<spanid="pyfts-models-ensemble-ensemble-module"></span><h2>pyFTS.models.ensemble.ensemble module<aclass="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>
<emclass="property"><spanclass="pre">class</span><spanclass="w"></span></em><spanclass="sig-prename descclassname"><spanclass="pre">pyFTS.models.ensemble.ensemble.</span></span><spanclass="sig-name descname"><spanclass="pre">AllMethodEnsembleFTS</span></span><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="o"><spanclass="pre">**</span></span><spanclass="n"><spanclass="pre">kwargs</span></span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ensemble/ensemble.html#AllMethodEnsembleFTS"><spanclass="viewcode-link"><spanclass="pre">[source]</span></span></a><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.AllMethodEnsembleFTS"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">alpha_cut</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#float"title="(in Python v3.10)"><spanclass="pre">float</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">auto_update</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">benchmark_only</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">detail</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/stdtypes.html#str"title="(in Python v3.10)"><spanclass="pre">str</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">dump</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.AllMethodEnsembleFTS.dump"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">flrgs</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/stdtypes.html#dict"title="(in Python v3.10)"><spanclass="pre">dict</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">has_interval_forecasting</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">has_point_forecasting</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">has_probability_forecasting</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">has_seasonality</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">is_clustered</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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
<spanclass="sig-name descname"><spanclass="pre">is_high_order</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">is_multivariate</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">is_time_variant</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">is_wrapper</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">log</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><spanclass="pre">pd.DataFrame</span></em><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.AllMethodEnsembleFTS.log"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">max_lag</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#int"title="(in Python v3.10)"><spanclass="pre">int</span></a></em><aclass="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
<spanclass="sig-name descname"><spanclass="pre">min_order</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#int"title="(in Python v3.10)"><spanclass="pre">int</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">name</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/stdtypes.html#str"title="(in Python v3.10)"><spanclass="pre">str</span></a></em><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.AllMethodEnsembleFTS.name"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">order</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#int"title="(in Python v3.10)"><spanclass="pre">int</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">original_max</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#float"title="(in Python v3.10)"><spanclass="pre">float</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">original_min</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#float"title="(in Python v3.10)"><spanclass="pre">float</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">partitioner</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference internal"href="pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner"title="pyFTS.partitioners.partitioner.Partitioner"><spanclass="pre">partitioner.Partitioner</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">set_transformations</span></span><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n"><spanclass="pre">model</span></span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ensemble/ensemble.html#AllMethodEnsembleFTS.set_transformations"><spanclass="viewcode-link"><spanclass="pre">[source]</span></span></a><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.AllMethodEnsembleFTS.set_transformations"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">shortname</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/stdtypes.html#str"title="(in Python v3.10)"><spanclass="pre">str</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">standard_horizon</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#int"title="(in Python v3.10)"><spanclass="pre">int</span></a></em><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.AllMethodEnsembleFTS.standard_horizon"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">train</span></span><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n"><spanclass="pre">data</span></span></em>, <emclass="sig-param"><spanclass="o"><spanclass="pre">**</span></span><spanclass="n"><spanclass="pre">kwargs</span></span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ensemble/ensemble.html#AllMethodEnsembleFTS.train"><spanclass="viewcode-link"><spanclass="pre">[source]</span></span></a><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.AllMethodEnsembleFTS.train"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">transformations</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/stdtypes.html#list"title="(in Python v3.10)"><spanclass="pre">list</span></a><spanclass="p"><spanclass="pre">[</span></span><aclass="reference internal"href="pyFTS.common.transformations.html#pyFTS.common.transformations.transformation.Transformation"title="pyFTS.common.transformations.transformation.Transformation"><spanclass="pre">transformation.Transformation</span></a><spanclass="p"><spanclass="pre">]</span></span></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">transformations_param</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/stdtypes.html#list"title="(in Python v3.10)"><spanclass="pre">list</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">uod_clip</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<emclass="property"><spanclass="pre">class</span><spanclass="w"></span></em><spanclass="sig-prename descclassname"><spanclass="pre">pyFTS.models.ensemble.ensemble.</span></span><spanclass="sig-name descname"><spanclass="pre">EnsembleFTS</span></span><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="o"><spanclass="pre">**</span></span><spanclass="n"><spanclass="pre">kwargs</span></span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ensemble/ensemble.html#EnsembleFTS"><spanclass="viewcode-link"><spanclass="pre">[source]</span></span></a><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.EnsembleFTS"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">alpha</span></span><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.alpha"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">alpha_cut</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#float"title="(in Python v3.10)"><spanclass="pre">float</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">append_model</span></span><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n"><spanclass="pre">model</span></span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ensemble/ensemble.html#EnsembleFTS.append_model"><spanclass="viewcode-link"><spanclass="pre">[source]</span></span></a><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.append_model"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">auto_update</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">benchmark_only</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">detail</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/stdtypes.html#str"title="(in Python v3.10)"><spanclass="pre">str</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">dump</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.dump"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">flrgs</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/stdtypes.html#dict"title="(in Python v3.10)"><spanclass="pre">dict</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">forecast</span></span><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n"><spanclass="pre">data</span></span></em>, <emclass="sig-param"><spanclass="o"><spanclass="pre">**</span></span><spanclass="n"><spanclass="pre">kwargs</span></span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ensemble/ensemble.html#EnsembleFTS.forecast"><spanclass="viewcode-link"><spanclass="pre">[source]</span></span></a><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.forecast"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">forecast_ahead_distribution</span></span><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n"><spanclass="pre">data</span></span></em>, <emclass="sig-param"><spanclass="n"><spanclass="pre">steps</span></span></em>, <emclass="sig-param"><spanclass="o"><spanclass="pre">**</span></span><spanclass="n"><spanclass="pre">kwargs</span></span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ensemble/ensemble.html#EnsembleFTS.forecast_ahead_distribution"><spanclass="viewcode-link"><spanclass="pre">[source]</span></span></a><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.forecast_ahead_distribution"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">forecast_ahead_interval</span></span><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n"><spanclass="pre">data</span></span></em>, <emclass="sig-param"><spanclass="n"><spanclass="pre">steps</span></span></em>, <emclass="sig-param"><spanclass="o"><spanclass="pre">**</span></span><spanclass="n"><spanclass="pre">kwargs</span></span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ensemble/ensemble.html#EnsembleFTS.forecast_ahead_interval"><spanclass="viewcode-link"><spanclass="pre">[source]</span></span></a><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.forecast_ahead_interval"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">forecast_distribution</span></span><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n"><spanclass="pre">data</span></span></em>, <emclass="sig-param"><spanclass="o"><spanclass="pre">**</span></span><spanclass="n"><spanclass="pre">kwargs</span></span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ensemble/ensemble.html#EnsembleFTS.forecast_distribution"><spanclass="viewcode-link"><spanclass="pre">[source]</span></span></a><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.forecast_distribution"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">forecast_interval</span></span><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n"><spanclass="pre">data</span></span></em>, <emclass="sig-param"><spanclass="o"><spanclass="pre">**</span></span><spanclass="n"><spanclass="pre">kwargs</span></span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ensemble/ensemble.html#EnsembleFTS.forecast_interval"><spanclass="viewcode-link"><spanclass="pre">[source]</span></span></a><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.forecast_interval"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">get_UoD</span></span><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ensemble/ensemble.html#EnsembleFTS.get_UoD"><spanclass="viewcode-link"><spanclass="pre">[source]</span></span></a><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.get_UoD"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">get_distribution_interquantile</span></span><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n"><spanclass="pre">forecasts</span></span></em>, <emclass="sig-param"><spanclass="n"><spanclass="pre">alpha</span></span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ensemble/ensemble.html#EnsembleFTS.get_distribution_interquantile"><spanclass="viewcode-link"><spanclass="pre">[source]</span></span></a><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.get_distribution_interquantile"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">get_interval</span></span><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n"><spanclass="pre">forecasts</span></span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ensemble/ensemble.html#EnsembleFTS.get_interval"><spanclass="viewcode-link"><spanclass="pre">[source]</span></span></a><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.get_interval"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">get_models_forecasts</span></span><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n"><spanclass="pre">data</span></span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ensemble/ensemble.html#EnsembleFTS.get_models_forecasts"><spanclass="viewcode-link"><spanclass="pre">[source]</span></span></a><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.get_models_forecasts"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">get_point</span></span><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n"><spanclass="pre">forecasts</span></span></em>, <emclass="sig-param"><spanclass="o"><spanclass="pre">**</span></span><spanclass="n"><spanclass="pre">kwargs</span></span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ensemble/ensemble.html#EnsembleFTS.get_point"><spanclass="viewcode-link"><spanclass="pre">[source]</span></span></a><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.get_point"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">has_interval_forecasting</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">has_point_forecasting</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">has_probability_forecasting</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">has_seasonality</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">interval_method</span></span><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.interval_method"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">is_clustered</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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
<spanclass="sig-name descname"><spanclass="pre">is_high_order</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">is_multivariate</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">is_time_variant</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">is_wrapper</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">log</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><spanclass="pre">pd.DataFrame</span></em><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.log"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">max_lag</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#int"title="(in Python v3.10)"><spanclass="pre">int</span></a></em><aclass="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
<spanclass="sig-name descname"><spanclass="pre">min_order</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#int"title="(in Python v3.10)"><spanclass="pre">int</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">models</span></span><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.models"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">name</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/stdtypes.html#str"title="(in Python v3.10)"><spanclass="pre">str</span></a></em><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.name"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">order</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#int"title="(in Python v3.10)"><spanclass="pre">int</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">original_max</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#float"title="(in Python v3.10)"><spanclass="pre">float</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">original_min</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#float"title="(in Python v3.10)"><spanclass="pre">float</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">parameters</span></span><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.parameters"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">partitioner</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference internal"href="pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner"title="pyFTS.partitioners.partitioner.Partitioner"><spanclass="pre">partitioner.Partitioner</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">point_method</span></span><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.point_method"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">shortname</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/stdtypes.html#str"title="(in Python v3.10)"><spanclass="pre">str</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">standard_horizon</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#int"title="(in Python v3.10)"><spanclass="pre">int</span></a></em><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.standard_horizon"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">train</span></span><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n"><spanclass="pre">data</span></span></em>, <emclass="sig-param"><spanclass="o"><spanclass="pre">**</span></span><spanclass="n"><spanclass="pre">kwargs</span></span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ensemble/ensemble.html#EnsembleFTS.train"><spanclass="viewcode-link"><spanclass="pre">[source]</span></span></a><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.train"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">transformations</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/stdtypes.html#list"title="(in Python v3.10)"><spanclass="pre">list</span></a><spanclass="p"><spanclass="pre">[</span></span><aclass="reference internal"href="pyFTS.common.transformations.html#pyFTS.common.transformations.transformation.Transformation"title="pyFTS.common.transformations.transformation.Transformation"><spanclass="pre">transformation.Transformation</span></a><spanclass="p"><spanclass="pre">]</span></span></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">transformations_param</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/stdtypes.html#list"title="(in Python v3.10)"><spanclass="pre">list</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">uod_clip</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<emclass="property"><spanclass="pre">class</span><spanclass="w"></span></em><spanclass="sig-prename descclassname"><spanclass="pre">pyFTS.models.ensemble.ensemble.</span></span><spanclass="sig-name descname"><spanclass="pre">SimpleEnsembleFTS</span></span><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="o"><spanclass="pre">**</span></span><spanclass="n"><spanclass="pre">kwargs</span></span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ensemble/ensemble.html#SimpleEnsembleFTS"><spanclass="viewcode-link"><spanclass="pre">[source]</span></span></a><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.SimpleEnsembleFTS"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">alpha_cut</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#float"title="(in Python v3.10)"><spanclass="pre">float</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">auto_update</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">benchmark_only</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">detail</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/stdtypes.html#str"title="(in Python v3.10)"><spanclass="pre">str</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">dump</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.SimpleEnsembleFTS.dump"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">flrgs</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/stdtypes.html#dict"title="(in Python v3.10)"><spanclass="pre">dict</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">has_interval_forecasting</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">has_point_forecasting</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">has_probability_forecasting</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">has_seasonality</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">is_clustered</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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
<spanclass="sig-name descname"><spanclass="pre">is_high_order</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">is_multivariate</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">is_time_variant</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">is_wrapper</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">log</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><spanclass="pre">pd.DataFrame</span></em><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.SimpleEnsembleFTS.log"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">max_lag</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#int"title="(in Python v3.10)"><spanclass="pre">int</span></a></em><aclass="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
<spanclass="sig-name descname"><spanclass="pre">method</span></span><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.SimpleEnsembleFTS.method"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">min_order</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#int"title="(in Python v3.10)"><spanclass="pre">int</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">name</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/stdtypes.html#str"title="(in Python v3.10)"><spanclass="pre">str</span></a></em><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.SimpleEnsembleFTS.name"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">order</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#int"title="(in Python v3.10)"><spanclass="pre">int</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">orders</span></span><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.SimpleEnsembleFTS.orders"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">original_max</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#float"title="(in Python v3.10)"><spanclass="pre">float</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">original_min</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#float"title="(in Python v3.10)"><spanclass="pre">float</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">partitioner</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference internal"href="pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner"title="pyFTS.partitioners.partitioner.Partitioner"><spanclass="pre">partitioner.Partitioner</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">partitioner_method</span></span><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.SimpleEnsembleFTS.partitioner_method"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">partitions</span></span><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.SimpleEnsembleFTS.partitions"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">shortname</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/stdtypes.html#str"title="(in Python v3.10)"><spanclass="pre">str</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">standard_horizon</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#int"title="(in Python v3.10)"><spanclass="pre">int</span></a></em><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.SimpleEnsembleFTS.standard_horizon"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">train</span></span><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n"><spanclass="pre">data</span></span></em>, <emclass="sig-param"><spanclass="o"><spanclass="pre">**</span></span><spanclass="n"><spanclass="pre">kwargs</span></span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ensemble/ensemble.html#SimpleEnsembleFTS.train"><spanclass="viewcode-link"><spanclass="pre">[source]</span></span></a><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.SimpleEnsembleFTS.train"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">transformations</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/stdtypes.html#list"title="(in Python v3.10)"><spanclass="pre">list</span></a><spanclass="p"><spanclass="pre">[</span></span><aclass="reference internal"href="pyFTS.common.transformations.html#pyFTS.common.transformations.transformation.Transformation"title="pyFTS.common.transformations.transformation.Transformation"><spanclass="pre">transformation.Transformation</span></a><spanclass="p"><spanclass="pre">]</span></span></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">transformations_param</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/stdtypes.html#list"title="(in Python v3.10)"><spanclass="pre">list</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">uod_clip</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-prename descclassname"><spanclass="pre">pyFTS.models.ensemble.ensemble.</span></span><spanclass="sig-name descname"><spanclass="pre">sampler</span></span><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n"><spanclass="pre">data</span></span></em>, <emclass="sig-param"><spanclass="n"><spanclass="pre">quantiles</span></span></em>, <emclass="sig-param"><spanclass="n"><spanclass="pre">bounds</span></span><spanclass="o"><spanclass="pre">=</span></span><spanclass="default_value"><spanclass="pre">False</span></span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ensemble/ensemble.html#sampler"><spanclass="viewcode-link"><spanclass="pre">[source]</span></span></a><aclass="headerlink"href="#pyFTS.models.ensemble.ensemble.sampler"title="Permalink to this definition">¶</a></dt>
<spanid="pyfts-models-ensemble-multiseasonal-module"></span><h2>pyFTS.models.ensemble.multiseasonal module<aclass="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>
<emclass="property"><spanclass="pre">class</span><spanclass="w"></span></em><spanclass="sig-prename descclassname"><spanclass="pre">pyFTS.models.ensemble.multiseasonal.</span></span><spanclass="sig-name descname"><spanclass="pre">SeasonalEnsembleFTS</span></span><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n"><spanclass="pre">name</span></span></em>, <emclass="sig-param"><spanclass="o"><spanclass="pre">**</span></span><spanclass="n"><spanclass="pre">kwargs</span></span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ensemble/multiseasonal.html#SeasonalEnsembleFTS"><spanclass="viewcode-link"><spanclass="pre">[source]</span></span></a><aclass="headerlink"href="#pyFTS.models.ensemble.multiseasonal.SeasonalEnsembleFTS"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">alpha_cut</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#float"title="(in Python v3.10)"><spanclass="pre">float</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">auto_update</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">benchmark_only</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">detail</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/stdtypes.html#str"title="(in Python v3.10)"><spanclass="pre">str</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">dump</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="headerlink"href="#pyFTS.models.ensemble.multiseasonal.SeasonalEnsembleFTS.dump"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">flrgs</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/stdtypes.html#dict"title="(in Python v3.10)"><spanclass="pre">dict</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">forecast_distribution</span></span><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n"><spanclass="pre">data</span></span></em>, <emclass="sig-param"><spanclass="o"><spanclass="pre">**</span></span><spanclass="n"><spanclass="pre">kwargs</span></span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ensemble/multiseasonal.html#SeasonalEnsembleFTS.forecast_distribution"><spanclass="viewcode-link"><spanclass="pre">[source]</span></span></a><aclass="headerlink"href="#pyFTS.models.ensemble.multiseasonal.SeasonalEnsembleFTS.forecast_distribution"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">has_interval_forecasting</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">has_point_forecasting</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">has_probability_forecasting</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">has_seasonality</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">is_clustered</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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
<spanclass="sig-name descname"><spanclass="pre">is_high_order</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">is_multivariate</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">is_time_variant</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">is_wrapper</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">log</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><spanclass="pre">pd.DataFrame</span></em><aclass="headerlink"href="#pyFTS.models.ensemble.multiseasonal.SeasonalEnsembleFTS.log"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">max_lag</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#int"title="(in Python v3.10)"><spanclass="pre">int</span></a></em><aclass="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
<spanclass="sig-name descname"><spanclass="pre">min_order</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#int"title="(in Python v3.10)"><spanclass="pre">int</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">name</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/stdtypes.html#str"title="(in Python v3.10)"><spanclass="pre">str</span></a></em><aclass="headerlink"href="#pyFTS.models.ensemble.multiseasonal.SeasonalEnsembleFTS.name"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">order</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#int"title="(in Python v3.10)"><spanclass="pre">int</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">original_max</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#float"title="(in Python v3.10)"><spanclass="pre">float</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">original_min</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#float"title="(in Python v3.10)"><spanclass="pre">float</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">partitioner</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference internal"href="pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner"title="pyFTS.partitioners.partitioner.Partitioner"><spanclass="pre">partitioner.Partitioner</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">shortname</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/stdtypes.html#str"title="(in Python v3.10)"><spanclass="pre">str</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">standard_horizon</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#int"title="(in Python v3.10)"><spanclass="pre">int</span></a></em><aclass="headerlink"href="#pyFTS.models.ensemble.multiseasonal.SeasonalEnsembleFTS.standard_horizon"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">train</span></span><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n"><spanclass="pre">data</span></span></em>, <emclass="sig-param"><spanclass="o"><spanclass="pre">**</span></span><spanclass="n"><spanclass="pre">kwargs</span></span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ensemble/multiseasonal.html#SeasonalEnsembleFTS.train"><spanclass="viewcode-link"><spanclass="pre">[source]</span></span></a><aclass="headerlink"href="#pyFTS.models.ensemble.multiseasonal.SeasonalEnsembleFTS.train"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-name descname"><spanclass="pre">transformations</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/stdtypes.html#list"title="(in Python v3.10)"><spanclass="pre">list</span></a><spanclass="p"><spanclass="pre">[</span></span><aclass="reference internal"href="pyFTS.common.transformations.html#pyFTS.common.transformations.transformation.Transformation"title="pyFTS.common.transformations.transformation.Transformation"><spanclass="pre">transformation.Transformation</span></a><spanclass="p"><spanclass="pre">]</span></span></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">transformations_param</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/stdtypes.html#list"title="(in Python v3.10)"><spanclass="pre">list</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">uod_clip</span></span><emclass="property"><spanclass="p"><spanclass="pre">:</span></span><spanclass="w"></span><aclass="reference external"href="https://docs.python.org/3/library/functions.html#bool"title="(in Python v3.10)"><spanclass="pre">bool</span></a></em><aclass="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>
<spanclass="sig-name descname"><spanclass="pre">update_uod</span></span><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n"><spanclass="pre">data</span></span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ensemble/multiseasonal.html#SeasonalEnsembleFTS.update_uod"><spanclass="viewcode-link"><spanclass="pre">[source]</span></span></a><aclass="headerlink"href="#pyFTS.models.ensemble.multiseasonal.SeasonalEnsembleFTS.update_uod"title="Permalink to this definition">¶</a></dt>
<spanclass="sig-prename descclassname"><spanclass="pre">pyFTS.models.ensemble.multiseasonal.</span></span><spanclass="sig-name descname"><spanclass="pre">train_individual_model</span></span><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n"><spanclass="pre">partitioner</span></span></em>, <emclass="sig-param"><spanclass="n"><spanclass="pre">train_data</span></span></em>, <emclass="sig-param"><spanclass="n"><spanclass="pre">indexer</span></span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ensemble/multiseasonal.html#train_individual_model"><spanclass="viewcode-link"><spanclass="pre">[source]</span></span></a><aclass="headerlink"href="#pyFTS.models.ensemble.multiseasonal.train_individual_model"title="Permalink to this definition">¶</a></dt>
<spanid="module-contents"></span><h2>Module contents<aclass="headerlink"href="#module-pyFTS.models.ensemble"title="Permalink to this headline">¶</a></h2>