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<div class="section" id="pyfts-models-incremental-package">
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<h1>pyFTS.models.incremental package<a class="headerlink" href="#pyfts-models-incremental-package" title="Permalink to this headline">¶</a></h1>
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<div class="section" id="module-pyFTS.models.incremental">
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<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-pyFTS.models.incremental" title="Permalink to this headline">¶</a></h2>
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<p>FTS methods with incremental/online learning</p>
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</div>
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<div class="section" id="submodules">
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<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this headline">¶</a></h2>
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</div>
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<div class="section" id="module-pyFTS.models.incremental.TimeVariant">
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<span id="pyfts-models-incremental-timevariant-module"></span><h2>pyFTS.models.incremental.TimeVariant module<a class="headerlink" href="#module-pyFTS.models.incremental.TimeVariant" title="Permalink to this headline">¶</a></h2>
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<p>Meta model that wraps another FTS method and continously retrain it using a data window with
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the most recent data</p>
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<dl class="py class">
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<dt id="pyFTS.models.incremental.TimeVariant.Retrainer">
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<em class="property">class </em><code class="sig-prename descclassname">pyFTS.models.incremental.TimeVariant.</code><code class="sig-name descname">Retrainer</code><span class="sig-paren">(</span><em class="sig-param"><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/incremental/TimeVariant.html#Retrainer"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.incremental.TimeVariant.Retrainer" title="Permalink to this definition">¶</a></dt>
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<dd><p>Bases: <a class="reference internal" href="pyFTS.common.html#pyFTS.common.fts.FTS" title="pyFTS.common.fts.FTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.fts.FTS</span></code></a></p>
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<p>Meta model for incremental/online learning that retrain its internal model after
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data windows controlled by the parameter ‘batch_size’, using as the training data a
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window of recent lags, whose size is controlled by the parameter ‘window_length’.</p>
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<dl class="py attribute">
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<dt id="pyFTS.models.incremental.TimeVariant.Retrainer.auto_update">
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<code class="sig-name descname">auto_update</code><a class="headerlink" href="#pyFTS.models.incremental.TimeVariant.Retrainer.auto_update" title="Permalink to this definition">¶</a></dt>
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<dd><p>If true the model is updated at each time and not recreated</p>
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</dd></dl>
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<dl class="py attribute">
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<dt id="pyFTS.models.incremental.TimeVariant.Retrainer.batch_size">
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<code class="sig-name descname">batch_size</code><a class="headerlink" href="#pyFTS.models.incremental.TimeVariant.Retrainer.batch_size" title="Permalink to this definition">¶</a></dt>
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<dd><p>The batch interval between each retraining</p>
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</dd></dl>
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<dl class="py method">
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<dt id="pyFTS.models.incremental.TimeVariant.Retrainer.forecast">
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<code class="sig-name descname">forecast</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">data</span></em>, <em class="sig-param"><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/incremental/TimeVariant.html#Retrainer.forecast"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.incremental.TimeVariant.Retrainer.forecast" title="Permalink to this definition">¶</a></dt>
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<dd><p>Point forecast one step ahead</p>
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<dl class="field-list simple">
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<dt class="field-odd">Parameters</dt>
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<dd class="field-odd"><ul class="simple">
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<li><p><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</p></li>
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<li><p><strong>kwargs</strong> – model specific parameters</p></li>
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</ul>
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</dd>
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<dt class="field-even">Returns</dt>
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<dd class="field-even"><p>a list with the forecasted values</p>
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</dd>
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</dl>
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</dd></dl>
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<dl class="py method">
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<dt id="pyFTS.models.incremental.TimeVariant.Retrainer.forecast_ahead">
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<code class="sig-name descname">forecast_ahead</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">data</span></em>, <em class="sig-param"><span class="n">steps</span></em>, <em class="sig-param"><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/incremental/TimeVariant.html#Retrainer.forecast_ahead"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.incremental.TimeVariant.Retrainer.forecast_ahead" title="Permalink to this definition">¶</a></dt>
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<dd><p>Point forecast from 1 to H steps ahead, where H is given by the steps parameter</p>
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<dl class="field-list simple">
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<dt class="field-odd">Parameters</dt>
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<dd class="field-odd"><ul class="simple">
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<li><p><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</p></li>
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<li><p><strong>steps</strong> – the number of steps ahead to forecast (default: 1)</p></li>
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<li><p><strong>start_at</strong> – in the multi step forecasting, the index of the data where to start forecasting (default: 0)</p></li>
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</ul>
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</dd>
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<dt class="field-even">Returns</dt>
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<dd class="field-even"><p>a list with the forecasted values</p>
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</dd>
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</dl>
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</dd></dl>
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<dl class="py attribute">
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<dt id="pyFTS.models.incremental.TimeVariant.Retrainer.fts_method">
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<code class="sig-name descname">fts_method</code><a class="headerlink" href="#pyFTS.models.incremental.TimeVariant.Retrainer.fts_method" title="Permalink to this definition">¶</a></dt>
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<dd><p>The FTS method to be called when a new model is build</p>
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</dd></dl>
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<dl class="py attribute">
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<dt id="pyFTS.models.incremental.TimeVariant.Retrainer.fts_params">
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<code class="sig-name descname">fts_params</code><a class="headerlink" href="#pyFTS.models.incremental.TimeVariant.Retrainer.fts_params" title="Permalink to this definition">¶</a></dt>
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<dd><p>The FTS method specific parameters</p>
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</dd></dl>
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<dl class="py attribute">
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<dt id="pyFTS.models.incremental.TimeVariant.Retrainer.model">
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<code class="sig-name descname">model</code><a class="headerlink" href="#pyFTS.models.incremental.TimeVariant.Retrainer.model" title="Permalink to this definition">¶</a></dt>
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<dd><p>The most recent trained model</p>
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</dd></dl>
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<dl class="py method">
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<dt id="pyFTS.models.incremental.TimeVariant.Retrainer.offset">
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<code class="sig-name descname">offset</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/incremental/TimeVariant.html#Retrainer.offset"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.incremental.TimeVariant.Retrainer.offset" title="Permalink to this definition">¶</a></dt>
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<dd><p>Returns the number of lags to skip in the input test data in order to synchronize it with
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the forecasted values given by the predict function. This is necessary due to the order of the
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model, among other parameters.</p>
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<dl class="field-list simple">
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<dt class="field-odd">Returns</dt>
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<dd class="field-odd"><p>An integer with the number of lags to skip</p>
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</dd>
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</dl>
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</dd></dl>
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<dl class="py attribute">
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<dt id="pyFTS.models.incremental.TimeVariant.Retrainer.partitioner">
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<code class="sig-name descname">partitioner</code><a class="headerlink" href="#pyFTS.models.incremental.TimeVariant.Retrainer.partitioner" title="Permalink to this definition">¶</a></dt>
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<dd><p>The most recent trained partitioner</p>
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</dd></dl>
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<dl class="py attribute">
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<dt id="pyFTS.models.incremental.TimeVariant.Retrainer.partitioner_method">
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<code class="sig-name descname">partitioner_method</code><a class="headerlink" href="#pyFTS.models.incremental.TimeVariant.Retrainer.partitioner_method" title="Permalink to this definition">¶</a></dt>
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<dd><p>The partitioner method to be called when a new model is build</p>
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</dd></dl>
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<dl class="py attribute">
|
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<dt id="pyFTS.models.incremental.TimeVariant.Retrainer.partitioner_params">
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<code class="sig-name descname">partitioner_params</code><a class="headerlink" href="#pyFTS.models.incremental.TimeVariant.Retrainer.partitioner_params" title="Permalink to this definition">¶</a></dt>
|
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<dd><p>The partitioner method parameters</p>
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</dd></dl>
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<dl class="py method">
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<dt id="pyFTS.models.incremental.TimeVariant.Retrainer.train">
|
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<code class="sig-name descname">train</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">data</span></em>, <em class="sig-param"><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/incremental/TimeVariant.html#Retrainer.train"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.incremental.TimeVariant.Retrainer.train" title="Permalink to this definition">¶</a></dt>
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<dd><p>Method specific parameter fitting</p>
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<dl class="field-list simple">
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<dt class="field-odd">Parameters</dt>
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<dd class="field-odd"><ul class="simple">
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<li><p><strong>data</strong> – training time series data</p></li>
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<li><p><strong>kwargs</strong> – Method specific parameters</p></li>
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</ul>
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</dd>
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</dl>
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</dd></dl>
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<dl class="py attribute">
|
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<dt id="pyFTS.models.incremental.TimeVariant.Retrainer.window_length">
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<code class="sig-name descname">window_length</code><a class="headerlink" href="#pyFTS.models.incremental.TimeVariant.Retrainer.window_length" title="Permalink to this definition">¶</a></dt>
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<dd><p>The memory window length</p>
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</dd></dl>
|
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</dd></dl>
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</div>
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<div class="section" id="module-pyFTS.models.incremental.IncrementalEnsemble">
|
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<span id="pyfts-models-incremental-incrementalensemble-module"></span><h2>pyFTS.models.incremental.IncrementalEnsemble module<a class="headerlink" href="#module-pyFTS.models.incremental.IncrementalEnsemble" title="Permalink to this headline">¶</a></h2>
|
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<p>Time Variant/Incremental Ensemble of FTS methods</p>
|
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<dl class="py class">
|
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<dt id="pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS">
|
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<em class="property">class </em><code class="sig-prename descclassname">pyFTS.models.incremental.IncrementalEnsemble.</code><code class="sig-name descname">IncrementalEnsembleFTS</code><span class="sig-paren">(</span><em class="sig-param"><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/incremental/IncrementalEnsemble.html#IncrementalEnsembleFTS"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS" title="Permalink to this definition">¶</a></dt>
|
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<dd><p>Bases: <a class="reference internal" href="pyFTS.models.ensemble.html#pyFTS.models.ensemble.ensemble.EnsembleFTS" title="pyFTS.models.ensemble.ensemble.EnsembleFTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.models.ensemble.ensemble.EnsembleFTS</span></code></a></p>
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<p>Time Variant/Incremental Ensemble of FTS methods</p>
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<dl class="py attribute">
|
||
<dt id="pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.batch_size">
|
||
<code class="sig-name descname">batch_size</code><a class="headerlink" href="#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.batch_size" title="Permalink to this definition">¶</a></dt>
|
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<dd><p>The batch interval between each retraining</p>
|
||
</dd></dl>
|
||
|
||
<dl class="py method">
|
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<dt id="pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.forecast">
|
||
<code class="sig-name descname">forecast</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">data</span></em>, <em class="sig-param"><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/incremental/IncrementalEnsemble.html#IncrementalEnsembleFTS.forecast"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.forecast" title="Permalink to this definition">¶</a></dt>
|
||
<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">
|
||
<dt id="pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.forecast_ahead">
|
||
<code class="sig-name descname">forecast_ahead</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">data</span></em>, <em class="sig-param"><span class="n">steps</span></em>, <em class="sig-param"><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/incremental/IncrementalEnsemble.html#IncrementalEnsembleFTS.forecast_ahead"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.forecast_ahead" title="Permalink to this definition">¶</a></dt>
|
||
<dd><p>Point forecast from 1 to H steps ahead, where H is given by the steps parameter</p>
|
||
<dl class="field-list simple">
|
||
<dt class="field-odd">Parameters</dt>
|
||
<dd class="field-odd"><ul class="simple">
|
||
<li><p><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</p></li>
|
||
<li><p><strong>steps</strong> – the number of steps ahead to forecast (default: 1)</p></li>
|
||
<li><p><strong>start_at</strong> – in the multi step forecasting, the index of the data where to start forecasting (default: 0)</p></li>
|
||
</ul>
|
||
</dd>
|
||
<dt class="field-even">Returns</dt>
|
||
<dd class="field-even"><p>a list with the forecasted values</p>
|
||
</dd>
|
||
</dl>
|
||
</dd></dl>
|
||
|
||
<dl class="py attribute">
|
||
<dt id="pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.fts_method">
|
||
<code class="sig-name descname">fts_method</code><a class="headerlink" href="#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.fts_method" title="Permalink to this definition">¶</a></dt>
|
||
<dd><p>The FTS method to be called when a new model is build</p>
|
||
</dd></dl>
|
||
|
||
<dl class="py attribute">
|
||
<dt id="pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.fts_params">
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||
<code class="sig-name descname">fts_params</code><a class="headerlink" href="#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.fts_params" title="Permalink to this definition">¶</a></dt>
|
||
<dd><p>The FTS method specific parameters</p>
|
||
</dd></dl>
|
||
|
||
<dl class="py attribute">
|
||
<dt id="pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.num_models">
|
||
<code class="sig-name descname">num_models</code><a class="headerlink" href="#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.num_models" title="Permalink to this definition">¶</a></dt>
|
||
<dd><p>The number of models to hold in the ensemble</p>
|
||
</dd></dl>
|
||
|
||
<dl class="py method">
|
||
<dt id="pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.offset">
|
||
<code class="sig-name descname">offset</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/incremental/IncrementalEnsemble.html#IncrementalEnsembleFTS.offset"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.offset" title="Permalink to this definition">¶</a></dt>
|
||
<dd><p>Returns the number of lags to skip in the input test data in order to synchronize it with
|
||
the forecasted values given by the predict function. This is necessary due to the order of the
|
||
model, among other parameters.</p>
|
||
<dl class="field-list simple">
|
||
<dt class="field-odd">Returns</dt>
|
||
<dd class="field-odd"><p>An integer with the number of lags to skip</p>
|
||
</dd>
|
||
</dl>
|
||
</dd></dl>
|
||
|
||
<dl class="py attribute">
|
||
<dt id="pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.partitioner_method">
|
||
<code class="sig-name descname">partitioner_method</code><a class="headerlink" href="#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.partitioner_method" title="Permalink to this definition">¶</a></dt>
|
||
<dd><p>The partitioner method to be called when a new model is build</p>
|
||
</dd></dl>
|
||
|
||
<dl class="py attribute">
|
||
<dt id="pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.partitioner_params">
|
||
<code class="sig-name descname">partitioner_params</code><a class="headerlink" href="#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.partitioner_params" title="Permalink to this definition">¶</a></dt>
|
||
<dd><p>The partitioner method parameters</p>
|
||
</dd></dl>
|
||
|
||
<dl class="py method">
|
||
<dt id="pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.train">
|
||
<code class="sig-name descname">train</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">data</span></em>, <em class="sig-param"><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/incremental/IncrementalEnsemble.html#IncrementalEnsembleFTS.train"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.train" title="Permalink to this definition">¶</a></dt>
|
||
<dd><p>Method specific parameter fitting</p>
|
||
<dl class="field-list simple">
|
||
<dt class="field-odd">Parameters</dt>
|
||
<dd class="field-odd"><ul class="simple">
|
||
<li><p><strong>data</strong> – training time series data</p></li>
|
||
<li><p><strong>kwargs</strong> – Method specific parameters</p></li>
|
||
</ul>
|
||
</dd>
|
||
</dl>
|
||
</dd></dl>
|
||
|
||
<dl class="py attribute">
|
||
<dt id="pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.window_length">
|
||
<code class="sig-name descname">window_length</code><a class="headerlink" href="#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.window_length" title="Permalink to this definition">¶</a></dt>
|
||
<dd><p>The memory window length</p>
|
||
</dd></dl>
|
||
|
||
</dd></dl>
|
||
|
||
</div>
|
||
</div>
|
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<h3><a href="index.html">Table of Contents</a></h3>
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||
<ul>
|
||
<li><a class="reference internal" href="#">pyFTS.models.incremental package</a><ul>
|
||
<li><a class="reference internal" href="#module-pyFTS.models.incremental">Module contents</a></li>
|
||
<li><a class="reference internal" href="#submodules">Submodules</a></li>
|
||
<li><a class="reference internal" href="#module-pyFTS.models.incremental.TimeVariant">pyFTS.models.incremental.TimeVariant module</a></li>
|
||
<li><a class="reference internal" href="#module-pyFTS.models.incremental.IncrementalEnsemble">pyFTS.models.incremental.IncrementalEnsemble module</a></li>
|
||
</ul>
|
||
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||
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