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Configuration and documentation update due the release 1.6
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<title>pyFTS.models.multivariate package &#8212; pyFTS 1.6 documentation</title>
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<ul>
<li><a class="reference internal" href="#">pyFTS.models.multivariate package</a><ul>
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<li><a class="reference internal" href="#module-pyFTS.models.multivariate">Module contents</a></li>
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<li><a class="reference internal" href="#submodules">Submodules</a></li>
<li><a class="reference internal" href="#module-pyFTS.models.multivariate.FLR">pyFTS.models.multivariate.FLR module</a></li>
<li><a class="reference internal" href="#module-pyFTS.models.multivariate.common">pyFTS.models.multivariate.common module</a></li>
Documentation update
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<li><a class="reference internal" href="#module-pyFTS.models.multivariate.variable">pyFTS.models.multivariate.variable module</a></li>
Updating the documentation
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<li><a class="reference internal" href="#module-pyFTS.models.multivariate.flrg">pyFTS.models.multivariate.flrg module</a></li>
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<li><a class="reference internal" href="#module-pyFTS.models.multivariate.partitioner">pyFTS.models.multivariate.partitioner module</a></li>
<li><a class="reference internal" href="#module-pyFTS.models.multivariate.grid">pyFTS.models.multivariate.grid module</a></li>
Updating the documentation
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<li><a class="reference internal" href="#module-pyFTS.models.multivariate.mvfts">pyFTS.models.multivariate.mvfts module</a></li>
Documentation update
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<li><a class="reference internal" href="#module-pyFTS.models.multivariate.wmvfts">pyFTS.models.multivariate.wmvfts module</a></li>
<li><a class="reference internal" href="#module-pyFTS.models.multivariate.cmvfts">pyFTS.models.multivariate.cmvfts module</a></li>
Documentation update
2019-04-22 17:01:58 +04:00
<li><a class="reference internal" href="#module-pyFTS.models.multivariate.granular">pyFTS.models.multivariate.granular module</a></li>
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</ul>
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Incremental module
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<div class="document">
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<div class="section" id="pyfts-models-multivariate-package">
<h1>pyFTS.models.multivariate package<a class="headerlink" href="#pyfts-models-multivariate-package" title="Permalink to this headline"></a></h1>
Updating the documentation
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<div class="section" id="module-pyFTS.models.multivariate">
<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-pyFTS.models.multivariate" title="Permalink to this headline"></a></h2>
<p>Multivariate Fuzzy Time Series methods</p>
</div>
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<div class="section" id="submodules">
<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this headline"></a></h2>
</div>
<div class="section" id="module-pyFTS.models.multivariate.FLR">
<span id="pyfts-models-multivariate-flr-module"></span><h2>pyFTS.models.multivariate.FLR module<a class="headerlink" href="#module-pyFTS.models.multivariate.FLR" title="Permalink to this headline"></a></h2>
<dl class="class">
<dt id="pyFTS.models.multivariate.FLR.FLR">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
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<em class="property">class </em><code class="descclassname">pyFTS.models.multivariate.FLR.</code><code class="descname">FLR</code><a class="headerlink" href="#pyFTS.models.multivariate.FLR.FLR" title="Permalink to this definition"></a></dt>
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<dd><p>Bases: <a class="reference external" href="https://docs.python.org/3/library/functions.html#object" title="(in Python v3.7)"><code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></a></p>
<p>Multivariate Fuzzy Logical Relationship</p>
<dl class="method">
<dt id="pyFTS.models.multivariate.FLR.FLR.set_lhs">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">set_lhs</code><span class="sig-paren">(</span><em>var</em>, <em>set</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.FLR.FLR.set_lhs" title="Permalink to this definition"></a></dt>
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<dd></dd></dl>
<dl class="method">
<dt id="pyFTS.models.multivariate.FLR.FLR.set_rhs">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">set_rhs</code><span class="sig-paren">(</span><em>set</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.FLR.FLR.set_rhs" title="Permalink to this definition"></a></dt>
Sphinx documentation for ReadTheDocs site
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<dd></dd></dl>
</dd></dl>
</div>
<div class="section" id="module-pyFTS.models.multivariate.common">
<span id="pyfts-models-multivariate-common-module"></span><h2>pyFTS.models.multivariate.common module<a class="headerlink" href="#module-pyFTS.models.multivariate.common" title="Permalink to this headline"></a></h2>
Documentation update
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<dl class="class">
<dt id="pyFTS.models.multivariate.common.MultivariateFuzzySet">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
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<em class="property">class </em><code class="descclassname">pyFTS.models.multivariate.common.</code><code class="descname">MultivariateFuzzySet</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.common.MultivariateFuzzySet" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>Bases: <a class="reference internal" href="pyFTS.common.html#pyFTS.common.Composite.FuzzySet" title="pyFTS.common.Composite.FuzzySet"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.Composite.FuzzySet</span></code></a></p>
<p>Multivariate Composite Fuzzy Set</p>
<dl class="method">
<dt id="pyFTS.models.multivariate.common.MultivariateFuzzySet.append_set">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
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<code class="descname">append_set</code><span class="sig-paren">(</span><em>variable</em>, <em>set</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.common.MultivariateFuzzySet.append_set" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>Appends a new fuzzy set from a new variable</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>variable</strong> – an multivariate.variable instance</li>
<li><strong>set</strong> – an common.FuzzySet instance</li>
</ul>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="pyFTS.models.multivariate.common.MultivariateFuzzySet.membership">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
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<code class="descname">membership</code><span class="sig-paren">(</span><em>x</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.common.MultivariateFuzzySet.membership" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><p>Calculate the membership value of a given input</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>x</strong> – input value</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">membership value of x at this fuzzy set</td>
</tr>
</tbody>
</table>
</dd></dl>
Single partitioner; documentation update
2018-12-13 01:35:02 +04:00
<dl class="method">
<dt id="pyFTS.models.multivariate.common.MultivariateFuzzySet.set_target_variable">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">set_target_variable</code><span class="sig-paren">(</span><em>variable</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.common.MultivariateFuzzySet.set_target_variable" title="Permalink to this definition"></a></dt>
Single partitioner; documentation update
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<dd></dd></dl>
Documentation update
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</dd></dl>
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<dl class="function">
<dt id="pyFTS.models.multivariate.common.fuzzyfy_instance">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descclassname">pyFTS.models.multivariate.common.</code><code class="descname">fuzzyfy_instance</code><span class="sig-paren">(</span><em>data_point</em>, <em>var</em>, <em>tuples=True</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.common.fuzzyfy_instance" title="Permalink to this definition"></a></dt>
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<dd></dd></dl>
Documentation update
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<dl class="function">
<dt id="pyFTS.models.multivariate.common.fuzzyfy_instance_clustered">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descclassname">pyFTS.models.multivariate.common.</code><code class="descname">fuzzyfy_instance_clustered</code><span class="sig-paren">(</span><em>data_point</em>, <em>cluster</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.common.fuzzyfy_instance_clustered" title="Permalink to this definition"></a></dt>
Documentation update
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<dd></dd></dl>
</div>
<div class="section" id="module-pyFTS.models.multivariate.variable">
<span id="pyfts-models-multivariate-variable-module"></span><h2>pyFTS.models.multivariate.variable module<a class="headerlink" href="#module-pyFTS.models.multivariate.variable" title="Permalink to this headline"></a></h2>
<dl class="class">
<dt id="pyFTS.models.multivariate.variable.Variable">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
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<em class="property">class </em><code class="descclassname">pyFTS.models.multivariate.variable.</code><code class="descname">Variable</code><span class="sig-paren">(</span><em>name</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.variable.Variable" title="Permalink to this definition"></a></dt>
Documentation update
2018-11-13 18:11:49 +04:00
<dd><p>Bases: <a class="reference external" href="https://docs.python.org/3/library/functions.html#object" title="(in Python v3.7)"><code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></a></p>
<p>A variable of a fuzzy time series multivariate model. Each variable contains its own
transformations and partitioners.</p>
<dl class="method">
<dt id="pyFTS.models.multivariate.variable.Variable.apply_inverse_transformations">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">apply_inverse_transformations</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.variable.Variable.apply_inverse_transformations" title="Permalink to this definition"></a></dt>
Documentation update
2018-11-13 18:11:49 +04:00
<dd></dd></dl>
<dl class="method">
<dt id="pyFTS.models.multivariate.variable.Variable.apply_transformations">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">apply_transformations</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.variable.Variable.apply_transformations" title="Permalink to this definition"></a></dt>
Documentation update
2018-11-13 18:11:49 +04:00
<dd></dd></dl>
<dl class="method">
<dt id="pyFTS.models.multivariate.variable.Variable.build">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">build</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.variable.Variable.build" title="Permalink to this definition"></a></dt>
Documentation update
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<dd><table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>kwargs</strong> – </td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"></td>
</tr>
</tbody>
</table>
</dd></dl>
</dd></dl>
Sphinx documentation for ReadTheDocs site
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</div>
<div class="section" id="module-pyFTS.models.multivariate.flrg">
<span id="pyfts-models-multivariate-flrg-module"></span><h2>pyFTS.models.multivariate.flrg module<a class="headerlink" href="#module-pyFTS.models.multivariate.flrg" title="Permalink to this headline"></a></h2>
<dl class="class">
<dt id="pyFTS.models.multivariate.flrg.FLRG">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<em class="property">class </em><code class="descclassname">pyFTS.models.multivariate.flrg.</code><code class="descname">FLRG</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.flrg.FLRG" title="Permalink to this definition"></a></dt>
Sphinx documentation for ReadTheDocs site
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<dd><p>Bases: <a class="reference internal" href="pyFTS.common.html#pyFTS.common.flrg.FLRG" title="pyFTS.common.flrg.FLRG"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.flrg.FLRG</span></code></a></p>
<p>Multivariate Fuzzy Logical Rule Group</p>
<dl class="method">
<dt id="pyFTS.models.multivariate.flrg.FLRG.append_rhs">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">append_rhs</code><span class="sig-paren">(</span><em>fset</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.flrg.FLRG.append_rhs" title="Permalink to this definition"></a></dt>
Sphinx documentation for ReadTheDocs site
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<dd></dd></dl>
Updating documentiation
2019-04-02 22:30:51 +04:00
<dl class="method">
<dt id="pyFTS.models.multivariate.flrg.FLRG.get_lower">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">get_lower</code><span class="sig-paren">(</span><em>sets</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.flrg.FLRG.get_lower" title="Permalink to this definition"></a></dt>
Updating documentiation
2019-04-02 22:30:51 +04:00
<dd><p>Returns the lower bound value for the RHS fuzzy sets</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>sets</strong> – fuzzy sets</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">lower bound value</td>
</tr>
</tbody>
</table>
</dd></dl>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
<dl class="method">
<dt id="pyFTS.models.multivariate.flrg.FLRG.get_membership">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">get_membership</code><span class="sig-paren">(</span><em>data</em>, <em>variables</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.flrg.FLRG.get_membership" title="Permalink to this definition"></a></dt>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
<dd><p>Returns the membership value of the FLRG for the input data</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> – input data</li>
<li><strong>sets</strong> – fuzzy sets</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">the membership value</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
Updating documentiation
2019-04-02 22:30:51 +04:00
<dl class="method">
<dt id="pyFTS.models.multivariate.flrg.FLRG.get_upper">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">get_upper</code><span class="sig-paren">(</span><em>sets</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.flrg.FLRG.get_upper" title="Permalink to this definition"></a></dt>
Updating documentiation
2019-04-02 22:30:51 +04:00
<dd><p>Returns the upper bound value for the RHS fuzzy sets</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>sets</strong> – fuzzy sets</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">upper bound value</td>
</tr>
</tbody>
</table>
</dd></dl>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
<dl class="method">
<dt id="pyFTS.models.multivariate.flrg.FLRG.set_lhs">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">set_lhs</code><span class="sig-paren">(</span><em>var</em>, <em>fset</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.flrg.FLRG.set_lhs" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
</dd></dl>
</div>
<div class="section" id="module-pyFTS.models.multivariate.partitioner">
<span id="pyfts-models-multivariate-partitioner-module"></span><h2>pyFTS.models.multivariate.partitioner module<a class="headerlink" href="#module-pyFTS.models.multivariate.partitioner" title="Permalink to this headline"></a></h2>
<dl class="class">
<dt id="pyFTS.models.multivariate.partitioner.MultivariatePartitioner">
<em class="property">class </em><code class="descclassname">pyFTS.models.multivariate.partitioner.</code><code class="descname">MultivariatePartitioner</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.partitioner.MultivariatePartitioner" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <a class="reference internal" href="pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner" title="pyFTS.partitioners.partitioner.Partitioner"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.partitioners.partitioner.Partitioner</span></code></a></p>
<p>Base class for partitioners which use the MultivariateFuzzySet</p>
<dl class="method">
<dt id="pyFTS.models.multivariate.partitioner.MultivariatePartitioner.append">
<code class="descname">append</code><span class="sig-paren">(</span><em>fset</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.partitioner.MultivariatePartitioner.append" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="pyFTS.models.multivariate.partitioner.MultivariatePartitioner.build">
<code class="descname">build</code><span class="sig-paren">(</span><em>data</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.partitioner.MultivariatePartitioner.build" title="Permalink to this definition"></a></dt>
<dd><p>Perform the partitioning of the Universe of Discourse</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>data</strong> – training data</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"></td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="pyFTS.models.multivariate.partitioner.MultivariatePartitioner.build_index">
<code class="descname">build_index</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.partitioner.MultivariatePartitioner.build_index" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="pyFTS.models.multivariate.partitioner.MultivariatePartitioner.change_target_variable">
<code class="descname">change_target_variable</code><span class="sig-paren">(</span><em>variable</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.partitioner.MultivariatePartitioner.change_target_variable" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="pyFTS.models.multivariate.partitioner.MultivariatePartitioner.format_data">
<code class="descname">format_data</code><span class="sig-paren">(</span><em>data</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.partitioner.MultivariatePartitioner.format_data" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="pyFTS.models.multivariate.partitioner.MultivariatePartitioner.fuzzyfy">
<code class="descname">fuzzyfy</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.partitioner.MultivariatePartitioner.fuzzyfy" title="Permalink to this definition"></a></dt>
<dd><p>Fuzzyfy the input data according to this partitioner fuzzy sets.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>data</strong> – input value to be fuzzyfied</li>
<li><strong>alpha_cut</strong> – the minimal membership value to be considered on fuzzyfication (only for mode=’sets’)</li>
<li><strong>method</strong> – the fuzzyfication method (fuzzy: all fuzzy memberships, maximum: only the maximum membership)</li>
<li><strong>mode</strong> – the fuzzyfication mode (sets: return the fuzzy sets names, vector: return a vector with the membership</li>
</ul>
</td>
</tr>
</tbody>
</table>
<p>values for all fuzzy sets, both: return a list with tuples (fuzzy set, membership value) )</p>
<p>:returns a list with the fuzzyfied values, depending on the mode</p>
</dd></dl>
<dl class="method">
<dt id="pyFTS.models.multivariate.partitioner.MultivariatePartitioner.prune">
<code class="descname">prune</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.partitioner.MultivariatePartitioner.prune" title="Permalink to this definition"></a></dt>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
<dd></dd></dl>
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<dl class="method">
<dt id="pyFTS.models.multivariate.partitioner.MultivariatePartitioner.search">
<code class="descname">search</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.partitioner.MultivariatePartitioner.search" title="Permalink to this definition"></a></dt>
<dd><p>Perform a search for the nearest fuzzy sets of the point ‘data’. This function were designed to work with several
overlapped fuzzy sets.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> – the value to search for the nearest fuzzy sets</li>
<li><strong>type</strong> – the return type: ‘index’ for the fuzzy set indexes or ‘name’ for fuzzy set names.</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a list with the nearest fuzzy sets</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
</dd></dl>
Documentation update
2019-04-22 17:01:58 +04:00
</div>
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<div class="section" id="module-pyFTS.models.multivariate.grid">
<span id="pyfts-models-multivariate-grid-module"></span><h2>pyFTS.models.multivariate.grid module<a class="headerlink" href="#module-pyFTS.models.multivariate.grid" title="Permalink to this headline"></a></h2>
<dl class="class">
Documentation update
2019-04-22 17:01:58 +04:00
<dt id="pyFTS.models.multivariate.grid.GridCluster">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<em class="property">class </em><code class="descclassname">pyFTS.models.multivariate.grid.</code><code class="descname">GridCluster</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.grid.GridCluster" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <a class="reference internal" href="#pyFTS.models.multivariate.partitioner.MultivariatePartitioner" title="pyFTS.models.multivariate.partitioner.MultivariatePartitioner"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.models.multivariate.partitioner.MultivariatePartitioner</span></code></a></p>
Documentation update
2019-04-22 17:01:58 +04:00
<p>A cartesian product of all fuzzy sets of all variables</p>
<dl class="method">
<dt id="pyFTS.models.multivariate.grid.GridCluster.build">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">build</code><span class="sig-paren">(</span><em>data</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.grid.GridCluster.build" title="Permalink to this definition"></a></dt>
Documentation update
2019-04-22 17:01:58 +04:00
<dd><p>Perform the partitioning of the Universe of Discourse</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>data</strong> – training data</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"></td>
</tr>
</tbody>
</table>
</dd></dl>
Documentation update
2019-06-21 18:34:49 +04:00
<dl class="method">
<dt id="pyFTS.models.multivariate.grid.GridCluster.defuzzyfy">
<code class="descname">defuzzyfy</code><span class="sig-paren">(</span><em>values</em>, <em>mode='both'</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.grid.GridCluster.defuzzyfy" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
Documentation update
2019-04-22 17:01:58 +04:00
</dd></dl>
<dl class="class">
<dt id="pyFTS.models.multivariate.grid.IncrementalGridCluster">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<em class="property">class </em><code class="descclassname">pyFTS.models.multivariate.grid.</code><code class="descname">IncrementalGridCluster</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.grid.IncrementalGridCluster" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <a class="reference internal" href="#pyFTS.models.multivariate.partitioner.MultivariatePartitioner" title="pyFTS.models.multivariate.partitioner.MultivariatePartitioner"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.models.multivariate.partitioner.MultivariatePartitioner</span></code></a></p>
Documentation update
2019-04-22 17:01:58 +04:00
<p>Create combinations of fuzzy sets of the variables on demand, incrementally increasing the
multivariate fuzzy set base.</p>
<dl class="method">
<dt id="pyFTS.models.multivariate.grid.IncrementalGridCluster.fuzzyfy">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">fuzzyfy</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.grid.IncrementalGridCluster.fuzzyfy" title="Permalink to this definition"></a></dt>
Documentation update
2019-04-22 17:01:58 +04:00
<dd><p>Fuzzyfy the input data according to this partitioner fuzzy sets.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>data</strong> – input value to be fuzzyfied</li>
<li><strong>alpha_cut</strong> – the minimal membership value to be considered on fuzzyfication (only for mode=’sets’)</li>
<li><strong>method</strong> – the fuzzyfication method (fuzzy: all fuzzy memberships, maximum: only the maximum membership)</li>
<li><strong>mode</strong> – the fuzzyfication mode (sets: return the fuzzy sets names, vector: return a vector with the membership</li>
</ul>
</td>
</tr>
</tbody>
</table>
<p>values for all fuzzy sets, both: return a list with tuples (fuzzy set, membership value) )</p>
<p>:returns a list with the fuzzyfied values, depending on the mode</p>
</dd></dl>
<dl class="method">
<dt id="pyFTS.models.multivariate.grid.IncrementalGridCluster.incremental_search">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">incremental_search</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.grid.IncrementalGridCluster.incremental_search" title="Permalink to this definition"></a></dt>
Documentation update
2019-04-22 17:01:58 +04:00
<dd></dd></dl>
<dl class="method">
<dt id="pyFTS.models.multivariate.grid.IncrementalGridCluster.prune">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">prune</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.grid.IncrementalGridCluster.prune" title="Permalink to this definition"></a></dt>
Documentation update
2019-04-22 17:01:58 +04:00
<dd></dd></dl>
</dd></dl>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
</div>
<div class="section" id="module-pyFTS.models.multivariate.mvfts">
<span id="pyfts-models-multivariate-mvfts-module"></span><h2>pyFTS.models.multivariate.mvfts module<a class="headerlink" href="#module-pyFTS.models.multivariate.mvfts" title="Permalink to this headline"></a></h2>
<dl class="class">
<dt id="pyFTS.models.multivariate.mvfts.MVFTS">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<em class="property">class </em><code class="descclassname">pyFTS.models.multivariate.mvfts.</code><code class="descname">MVFTS</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS" title="Permalink to this definition"></a></dt>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
<dd><p>Bases: <a class="reference internal" href="pyFTS.common.html#pyFTS.common.fts.FTS" title="pyFTS.common.fts.FTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.fts.FTS</span></code></a></p>
<p>Multivariate extension of Chen’s ConventionalFTS method</p>
<dl class="method">
<dt id="pyFTS.models.multivariate.mvfts.MVFTS.append_variable">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">append_variable</code><span class="sig-paren">(</span><em>var</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.append_variable" title="Permalink to this definition"></a></dt>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
<dd><p>Append a new endogenous variable to the model</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>var</strong> – variable object</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"></td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="pyFTS.models.multivariate.mvfts.MVFTS.apply_transformations">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">apply_transformations</code><span class="sig-paren">(</span><em>data</em>, <em>params=None</em>, <em>updateUoD=False</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.apply_transformations" title="Permalink to this definition"></a></dt>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
<dd><p>Apply the data transformations for data preprocessing</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> – input data</li>
<li><strong>params</strong> – transformation parameters</li>
<li><strong>updateUoD</strong> – </li>
<li><strong>kwargs</strong> – </li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">preprocessed data</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="pyFTS.models.multivariate.mvfts.MVFTS.clone_parameters">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">clone_parameters</code><span class="sig-paren">(</span><em>model</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.clone_parameters" title="Permalink to this definition"></a></dt>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
<dd><p>Import the parameters values from other model</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>model</strong> – </td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="pyFTS.models.multivariate.mvfts.MVFTS.forecast">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">forecast</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.forecast" title="Permalink to this definition"></a></dt>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
<dd><p>Point forecast one step ahead</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</li>
<li><strong>kwargs</strong> – model specific parameters</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a list with the forecasted values</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
Documentation update
2018-11-13 18:11:49 +04:00
<dl class="method">
<dt id="pyFTS.models.multivariate.mvfts.MVFTS.forecast_ahead">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">forecast_ahead</code><span class="sig-paren">(</span><em>data</em>, <em>steps</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.forecast_ahead" title="Permalink to this definition"></a></dt>
Documentation update
2018-11-13 18:11:49 +04:00
<dd><p>Point forecast n steps ahead</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</li>
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<li><strong>steps</strong> – the number of steps ahead to forecast (default: 1)</li>
<li><strong>start_at</strong> – in the multi step forecasting, the index of the data where to start forecasting (default: 0)</li>
Documentation update
2018-11-13 18:11:49 +04:00
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a list with the forecasted values</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<dl class="method">
<dt id="pyFTS.models.multivariate.mvfts.MVFTS.forecast_ahead_interval">
<code class="descname">forecast_ahead_interval</code><span class="sig-paren">(</span><em>data</em>, <em>steps</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.forecast_ahead_interval" title="Permalink to this definition"></a></dt>
<dd><p>Interval forecast n steps ahead</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</li>
<li><strong>steps</strong> – the number of steps ahead to forecast</li>
<li><strong>start_at</strong> – in the multi step forecasting, the index of the data where to start forecasting (default: 0)</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a list with the forecasted intervals</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
Updating documentiation
2019-04-02 22:30:51 +04:00
<dl class="method">
<dt id="pyFTS.models.multivariate.mvfts.MVFTS.forecast_interval">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">forecast_interval</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.forecast_interval" title="Permalink to this definition"></a></dt>
Updating documentiation
2019-04-02 22:30:51 +04:00
<dd><p>Interval forecast one step ahead</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</li>
<li><strong>kwargs</strong> – model specific parameters</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a list with the prediction intervals</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
Sphinx documentation for ReadTheDocs site
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<dl class="method">
<dt id="pyFTS.models.multivariate.mvfts.MVFTS.format_data">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">format_data</code><span class="sig-paren">(</span><em>data</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.format_data" title="Permalink to this definition"></a></dt>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
<dd></dd></dl>
<dl class="method">
<dt id="pyFTS.models.multivariate.mvfts.MVFTS.generate_flrg">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">generate_flrg</code><span class="sig-paren">(</span><em>flrs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.generate_flrg" title="Permalink to this definition"></a></dt>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
<dd></dd></dl>
<dl class="method">
<dt id="pyFTS.models.multivariate.mvfts.MVFTS.generate_flrs">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">generate_flrs</code><span class="sig-paren">(</span><em>data</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.generate_flrs" title="Permalink to this definition"></a></dt>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
<dd></dd></dl>
<dl class="method">
<dt id="pyFTS.models.multivariate.mvfts.MVFTS.generate_lhs_flrs">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">generate_lhs_flrs</code><span class="sig-paren">(</span><em>data</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.generate_lhs_flrs" title="Permalink to this definition"></a></dt>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
<dd></dd></dl>
<dl class="method">
<dt id="pyFTS.models.multivariate.mvfts.MVFTS.train">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">train</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.train" title="Permalink to this definition"></a></dt>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
<dd><p>Method specific parameter fitting</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>data</strong> – training time series data</li>
<li><strong>kwargs</strong> – Method specific parameters</li>
</ul>
</td>
</tr>
</tbody>
</table>
</dd></dl>
</dd></dl>
Updating the documentation
2019-02-21 19:00:09 +04:00
<dl class="function">
<dt id="pyFTS.models.multivariate.mvfts.product_dict">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descclassname">pyFTS.models.multivariate.mvfts.</code><code class="descname">product_dict</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.product_dict" title="Permalink to this definition"></a></dt>
Updating the documentation
2019-02-21 19:00:09 +04:00
<dd><p>Code by Seth Johnson
:param kwargs:
:return:</p>
</dd></dl>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
</div>
Documentation update
2018-11-13 18:11:49 +04:00
<div class="section" id="module-pyFTS.models.multivariate.wmvfts">
<span id="pyfts-models-multivariate-wmvfts-module"></span><h2>pyFTS.models.multivariate.wmvfts module<a class="headerlink" href="#module-pyFTS.models.multivariate.wmvfts" title="Permalink to this headline"></a></h2>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
<dl class="class">
Documentation update
2018-11-13 18:11:49 +04:00
<dt id="pyFTS.models.multivariate.wmvfts.WeightedFLRG">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<em class="property">class </em><code class="descclassname">pyFTS.models.multivariate.wmvfts.</code><code class="descname">WeightedFLRG</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedFLRG" title="Permalink to this definition"></a></dt>
Documentation update
2018-11-13 18:11:49 +04:00
<dd><p>Bases: <a class="reference internal" href="#pyFTS.models.multivariate.flrg.FLRG" title="pyFTS.models.multivariate.flrg.FLRG"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.models.multivariate.flrg.FLRG</span></code></a></p>
<p>Weighted Multivariate Fuzzy Logical Rule Group</p>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
<dl class="method">
Documentation update
2018-11-13 18:11:49 +04:00
<dt id="pyFTS.models.multivariate.wmvfts.WeightedFLRG.append_rhs">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">append_rhs</code><span class="sig-paren">(</span><em>fset</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedFLRG.append_rhs" title="Permalink to this definition"></a></dt>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
<dd></dd></dl>
Updating documentiation
2019-04-02 22:30:51 +04:00
<dl class="method">
<dt id="pyFTS.models.multivariate.wmvfts.WeightedFLRG.get_lower">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">get_lower</code><span class="sig-paren">(</span><em>sets</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedFLRG.get_lower" title="Permalink to this definition"></a></dt>
Updating documentiation
2019-04-02 22:30:51 +04:00
<dd><p>Returns the lower bound value for the RHS fuzzy sets</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>sets</strong> – fuzzy sets</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">lower bound value</td>
</tr>
</tbody>
</table>
</dd></dl>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
<dl class="method">
Documentation update
2018-11-13 18:11:49 +04:00
<dt id="pyFTS.models.multivariate.wmvfts.WeightedFLRG.get_midpoint">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">get_midpoint</code><span class="sig-paren">(</span><em>sets</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedFLRG.get_midpoint" title="Permalink to this definition"></a></dt>
Documentation update
2018-11-13 18:11:49 +04:00
<dd><p>Returns the midpoint value for the RHS fuzzy sets</p>
<table class="docutils field-list" frame="void" rules="none">
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
Documentation update
2018-11-13 18:11:49 +04:00
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>sets</strong> – fuzzy sets</td>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
</tr>
Documentation update
2018-11-13 18:11:49 +04:00
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">the midpoint value</td>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
</tr>
</tbody>
</table>
</dd></dl>
Updating documentiation
2019-04-02 22:30:51 +04:00
<dl class="method">
<dt id="pyFTS.models.multivariate.wmvfts.WeightedFLRG.get_upper">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">get_upper</code><span class="sig-paren">(</span><em>sets</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedFLRG.get_upper" title="Permalink to this definition"></a></dt>
Updating documentiation
2019-04-02 22:30:51 +04:00
<dd><p>Returns the upper bound value for the RHS fuzzy sets</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>sets</strong> – fuzzy sets</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">upper bound value</td>
</tr>
</tbody>
</table>
</dd></dl>
Documentation update
2018-11-13 18:11:49 +04:00
<dl class="method">
<dt id="pyFTS.models.multivariate.wmvfts.WeightedFLRG.weights">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">weights</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedFLRG.weights" title="Permalink to this definition"></a></dt>
Documentation update
2018-11-13 18:11:49 +04:00
<dd></dd></dl>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
</dd></dl>
Documentation update
2018-11-13 18:11:49 +04:00
<dl class="class">
<dt id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<em class="property">class </em><code class="descclassname">pyFTS.models.multivariate.wmvfts.</code><code class="descname">WeightedMVFTS</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS" title="Permalink to this definition"></a></dt>
Documentation update
2018-11-13 18:11:49 +04:00
<dd><p>Bases: <a class="reference internal" href="#pyFTS.models.multivariate.mvfts.MVFTS" title="pyFTS.models.multivariate.mvfts.MVFTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.models.multivariate.mvfts.MVFTS</span></code></a></p>
<p>Weighted Multivariate FTS</p>
<dl class="method">
<dt id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.generate_flrg">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">generate_flrg</code><span class="sig-paren">(</span><em>flrs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.generate_flrg" title="Permalink to this definition"></a></dt>
Documentation update
2018-11-13 18:11:49 +04:00
<dd></dd></dl>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
</dd></dl>
</div>
Documentation update
2018-11-13 18:11:49 +04:00
<div class="section" id="module-pyFTS.models.multivariate.cmvfts">
<span id="pyfts-models-multivariate-cmvfts-module"></span><h2>pyFTS.models.multivariate.cmvfts module<a class="headerlink" href="#module-pyFTS.models.multivariate.cmvfts" title="Permalink to this headline"></a></h2>
<dl class="class">
<dt id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<em class="property">class </em><code class="descclassname">pyFTS.models.multivariate.cmvfts.</code><code class="descname">ClusteredMVFTS</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS" title="Permalink to this definition"></a></dt>
Documentation update
2018-11-13 18:11:49 +04:00
<dd><p>Bases: <a class="reference internal" href="#pyFTS.models.multivariate.mvfts.MVFTS" title="pyFTS.models.multivariate.mvfts.MVFTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.models.multivariate.mvfts.MVFTS</span></code></a></p>
Documentation update
2019-04-22 17:01:58 +04:00
<p>Meta model for high order, clustered multivariate FTS</p>
Updating documentation
2018-12-12 00:27:18 +04:00
<dl class="method">
<dt id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.check_data">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">check_data</code><span class="sig-paren">(</span><em>data</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.check_data" title="Permalink to this definition"></a></dt>
Updating documentation
2018-12-12 00:27:18 +04:00
<dd></dd></dl>
Updating the documentation
2018-11-09 23:49:39 +04:00
<dl class="method">
Documentation update
2018-11-13 18:11:49 +04:00
<dt id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.forecast">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">forecast</code><span class="sig-paren">(</span><em>ndata</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.forecast" title="Permalink to this definition"></a></dt>
Updating the documentation
2018-11-09 23:49:39 +04:00
<dd><p>Point forecast one step ahead</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</li>
<li><strong>kwargs</strong> – model specific parameters</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a list with the forecasted values</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
Documentation update
2019-06-21 18:34:49 +04:00
<dl class="method">
<dt id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.forecast_ahead_distribution">
<code class="descname">forecast_ahead_distribution</code><span class="sig-paren">(</span><em>data</em>, <em>steps</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.forecast_ahead_distribution" title="Permalink to this definition"></a></dt>
<dd><p>Probabilistic forecast n steps ahead</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</li>
<li><strong>steps</strong> – the number of steps ahead to forecast</li>
<li><strong>start_at</strong> – in the multi step forecasting, the index of the data where to start forecasting (default: 0)</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a list with the forecasted Probability Distributions</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.forecast_ahead_interval">
<code class="descname">forecast_ahead_interval</code><span class="sig-paren">(</span><em>data</em>, <em>steps</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.forecast_ahead_interval" title="Permalink to this definition"></a></dt>
<dd><p>Interval forecast n steps ahead</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</li>
<li><strong>steps</strong> – the number of steps ahead to forecast</li>
<li><strong>start_at</strong> – in the multi step forecasting, the index of the data where to start forecasting (default: 0)</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a list with the forecasted intervals</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
Documentation update
2019-04-22 17:01:58 +04:00
<dl class="method">
<dt id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.forecast_ahead_multivariate">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">forecast_ahead_multivariate</code><span class="sig-paren">(</span><em>data</em>, <em>steps</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.forecast_ahead_multivariate" title="Permalink to this definition"></a></dt>
Documentation update
2019-04-22 17:01:58 +04:00
<dd><p>Multivariate forecast n step ahead</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> – Pandas dataframe with one column for each variable and with the minimal length equal to the max_lag of the model</li>
<li><strong>steps</strong> – the number of steps ahead to forecast</li>
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<li><strong>start_at</strong> – in the multi step forecasting, the index of the data where to start forecasting (default: 0)</li>
Documentation update
2019-04-22 17:01:58 +04:00
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a Pandas Dataframe object representing the forecasted values for each variable</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
Documentation update
2019-06-21 18:34:49 +04:00
<dl class="method">
<dt id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.forecast_distribution">
<code class="descname">forecast_distribution</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.forecast_distribution" title="Permalink to this definition"></a></dt>
<dd><p>Probabilistic forecast one step ahead</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</li>
<li><strong>kwargs</strong> – model specific parameters</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a list with probabilistic.ProbabilityDistribution objects representing the forecasted Probability Distributions</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.forecast_interval">
<code class="descname">forecast_interval</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.forecast_interval" title="Permalink to this definition"></a></dt>
<dd><p>Interval forecast one step ahead</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</li>
<li><strong>kwargs</strong> – model specific parameters</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a list with the prediction intervals</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
Updating documentation
2018-12-12 00:27:18 +04:00
<dl class="method">
<dt id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.forecast_multivariate">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">forecast_multivariate</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.forecast_multivariate" title="Permalink to this definition"></a></dt>
Updating documentation
2018-12-12 00:27:18 +04:00
<dd><p>Multivariate forecast one step ahead</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>data</strong> – Pandas dataframe with one column for each variable and with the minimal length equal to the max_lag of the model</li>
<li><strong>kwargs</strong> – model specific parameters</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">a Pandas Dataframe object representing the forecasted values for each variable</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
Updating the documentation
2018-11-09 23:49:39 +04:00
<dl class="method">
Documentation update
2018-11-13 18:11:49 +04:00
<dt id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.fuzzyfy">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">fuzzyfy</code><span class="sig-paren">(</span><em>data</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.fuzzyfy" title="Permalink to this definition"></a></dt>
Updating the documentation
2018-11-09 23:49:39 +04:00
<dd></dd></dl>
<dl class="method">
Documentation update
2018-11-13 18:11:49 +04:00
<dt id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.train">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">train</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.train" title="Permalink to this definition"></a></dt>
Updating the documentation
2018-11-09 23:49:39 +04:00
<dd><p>Method specific parameter fitting</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>data</strong> – training time series data</li>
<li><strong>kwargs</strong> – Method specific parameters</li>
</ul>
</td>
</tr>
</tbody>
</table>
</dd></dl>
</dd></dl>
Documentation update
2019-04-22 17:01:58 +04:00
</div>
<div class="section" id="module-pyFTS.models.multivariate.granular">
<span id="pyfts-models-multivariate-granular-module"></span><h2>pyFTS.models.multivariate.granular module<a class="headerlink" href="#module-pyFTS.models.multivariate.granular" title="Permalink to this headline"></a></h2>
<dl class="class">
<dt id="pyFTS.models.multivariate.granular.GranularWMVFTS">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<em class="property">class </em><code class="descclassname">pyFTS.models.multivariate.granular.</code><code class="descname">GranularWMVFTS</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS" title="Permalink to this definition"></a></dt>
Documentation update
2019-04-22 17:01:58 +04:00
<dd><p>Bases: <a class="reference internal" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS" title="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.models.multivariate.cmvfts.ClusteredMVFTS</span></code></a></p>
<p>Granular multivariate weighted high order FTS</p>
<dl class="method">
<dt id="pyFTS.models.multivariate.granular.GranularWMVFTS.train">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<code class="descname">train</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.train" title="Permalink to this definition"></a></dt>
Documentation update
2019-04-22 17:01:58 +04:00
<dd><p>Method specific parameter fitting</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>data</strong> – training time series data</li>
<li><strong>kwargs</strong> – Method specific parameters</li>
</ul>
</td>
</tr>
</tbody>
</table>
</dd></dl>
</dd></dl>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
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Updating the documentation
2018-08-30 23:04:52 +04:00
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