEnsembleFTS</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/ensemble/ensemble.html#AllMethodEnsembleFTS"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ensemble.ensemble.AllMethodEnsembleFTS" title="Permalink to this definition"></a></dt>
2021-01-13 01:04:42 +04:00
<dd><p>Bases: <a class="reference internal" href="#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>Creates an EnsembleFTS with all point forecast methods, sharing the same partitioner</p>
2022-04-10 21:32:24 +04:00
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.dump" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.flrgs" title="Permalink to this definition"></a></dt>
<dd><p>The list of Fuzzy Logical Relationship Groups - FLRG</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.log" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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>
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<dl class="py method">
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.AllMethodEnsembleFTS.set_transformations">
<span class="sig-name descname"><span class="pre">set_transformations</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/ensemble/ensemble.html#AllMethodEnsembleFTS.set_transformations"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ensemble.ensemble.AllMethodEnsembleFTS.set_transformations" title="Permalink to this definition"></a></dt>
2021-01-13 01:04:42 +04:00
<dd></dd></dl>
2022-04-10 21:32:24 +04:00
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.standard_horizon" title="Permalink to this definition"></a></dt>
<dd><p>Standard forecasting horizon (Default: 1)</p>
</dd></dl>
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<dl class="py method">
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<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.AllMethodEnsembleFTS.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/ensemble/ensemble.html#AllMethodEnsembleFTS.train"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ensemble.ensemble.AllMethodEnsembleFTS.train" title="Permalink to this definition"></a></dt>
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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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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.ensemble.ensemble.AllMethodEnsembleFTS.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>
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</dd></dl>
<dl class="py class">
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<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.EnsembleFTS">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.ensemble.ensemble.</span></span><span class="sig-name descname"><span class="pre">EnsembleFTS</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/ensemble/ensemble.html#EnsembleFTS"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ensemble.ensemble.EnsembleFTS" 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>Ensemble FTS</p>
<dl class="py attribute">
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<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.EnsembleFTS.alpha">
<span class="sig-name descname"><span class="pre">alpha</span></span><a class="headerlink" href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.alpha" title="Permalink to this definition"></a></dt>
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<dd><p>The quantiles</p>
</dd></dl>
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<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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>
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<dl class="py method">
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<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.EnsembleFTS.append_model">
<span class="sig-name descname"><span class="pre">append_model</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/ensemble/ensemble.html#EnsembleFTS.append_model"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.append_model" title="Permalink to this definition"></a></dt>
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<dd><p>Append a new trained model to the ensemble</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>model</strong> FTS model</p>
</dd>
</dl>
</dd></dl>
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<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.dump" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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/ensemble/ensemble.html#EnsembleFTS.forecast"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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">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/ensemble/ensemble.html#EnsembleFTS.forecast_ahead_distribution"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.forecast_ahead_distribution" title="Permalink to this definition"></a></dt>
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<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">
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<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.EnsembleFTS.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/ensemble/ensemble.html#EnsembleFTS.forecast_ahead_interval"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.forecast_ahead_interval" title="Permalink to this definition"></a></dt>
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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">
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<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.EnsembleFTS.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">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/ensemble/ensemble.html#EnsembleFTS.forecast_distribution"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.forecast_distribution" title="Permalink to this definition"></a></dt>
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<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">
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<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.EnsembleFTS.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">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/ensemble/ensemble.html#EnsembleFTS.forecast_interval"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.forecast_interval" title="Permalink to this definition"></a></dt>
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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>
<dl class="py method">
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<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.EnsembleFTS.get_UoD">
<span class="sig-name descname"><span class="pre">get_UoD</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ensemble/ensemble.html#EnsembleFTS.get_UoD"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.get_UoD" title="Permalink to this definition"></a></dt>
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<dd><p>Returns the interval of the known bounds of the universe of discourse (UoD), i. e.,
the known minimum and maximum values of the time series.</p>
<dl class="field-list simple">
<dt class="field-odd">Returns</dt>
<dd class="field-odd"><p>A set with the lower and the upper bounds of the UoD</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
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<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.EnsembleFTS.get_distribution_interquantile">
<span class="sig-name descname"><span class="pre">get_distribution_interquantile</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecasts</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ensemble/ensemble.html#EnsembleFTS.get_distribution_interquantile"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.get_distribution_interquantile" title="Permalink to this definition"></a></dt>
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<dd></dd></dl>
<dl class="py method">
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<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.EnsembleFTS.get_interval">
<span class="sig-name descname"><span class="pre">get_interval</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecasts</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ensemble/ensemble.html#EnsembleFTS.get_interval"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.get_interval" title="Permalink to this definition"></a></dt>
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<dd></dd></dl>
<dl class="py method">
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<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.EnsembleFTS.get_models_forecasts">
<span class="sig-name descname"><span class="pre">get_models_forecasts</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/ensemble/ensemble.html#EnsembleFTS.get_models_forecasts"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.get_models_forecasts" title="Permalink to this definition"></a></dt>
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<dd></dd></dl>
<dl class="py method">
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<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.EnsembleFTS.get_point">
<span class="sig-name descname"><span class="pre">get_point</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">forecasts</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/ensemble/ensemble.html#EnsembleFTS.get_point"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.get_point" title="Permalink to this definition"></a></dt>
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<dd></dd></dl>
<dl class="py attribute">
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<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.interval_method">
<span class="sig-name descname"><span class="pre">interval_method</span></span><a class="headerlink" href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.interval_method" title="Permalink to this definition"></a></dt>
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<dd><p>The method used to mix the several models forecasts into a interval forecast. Options: quantile, extremum, normal</p>
</dd></dl>
<dl class="py attribute">
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<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.log" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.models">
<span class="sig-name descname"><span class="pre">models</span></span><a class="headerlink" href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.models" title="Permalink to this definition"></a></dt>
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<dd><p>A list of FTS models, the ensemble components</p>
</dd></dl>
<dl class="py attribute">
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<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.parameters">
<span class="sig-name descname"><span class="pre">parameters</span></span><a class="headerlink" href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.parameters" title="Permalink to this definition"></a></dt>
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<dd><p>A list with the parameters for each component model</p>
</dd></dl>
<dl class="py attribute">
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<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.point_method">
<span class="sig-name descname"><span class="pre">point_method</span></span><a class="headerlink" href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.point_method" title="Permalink to this definition"></a></dt>
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<dd><p>The method used to mix the several models forecasts into a unique point forecast. Options: mean, median, quantile, exponential</p>
</dd></dl>
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<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.standard_horizon" title="Permalink to this definition"></a></dt>
<dd><p>Standard forecasting horizon (Default: 1)</p>
</dd></dl>
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<dl class="py method">
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<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.EnsembleFTS.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/ensemble/ensemble.html#EnsembleFTS.train"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.train" title="Permalink to this definition"></a></dt>
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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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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.ensemble.ensemble.EnsembleFTS.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>
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</dd></dl>
<dl class="py class">
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<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.SimpleEnsembleFTS">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.ensemble.ensemble.</span></span><span class="sig-name descname"><span class="pre">SimpleEnsembleFTS</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/ensemble/ensemble.html#SimpleEnsembleFTS"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ensemble.ensemble.SimpleEnsembleFTS" title="Permalink to this definition"></a></dt>
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<dd><p>Bases: <a class="reference internal" href="#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>An homogeneous FTS method ensemble with variations on partitionings and orders.</p>
<dl class="py attribute">
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<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.dump" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.flrgs" title="Permalink to this definition"></a></dt>
<dd><p>The list of Fuzzy Logical Relationship Groups - FLRG</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.log" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.method">
<span class="sig-name descname"><span class="pre">method</span></span><a class="headerlink" href="#pyFTS.models.ensemble.ensemble.SimpleEnsembleFTS.method" title="Permalink to this definition"></a></dt>
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<dd><p>FTS method class that will be used on internal models</p>
</dd></dl>
<dl class="py attribute">
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<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.orders">
<span class="sig-name descname"><span class="pre">orders</span></span><a class="headerlink" href="#pyFTS.models.ensemble.ensemble.SimpleEnsembleFTS.orders" title="Permalink to this definition"></a></dt>
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<dd><p>Possible variations of order on internal models</p>
</dd></dl>
<dl class="py attribute">
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<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.partitioner_method">
<span class="sig-name descname"><span class="pre">partitioner_method</span></span><a class="headerlink" href="#pyFTS.models.ensemble.ensemble.SimpleEnsembleFTS.partitioner_method" title="Permalink to this definition"></a></dt>
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<dd><p>UoD partitioner class that will be used on internal methods</p>
</dd></dl>
<dl class="py attribute">
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<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.SimpleEnsembleFTS.partitions">
<span class="sig-name descname"><span class="pre">partitions</span></span><a class="headerlink" href="#pyFTS.models.ensemble.ensemble.SimpleEnsembleFTS.partitions" title="Permalink to this definition"></a></dt>
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<dd><p>Possible variations of number of partitions on internal models</p>
</dd></dl>
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<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.standard_horizon" title="Permalink to this definition"></a></dt>
<dd><p>Standard forecasting horizon (Default: 1)</p>
</dd></dl>
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<dl class="py method">
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<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.SimpleEnsembleFTS.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/ensemble/ensemble.html#SimpleEnsembleFTS.train"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ensemble.ensemble.SimpleEnsembleFTS.train" title="Permalink to this definition"></a></dt>
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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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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.ensemble.ensemble.SimpleEnsembleFTS.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>
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</dd></dl>
<dl class="py function">
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<dt class="sig sig-object py" id="pyFTS.models.ensemble.ensemble.sampler">
<span class="sig-prename descclassname"><span class="pre">pyFTS.models.ensemble.ensemble.</span></span><span class="sig-name descname"><span class="pre">sampler</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">quantiles</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bounds</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/ensemble/ensemble.html#sampler"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ensemble.ensemble.sampler" title="Permalink to this definition"></a></dt>
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<dd></dd></dl>
</div>
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<div class="section" id="module-pyFTS.models.ensemble.multiseasonal">
<span id="pyfts-models-ensemble-multiseasonal-module"></span><h2>pyFTS.models.ensemble.multiseasonal module<a class="headerlink" href="#module-pyFTS.models.ensemble.multiseasonal" title="Permalink to this headline"></a></h2>
<p>Silva, P. C. L et al. Probabilistic Forecasting with Seasonal Ensemble Fuzzy Time-Series
XIII Brazilian Congress on Computational Intelligence, 2017. Rio de Janeiro, Brazil.</p>
<dl class="py class">
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<dt class="sig sig-object py" id="pyFTS.models.ensemble.multiseasonal.SeasonalEnsembleFTS">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.ensemble.multiseasonal.</span></span><span class="sig-name descname"><span class="pre">SeasonalEnsembleFTS</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</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/ensemble/multiseasonal.html#SeasonalEnsembleFTS"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ensemble.multiseasonal.SeasonalEnsembleFTS" title="Permalink to this definition"></a></dt>
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<dd><p>Bases: <a class="reference internal" href="#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>
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<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.dump" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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">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/ensemble/multiseasonal.html#SeasonalEnsembleFTS.forecast_distribution"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ensemble.multiseasonal.SeasonalEnsembleFTS.forecast_distribution" title="Permalink to this definition"></a></dt>
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<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>
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<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.log" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.standard_horizon" title="Permalink to this definition"></a></dt>
<dd><p>Standard forecasting horizon (Default: 1)</p>
</dd></dl>
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<dl class="py method">
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<dt class="sig sig-object py" id="pyFTS.models.ensemble.multiseasonal.SeasonalEnsembleFTS.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/ensemble/multiseasonal.html#SeasonalEnsembleFTS.train"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ensemble.multiseasonal.SeasonalEnsembleFTS.train" title="Permalink to this definition"></a></dt>
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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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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.ensemble.multiseasonal.SeasonalEnsembleFTS.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>
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<dl class="py method">
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<dt class="sig sig-object py" id="pyFTS.models.ensemble.multiseasonal.SeasonalEnsembleFTS.update_uod">
<span class="sig-name descname"><span class="pre">update_uod</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/ensemble/multiseasonal.html#SeasonalEnsembleFTS.update_uod"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ensemble.multiseasonal.SeasonalEnsembleFTS.update_uod" title="Permalink to this definition"></a></dt>
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<dd></dd></dl>
</dd></dl>
<dl class="py function">
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<dt class="sig sig-object py" id="pyFTS.models.ensemble.multiseasonal.train_individual_model">
<span class="sig-prename descclassname"><span class="pre">pyFTS.models.ensemble.multiseasonal.</span></span><span class="sig-name descname"><span class="pre">train_individual_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">partitioner</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">train_data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">indexer</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ensemble/multiseasonal.html#train_individual_model"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.ensemble.multiseasonal.train_individual_model" title="Permalink to this definition"></a></dt>
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<dd></dd></dl>
</div>
<div class="section" id="module-pyFTS.models.ensemble">
<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-pyFTS.models.ensemble" title="Permalink to this headline"></a></h2>
<p>Meta FTS that aggregates other FTS methods</p>
</div>
</div>
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<li><a class="reference internal" href="#">pyFTS.models.ensemble package</a><ul>
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