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<li><a class="reference internal" href="#">pyFTS.models package</a><ul>
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<li><a class="reference internal" href="#module-pyFTS.models">Module contents</a></li>
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<li><a class="reference internal" href="#subpackages">Subpackages</a></li>
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<li><a class="reference internal" href="#submodules">Submodules</a></li>
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<li><a class="reference internal" href="#module-pyFTS.models.song">pyFTS.models.song module</a></li>
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<li><a class="reference internal" href="#module-pyFTS.models.chen">pyFTS.models.chen module</a></li>
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<li><a class="reference internal" href="#module-pyFTS.models.yu">pyFTS.models.yu module</a></li>
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<li><a class="reference internal" href="#module-pyFTS.models.cheng">pyFTS.models.cheng module</a></li>
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<div class="section" id="pyfts-models-package">
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<h1>pyFTS.models package<a class="headerlink" href="#pyfts-models-package" title="Permalink to this headline">¶</a></h1>
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<div class="section" id="module-pyFTS.models">
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<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-pyFTS.models" title="Permalink to this headline">¶</a></h2>
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<p>Fuzzy Time Series methods</p>
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<h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to this headline">¶</a></h2>
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<li class="toctree-l2"><a class="reference internal" href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate">Module contents</a></li>
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<li class="toctree-l2"><a class="reference internal" href="pyFTS.models.nonstationary.html#module-pyFTS.models.nonstationary.cvfts">pyFTS.models.nonstationary.cvfts module</a></li>
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<li class="toctree-l2"><a class="reference internal" href="pyFTS.models.nonstationary.html#module-pyFTS.models.nonstationary.flrg">pyFTS.models.nonstationary.flrg module</a></li>
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<li class="toctree-l2"><a class="reference internal" href="pyFTS.models.nonstationary.html#module-pyFTS.models.nonstationary.honsfts">pyFTS.models.nonstationary.honsfts module</a></li>
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<li class="toctree-l2"><a class="reference internal" href="pyFTS.models.nonstationary.html#module-pyFTS.models.nonstationary.nsfts">pyFTS.models.nonstationary.nsfts module</a></li>
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<li class="toctree-l2"><a class="reference internal" href="pyFTS.models.nonstationary.html#module-pyFTS.models.nonstationary.partitioners">pyFTS.models.nonstationary.partitioners module</a></li>
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<li class="toctree-l2"><a class="reference internal" href="pyFTS.models.nonstationary.html#module-pyFTS.models.nonstationary.perturbation">pyFTS.models.nonstationary.perturbation module</a></li>
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<li class="toctree-l2"><a class="reference internal" href="pyFTS.models.nonstationary.html#module-pyFTS.models.nonstationary.util">pyFTS.models.nonstationary.util module</a></li>
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<li class="toctree-l1"><a class="reference internal" href="pyFTS.models.seasonal.html">pyFTS.models.seasonal package</a><ul>
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<li class="toctree-l2"><a class="reference internal" href="pyFTS.models.seasonal.html#module-pyFTS.models.seasonal.SeasonalIndexer">pyFTS.models.seasonal.SeasonalIndexer module</a></li>
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<li class="toctree-l2"><a class="reference internal" href="pyFTS.models.seasonal.html#module-pyFTS.models.seasonal.cmsfts">pyFTS.models.seasonal.cmsfts module</a></li>
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<li class="toctree-l2"><a class="reference internal" href="pyFTS.models.seasonal.html#module-pyFTS.models.seasonal.common">pyFTS.models.seasonal.common module</a></li>
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<li class="toctree-l2"><a class="reference internal" href="pyFTS.models.seasonal.html#module-pyFTS.models.seasonal.msfts">pyFTS.models.seasonal.msfts module</a></li>
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<li class="toctree-l2"><a class="reference internal" href="pyFTS.models.seasonal.html#module-pyFTS.models.seasonal.partitioner">pyFTS.models.seasonal.partitioner module</a></li>
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<li class="toctree-l2"><a class="reference internal" href="pyFTS.models.seasonal.html#module-pyFTS.models.seasonal.sfts">pyFTS.models.seasonal.sfts module</a></li>
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<li class="toctree-l2"><a class="reference internal" href="pyFTS.models.seasonal.html#module-pyFTS.models.seasonal">Module contents</a></li>
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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.song">
|
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<span id="pyfts-models-song-module"></span><h2>pyFTS.models.song module<a class="headerlink" href="#module-pyFTS.models.song" title="Permalink to this headline">¶</a></h2>
|
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<p>First Order Traditional Fuzzy Time Series method by Song & Chissom (1993)</p>
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<ol class="upperalpha simple" start="17">
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<li>Song and B. S. Chissom, “Fuzzy time series and its models,” Fuzzy Sets Syst., vol. 54, no. 3, pp. 269–277, 1993.</li>
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</ol>
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<dl class="class">
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<dt id="pyFTS.models.song.ConventionalFTS">
|
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<em class="property">class </em><code class="descclassname">pyFTS.models.song.</code><code class="descname">ConventionalFTS</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/song.html#ConventionalFTS"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS" 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>Traditional Fuzzy Time Series</p>
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<dl class="method">
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<dt id="pyFTS.models.song.ConventionalFTS.flr_membership_matrix">
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<code class="descname">flr_membership_matrix</code><span class="sig-paren">(</span><em>flr</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/song.html#ConventionalFTS.flr_membership_matrix"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.flr_membership_matrix" title="Permalink to this definition">¶</a></dt>
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<dd></dd></dl>
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<dl class="method">
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<dt id="pyFTS.models.song.ConventionalFTS.forecast">
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<code class="descname">forecast</code><span class="sig-paren">(</span><em>ndata</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/song.html#ConventionalFTS.forecast"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.forecast" title="Permalink to this definition">¶</a></dt>
|
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<dd><p>Point forecast one step ahead</p>
|
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<table class="docutils field-list" frame="void" rules="none">
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<col class="field-name" />
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||
<col class="field-body" />
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||
<tbody valign="top">
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||
<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>
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</ul>
|
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</td>
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</tr>
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<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>
|
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</td>
|
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</tr>
|
||
</tbody>
|
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</table>
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</dd></dl>
|
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|
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<dl class="method">
|
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<dt id="pyFTS.models.song.ConventionalFTS.operation_matrix">
|
||
<code class="descname">operation_matrix</code><span class="sig-paren">(</span><em>flrs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/song.html#ConventionalFTS.operation_matrix"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.operation_matrix" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.song.ConventionalFTS.train">
|
||
<code class="descname">train</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/song.html#ConventionalFTS.train"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.song.ConventionalFTS.train" title="Permalink to this definition">¶</a></dt>
|
||
<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>
|
||
|
||
</div>
|
||
<div class="section" id="module-pyFTS.models.chen">
|
||
<span id="pyfts-models-chen-module"></span><h2>pyFTS.models.chen module<a class="headerlink" href="#module-pyFTS.models.chen" title="Permalink to this headline">¶</a></h2>
|
||
<p>First Order Conventional Fuzzy Time Series by Chen (1996)</p>
|
||
<p>S.-M. Chen, “Forecasting enrollments based on fuzzy time series,” Fuzzy Sets Syst., vol. 81, no. 3, pp. 311–319, 1996.</p>
|
||
<dl class="class">
|
||
<dt id="pyFTS.models.chen.ConventionalFLRG">
|
||
<em class="property">class </em><code class="descclassname">pyFTS.models.chen.</code><code class="descname">ConventionalFLRG</code><span class="sig-paren">(</span><em>LHS</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/chen.html#ConventionalFLRG"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.chen.ConventionalFLRG" title="Permalink to this definition">¶</a></dt>
|
||
<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>First Order Conventional Fuzzy Logical Relationship Group</p>
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.chen.ConventionalFLRG.append_rhs">
|
||
<code class="descname">append_rhs</code><span class="sig-paren">(</span><em>c</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/chen.html#ConventionalFLRG.append_rhs"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.chen.ConventionalFLRG.append_rhs" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.chen.ConventionalFLRG.get_key">
|
||
<code class="descname">get_key</code><span class="sig-paren">(</span><em>sets</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/chen.html#ConventionalFLRG.get_key"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.chen.ConventionalFLRG.get_key" title="Permalink to this definition">¶</a></dt>
|
||
<dd><p>Returns a unique identifier for this FLRG</p>
|
||
</dd></dl>
|
||
|
||
</dd></dl>
|
||
|
||
<dl class="class">
|
||
<dt id="pyFTS.models.chen.ConventionalFTS">
|
||
<em class="property">class </em><code class="descclassname">pyFTS.models.chen.</code><code class="descname">ConventionalFTS</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/chen.html#ConventionalFTS"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS" title="Permalink to this definition">¶</a></dt>
|
||
<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>Conventional Fuzzy Time Series</p>
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.chen.ConventionalFTS.forecast">
|
||
<code class="descname">forecast</code><span class="sig-paren">(</span><em>ndata</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/chen.html#ConventionalFTS.forecast"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.forecast" title="Permalink to this definition">¶</a></dt>
|
||
<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>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.chen.ConventionalFTS.generate_flrg">
|
||
<code class="descname">generate_flrg</code><span class="sig-paren">(</span><em>flrs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/chen.html#ConventionalFTS.generate_flrg"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.generate_flrg" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.chen.ConventionalFTS.train">
|
||
<code class="descname">train</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/chen.html#ConventionalFTS.train"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.chen.ConventionalFTS.train" title="Permalink to this definition">¶</a></dt>
|
||
<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>
|
||
|
||
</div>
|
||
<div class="section" id="module-pyFTS.models.yu">
|
||
<span id="pyfts-models-yu-module"></span><h2>pyFTS.models.yu module<a class="headerlink" href="#module-pyFTS.models.yu" title="Permalink to this headline">¶</a></h2>
|
||
<p>First Order Weighted Fuzzy Time Series by Yu(2005)</p>
|
||
<p>H.-K. Yu, “Weighted fuzzy time series models for TAIEX forecasting,”
|
||
Phys. A Stat. Mech. its Appl., vol. 349, no. 3, pp. 609–624, 2005.</p>
|
||
<dl class="class">
|
||
<dt id="pyFTS.models.yu.WeightedFLRG">
|
||
<em class="property">class </em><code class="descclassname">pyFTS.models.yu.</code><code class="descname">WeightedFLRG</code><span class="sig-paren">(</span><em>LHS</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/yu.html#WeightedFLRG"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.yu.WeightedFLRG" title="Permalink to this definition">¶</a></dt>
|
||
<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>First Order Weighted Fuzzy Logical Relationship Group</p>
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.yu.WeightedFLRG.append_rhs">
|
||
<code class="descname">append_rhs</code><span class="sig-paren">(</span><em>c</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/yu.html#WeightedFLRG.append_rhs"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.yu.WeightedFLRG.append_rhs" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.yu.WeightedFLRG.weights">
|
||
<code class="descname">weights</code><span class="sig-paren">(</span><em>sets</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/yu.html#WeightedFLRG.weights"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.yu.WeightedFLRG.weights" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
</dd></dl>
|
||
|
||
<dl class="class">
|
||
<dt id="pyFTS.models.yu.WeightedFTS">
|
||
<em class="property">class </em><code class="descclassname">pyFTS.models.yu.</code><code class="descname">WeightedFTS</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/yu.html#WeightedFTS"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS" title="Permalink to this definition">¶</a></dt>
|
||
<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>First Order Weighted Fuzzy Time Series</p>
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.yu.WeightedFTS.forecast">
|
||
<code class="descname">forecast</code><span class="sig-paren">(</span><em>ndata</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/yu.html#WeightedFTS.forecast"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.forecast" title="Permalink to this definition">¶</a></dt>
|
||
<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>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.yu.WeightedFTS.generate_FLRG">
|
||
<code class="descname">generate_FLRG</code><span class="sig-paren">(</span><em>flrs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/yu.html#WeightedFTS.generate_FLRG"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.generate_FLRG" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.yu.WeightedFTS.train">
|
||
<code class="descname">train</code><span class="sig-paren">(</span><em>ndata</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/yu.html#WeightedFTS.train"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.yu.WeightedFTS.train" title="Permalink to this definition">¶</a></dt>
|
||
<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>
|
||
|
||
</div>
|
||
<div class="section" id="module-pyFTS.models.cheng">
|
||
<span id="pyfts-models-cheng-module"></span><h2>pyFTS.models.cheng module<a class="headerlink" href="#module-pyFTS.models.cheng" title="Permalink to this headline">¶</a></h2>
|
||
<p>Trend Weighted Fuzzy Time Series by Cheng, Chen and Wu (2009)</p>
|
||
<p>C.-H. Cheng, Y.-S. Chen, and Y.-L. Wu, “Forecasting innovation diffusion of products using trend-weighted fuzzy time-series model,”
|
||
Expert Syst. Appl., vol. 36, no. 2, pp. 1826–1832, 2009.</p>
|
||
<dl class="class">
|
||
<dt id="pyFTS.models.cheng.TrendWeightedFLRG">
|
||
<em class="property">class </em><code class="descclassname">pyFTS.models.cheng.</code><code class="descname">TrendWeightedFLRG</code><span class="sig-paren">(</span><em>LHS</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/cheng.html#TrendWeightedFLRG"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFLRG" title="Permalink to this definition">¶</a></dt>
|
||
<dd><p>Bases: <a class="reference internal" href="#pyFTS.models.yu.WeightedFLRG" title="pyFTS.models.yu.WeightedFLRG"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.models.yu.WeightedFLRG</span></code></a></p>
|
||
<p>First Order Trend Weighted Fuzzy Logical Relationship Group</p>
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.cheng.TrendWeightedFLRG.weights">
|
||
<code class="descname">weights</code><span class="sig-paren">(</span><em>sets</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/cheng.html#TrendWeightedFLRG.weights"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFLRG.weights" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
</dd></dl>
|
||
|
||
<dl class="class">
|
||
<dt id="pyFTS.models.cheng.TrendWeightedFTS">
|
||
<em class="property">class </em><code class="descclassname">pyFTS.models.cheng.</code><code class="descname">TrendWeightedFTS</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/cheng.html#TrendWeightedFTS"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS" title="Permalink to this definition">¶</a></dt>
|
||
<dd><p>Bases: <a class="reference internal" href="#pyFTS.models.yu.WeightedFTS" title="pyFTS.models.yu.WeightedFTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.models.yu.WeightedFTS</span></code></a></p>
|
||
<p>First Order Trend Weighted Fuzzy Time Series</p>
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.cheng.TrendWeightedFTS.generate_FLRG">
|
||
<code class="descname">generate_FLRG</code><span class="sig-paren">(</span><em>flrs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/cheng.html#TrendWeightedFTS.generate_FLRG"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.cheng.TrendWeightedFTS.generate_FLRG" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
</dd></dl>
|
||
|
||
</div>
|
||
<div class="section" id="module-pyFTS.models.hofts">
|
||
<span id="pyfts-models-hofts-module"></span><h2>pyFTS.models.hofts module<a class="headerlink" href="#module-pyFTS.models.hofts" title="Permalink to this headline">¶</a></h2>
|
||
<p>High Order FTS</p>
|
||
<p>Severiano, S. A. Jr; Silva, P. C. L.; Sadaei, H. J.; Guimarães, F. G. Very Short-term Solar Forecasting
|
||
using Fuzzy Time Series. 2017 IEEE International Conference on Fuzzy Systems. DOI10.1109/FUZZ-IEEE.2017.8015732</p>
|
||
<dl class="class">
|
||
<dt id="pyFTS.models.hofts.HighOrderFLRG">
|
||
<em class="property">class </em><code class="descclassname">pyFTS.models.hofts.</code><code class="descname">HighOrderFLRG</code><span class="sig-paren">(</span><em>order</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#HighOrderFLRG"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFLRG" title="Permalink to this definition">¶</a></dt>
|
||
<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>Conventional High Order Fuzzy Logical Relationship Group</p>
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.hofts.HighOrderFLRG.append_lhs">
|
||
<code class="descname">append_lhs</code><span class="sig-paren">(</span><em>c</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#HighOrderFLRG.append_lhs"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFLRG.append_lhs" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.hofts.HighOrderFLRG.append_rhs">
|
||
<code class="descname">append_rhs</code><span class="sig-paren">(</span><em>c</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#HighOrderFLRG.append_rhs"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFLRG.append_rhs" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
</dd></dl>
|
||
|
||
<dl class="class">
|
||
<dt id="pyFTS.models.hofts.HighOrderFTS">
|
||
<em class="property">class </em><code class="descclassname">pyFTS.models.hofts.</code><code class="descname">HighOrderFTS</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#HighOrderFTS"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS" title="Permalink to this definition">¶</a></dt>
|
||
<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>Conventional High Order Fuzzy Time Series</p>
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.hofts.HighOrderFTS.configure_lags">
|
||
<code class="descname">configure_lags</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#HighOrderFTS.configure_lags"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.configure_lags" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.hofts.HighOrderFTS.forecast">
|
||
<code class="descname">forecast</code><span class="sig-paren">(</span><em>ndata</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#HighOrderFTS.forecast"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.forecast" title="Permalink to this definition">¶</a></dt>
|
||
<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>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.hofts.HighOrderFTS.generate_flrg">
|
||
<code class="descname">generate_flrg</code><span class="sig-paren">(</span><em>data</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#HighOrderFTS.generate_flrg"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.generate_flrg" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.hofts.HighOrderFTS.generate_lhs_flrg">
|
||
<code class="descname">generate_lhs_flrg</code><span class="sig-paren">(</span><em>sample</em>, <em>explain=False</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#HighOrderFTS.generate_lhs_flrg"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.generate_lhs_flrg" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.hofts.HighOrderFTS.train">
|
||
<code class="descname">train</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#HighOrderFTS.train"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.train" title="Permalink to this definition">¶</a></dt>
|
||
<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>
|
||
|
||
</div>
|
||
<div class="section" id="module-pyFTS.models.hwang">
|
||
<span id="pyfts-models-hwang-module"></span><h2>pyFTS.models.hwang module<a class="headerlink" href="#module-pyFTS.models.hwang" title="Permalink to this headline">¶</a></h2>
|
||
<p>High Order Fuzzy Time Series by Hwang, Chen and Lee (1998)</p>
|
||
<p>Jeng-Ren Hwang, Shyi-Ming Chen, and Chia-Hoang Lee, “Handling forecasting problems using fuzzy time series,”
|
||
Fuzzy Sets Syst., no. 100, pp. 217–228, 1998.</p>
|
||
<dl class="class">
|
||
<dt id="pyFTS.models.hwang.HighOrderFTS">
|
||
<em class="property">class </em><code class="descclassname">pyFTS.models.hwang.</code><code class="descname">HighOrderFTS</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hwang.html#HighOrderFTS"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS" title="Permalink to this definition">¶</a></dt>
|
||
<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>
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.hwang.HighOrderFTS.configure_lags">
|
||
<code class="descname">configure_lags</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hwang.html#HighOrderFTS.configure_lags"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.configure_lags" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.hwang.HighOrderFTS.forecast">
|
||
<code class="descname">forecast</code><span class="sig-paren">(</span><em>ndata</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hwang.html#HighOrderFTS.forecast"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.forecast" title="Permalink to this definition">¶</a></dt>
|
||
<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>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.hwang.HighOrderFTS.train">
|
||
<code class="descname">train</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hwang.html#HighOrderFTS.train"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.hwang.HighOrderFTS.train" title="Permalink to this definition">¶</a></dt>
|
||
<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>
|
||
|
||
</div>
|
||
<div class="section" id="module-pyFTS.models.ifts">
|
||
<span id="pyfts-models-ifts-module"></span><h2>pyFTS.models.ifts module<a class="headerlink" href="#module-pyFTS.models.ifts" title="Permalink to this headline">¶</a></h2>
|
||
<p>High Order Interval Fuzzy Time Series</p>
|
||
<p>SILVA, Petrônio CL; SADAEI, Hossein Javedani; GUIMARÃES, Frederico Gadelha. Interval Forecasting with Fuzzy Time Series.
|
||
In: Computational Intelligence (SSCI), 2016 IEEE Symposium Series on. IEEE, 2016. p. 1-8.</p>
|
||
<dl class="class">
|
||
<dt id="pyFTS.models.ifts.IntervalFTS">
|
||
<em class="property">class </em><code class="descclassname">pyFTS.models.ifts.</code><code class="descname">IntervalFTS</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ifts.html#IntervalFTS"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS" title="Permalink to this definition">¶</a></dt>
|
||
<dd><p>Bases: <a class="reference internal" href="#pyFTS.models.hofts.HighOrderFTS" title="pyFTS.models.hofts.HighOrderFTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.models.hofts.HighOrderFTS</span></code></a></p>
|
||
<p>High Order Interval Fuzzy Time Series</p>
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.ifts.IntervalFTS.forecast_interval">
|
||
<code class="descname">forecast_interval</code><span class="sig-paren">(</span><em>ndata</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ifts.html#IntervalFTS.forecast_interval"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.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>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.ifts.IntervalFTS.get_lower">
|
||
<code class="descname">get_lower</code><span class="sig-paren">(</span><em>flrg</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ifts.html#IntervalFTS.get_lower"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.get_lower" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.ifts.IntervalFTS.get_sequence_membership">
|
||
<code class="descname">get_sequence_membership</code><span class="sig-paren">(</span><em>data</em>, <em>fuzzySets</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ifts.html#IntervalFTS.get_sequence_membership"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.get_sequence_membership" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.ifts.IntervalFTS.get_upper">
|
||
<code class="descname">get_upper</code><span class="sig-paren">(</span><em>flrg</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ifts.html#IntervalFTS.get_upper"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS.get_upper" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
</dd></dl>
|
||
|
||
</div>
|
||
<div class="section" id="module-pyFTS.models.ismailefendi">
|
||
<span id="pyfts-models-ismailefendi-module"></span><h2>pyFTS.models.ismailefendi module<a class="headerlink" href="#module-pyFTS.models.ismailefendi" title="Permalink to this headline">¶</a></h2>
|
||
<p>First Order Improved Weighted Fuzzy Time Series by Efendi, Ismail and Deris (2013)</p>
|
||
<p>R. Efendi, Z. Ismail, and M. M. Deris, “Improved weight Fuzzy Time Series as used in the exchange rates forecasting of
|
||
US Dollar to Ringgit Malaysia,” Int. J. Comput. Intell. Appl., vol. 12, no. 1, p. 1350005, 2013.</p>
|
||
<dl class="class">
|
||
<dt id="pyFTS.models.ismailefendi.ImprovedWeightedFLRG">
|
||
<em class="property">class </em><code class="descclassname">pyFTS.models.ismailefendi.</code><code class="descname">ImprovedWeightedFLRG</code><span class="sig-paren">(</span><em>LHS</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ismailefendi.html#ImprovedWeightedFLRG"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFLRG" title="Permalink to this definition">¶</a></dt>
|
||
<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>First Order Improved Weighted Fuzzy Logical Relationship Group</p>
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.ismailefendi.ImprovedWeightedFLRG.append_rhs">
|
||
<code class="descname">append_rhs</code><span class="sig-paren">(</span><em>c</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ismailefendi.html#ImprovedWeightedFLRG.append_rhs"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFLRG.append_rhs" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.ismailefendi.ImprovedWeightedFLRG.weights">
|
||
<code class="descname">weights</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ismailefendi.html#ImprovedWeightedFLRG.weights"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFLRG.weights" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
</dd></dl>
|
||
|
||
<dl class="class">
|
||
<dt id="pyFTS.models.ismailefendi.ImprovedWeightedFTS">
|
||
<em class="property">class </em><code class="descclassname">pyFTS.models.ismailefendi.</code><code class="descname">ImprovedWeightedFTS</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ismailefendi.html#ImprovedWeightedFTS"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS" title="Permalink to this definition">¶</a></dt>
|
||
<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>First Order Improved Weighted Fuzzy Time Series</p>
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.forecast">
|
||
<code class="descname">forecast</code><span class="sig-paren">(</span><em>ndata</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ismailefendi.html#ImprovedWeightedFTS.forecast"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.forecast" title="Permalink to this definition">¶</a></dt>
|
||
<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>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.generate_flrg">
|
||
<code class="descname">generate_flrg</code><span class="sig-paren">(</span><em>flrs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ismailefendi.html#ImprovedWeightedFTS.generate_flrg"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.generate_flrg" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.ismailefendi.ImprovedWeightedFTS.train">
|
||
<code class="descname">train</code><span class="sig-paren">(</span><em>ndata</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ismailefendi.html#ImprovedWeightedFTS.train"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.train" title="Permalink to this definition">¶</a></dt>
|
||
<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>
|
||
|
||
</div>
|
||
<div class="section" id="module-pyFTS.models.pwfts">
|
||
<span id="pyfts-models-pwfts-module"></span><h2>pyFTS.models.pwfts module<a class="headerlink" href="#module-pyFTS.models.pwfts" title="Permalink to this headline">¶</a></h2>
|
||
<dl class="class">
|
||
<dt id="pyFTS.models.pwfts.ProbabilisticWeightedFLRG">
|
||
<em class="property">class </em><code class="descclassname">pyFTS.models.pwfts.</code><code class="descname">ProbabilisticWeightedFLRG</code><span class="sig-paren">(</span><em>order</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFLRG"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFLRG" title="Permalink to this definition">¶</a></dt>
|
||
<dd><p>Bases: <a class="reference internal" href="#pyFTS.models.hofts.HighOrderFLRG" title="pyFTS.models.hofts.HighOrderFLRG"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.models.hofts.HighOrderFLRG</span></code></a></p>
|
||
<p>High Order Probabilistic Weighted Fuzzy Logical Relationship Group</p>
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.pwfts.ProbabilisticWeightedFLRG.append_rhs">
|
||
<code class="descname">append_rhs</code><span class="sig-paren">(</span><em>c</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFLRG.append_rhs"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.append_rhs" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.pwfts.ProbabilisticWeightedFLRG.get_lower">
|
||
<code class="descname">get_lower</code><span class="sig-paren">(</span><em>sets</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFLRG.get_lower"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.get_lower" title="Permalink to this definition">¶</a></dt>
|
||
<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>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.pwfts.ProbabilisticWeightedFLRG.get_membership">
|
||
<code class="descname">get_membership</code><span class="sig-paren">(</span><em>data</em>, <em>sets</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFLRG.get_membership"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.get_membership" title="Permalink to this definition">¶</a></dt>
|
||
<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>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.pwfts.ProbabilisticWeightedFLRG.get_midpoint">
|
||
<code class="descname">get_midpoint</code><span class="sig-paren">(</span><em>sets</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFLRG.get_midpoint"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.get_midpoint" title="Permalink to this definition">¶</a></dt>
|
||
<dd><p>Return the expectation of the PWFLRG, the weighted sum</p>
|
||
</dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.pwfts.ProbabilisticWeightedFLRG.get_upper">
|
||
<code class="descname">get_upper</code><span class="sig-paren">(</span><em>sets</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFLRG.get_upper"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.get_upper" title="Permalink to this definition">¶</a></dt>
|
||
<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>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.pwfts.ProbabilisticWeightedFLRG.lhs_conditional_probability">
|
||
<code class="descname">lhs_conditional_probability</code><span class="sig-paren">(</span><em>x</em>, <em>sets</em>, <em>norm</em>, <em>uod</em>, <em>nbins</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFLRG.lhs_conditional_probability"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.lhs_conditional_probability" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.pwfts.ProbabilisticWeightedFLRG.partition_function">
|
||
<code class="descname">partition_function</code><span class="sig-paren">(</span><em>sets</em>, <em>uod</em>, <em>nbins=100</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFLRG.partition_function"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.partition_function" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.pwfts.ProbabilisticWeightedFLRG.rhs_conditional_probability">
|
||
<code class="descname">rhs_conditional_probability</code><span class="sig-paren">(</span><em>x</em>, <em>sets</em>, <em>uod</em>, <em>nbins</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFLRG.rhs_conditional_probability"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.rhs_conditional_probability" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.pwfts.ProbabilisticWeightedFLRG.rhs_unconditional_probability">
|
||
<code class="descname">rhs_unconditional_probability</code><span class="sig-paren">(</span><em>c</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFLRG.rhs_unconditional_probability"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.rhs_unconditional_probability" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
</dd></dl>
|
||
|
||
<dl class="class">
|
||
<dt id="pyFTS.models.pwfts.ProbabilisticWeightedFTS">
|
||
<em class="property">class </em><code class="descclassname">pyFTS.models.pwfts.</code><code class="descname">ProbabilisticWeightedFTS</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS" title="Permalink to this definition">¶</a></dt>
|
||
<dd><p>Bases: <a class="reference internal" href="#pyFTS.models.ifts.IntervalFTS" title="pyFTS.models.ifts.IntervalFTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.models.ifts.IntervalFTS</span></code></a></p>
|
||
<p>High Order Probabilistic Weighted Fuzzy Time Series</p>
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.add_new_PWFLGR">
|
||
<code class="descname">add_new_PWFLGR</code><span class="sig-paren">(</span><em>flrg</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.add_new_PWFLGR"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.add_new_PWFLGR" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.flrg_lhs_conditional_probability">
|
||
<code class="descname">flrg_lhs_conditional_probability</code><span class="sig-paren">(</span><em>x</em>, <em>flrg</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.flrg_lhs_conditional_probability"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.flrg_lhs_conditional_probability" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.flrg_lhs_unconditional_probability">
|
||
<code class="descname">flrg_lhs_unconditional_probability</code><span class="sig-paren">(</span><em>flrg</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.flrg_lhs_unconditional_probability"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.flrg_lhs_unconditional_probability" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.flrg_rhs_conditional_probability">
|
||
<code class="descname">flrg_rhs_conditional_probability</code><span class="sig-paren">(</span><em>x</em>, <em>flrg</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.flrg_rhs_conditional_probability"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.flrg_rhs_conditional_probability" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast">
|
||
<code class="descname">forecast</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.forecast"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast" title="Permalink to this definition">¶</a></dt>
|
||
<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>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast_ahead">
|
||
<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="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.forecast_ahead"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast_ahead" title="Permalink to this definition">¶</a></dt>
|
||
<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>
|
||
<li><strong>steps</strong> – the number of steps ahead to forecast</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>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast_ahead_distribution">
|
||
<code class="descname">forecast_ahead_distribution</code><span class="sig-paren">(</span><em>ndata</em>, <em>steps</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.forecast_ahead_distribution"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.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>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 Probability Distributions</p>
|
||
</td>
|
||
</tr>
|
||
</tbody>
|
||
</table>
|
||
</dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.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="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.forecast_ahead_interval"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.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>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 intervals</p>
|
||
</td>
|
||
</tr>
|
||
</tbody>
|
||
</table>
|
||
</dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast_distribution">
|
||
<code class="descname">forecast_distribution</code><span class="sig-paren">(</span><em>ndata</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.forecast_distribution"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.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.pwfts.ProbabilisticWeightedFTS.forecast_interval">
|
||
<code class="descname">forecast_interval</code><span class="sig-paren">(</span><em>ndata</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.forecast_interval"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.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>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.generate_flrg">
|
||
<code class="descname">generate_flrg</code><span class="sig-paren">(</span><em>data</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.generate_flrg"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.generate_flrg" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.generate_lhs_flrg">
|
||
<code class="descname">generate_lhs_flrg</code><span class="sig-paren">(</span><em>sample</em>, <em>explain=False</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.generate_lhs_flrg"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.generate_lhs_flrg" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.get_lower">
|
||
<code class="descname">get_lower</code><span class="sig-paren">(</span><em>flrg</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.get_lower"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.get_lower" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.get_midpoint">
|
||
<code class="descname">get_midpoint</code><span class="sig-paren">(</span><em>flrg</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.get_midpoint"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.get_midpoint" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.get_upper">
|
||
<code class="descname">get_upper</code><span class="sig-paren">(</span><em>flrg</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.get_upper"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.get_upper" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.interval_heuristic">
|
||
<code class="descname">interval_heuristic</code><span class="sig-paren">(</span><em>sample</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.interval_heuristic"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.interval_heuristic" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.interval_quantile">
|
||
<code class="descname">interval_quantile</code><span class="sig-paren">(</span><em>ndata</em>, <em>alpha</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.interval_quantile"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.interval_quantile" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.point_expected_value">
|
||
<code class="descname">point_expected_value</code><span class="sig-paren">(</span><em>sample</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.point_expected_value"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.point_expected_value" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.point_heuristic">
|
||
<code class="descname">point_heuristic</code><span class="sig-paren">(</span><em>sample</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.point_heuristic"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.point_heuristic" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.train">
|
||
<code class="descname">train</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.train"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.train" title="Permalink to this definition">¶</a></dt>
|
||
<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>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.pwfts.ProbabilisticWeightedFTS.update_model">
|
||
<code class="descname">update_model</code><span class="sig-paren">(</span><em>data</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.update_model"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.update_model" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
</dd></dl>
|
||
|
||
<dl class="function">
|
||
<dt id="pyFTS.models.pwfts.visualize_distributions">
|
||
<code class="descclassname">pyFTS.models.pwfts.</code><code class="descname">visualize_distributions</code><span class="sig-paren">(</span><em>model</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/pwfts.html#visualize_distributions"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.pwfts.visualize_distributions" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
</div>
|
||
<div class="section" id="module-pyFTS.models.sadaei">
|
||
<span id="pyfts-models-sadaei-module"></span><h2>pyFTS.models.sadaei module<a class="headerlink" href="#module-pyFTS.models.sadaei" title="Permalink to this headline">¶</a></h2>
|
||
<p>First Order Exponentialy Weighted Fuzzy Time Series by Sadaei et al. (2013)</p>
|
||
<p>H. J. Sadaei, R. Enayatifar, A. H. Abdullah, and A. Gani, “Short-term load forecasting using a hybrid model with a
|
||
refined exponentially weighted fuzzy time series and an improved harmony search,” Int. J. Electr. Power Energy Syst., vol. 62, no. from 2005, pp. 118–129, 2014.</p>
|
||
<dl class="class">
|
||
<dt id="pyFTS.models.sadaei.ExponentialyWeightedFLRG">
|
||
<em class="property">class </em><code class="descclassname">pyFTS.models.sadaei.</code><code class="descname">ExponentialyWeightedFLRG</code><span class="sig-paren">(</span><em>LHS</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/sadaei.html#ExponentialyWeightedFLRG"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFLRG" title="Permalink to this definition">¶</a></dt>
|
||
<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>First Order Exponentialy Weighted Fuzzy Logical Relationship Group</p>
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.sadaei.ExponentialyWeightedFLRG.append_rhs">
|
||
<code class="descname">append_rhs</code><span class="sig-paren">(</span><em>c</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/sadaei.html#ExponentialyWeightedFLRG.append_rhs"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFLRG.append_rhs" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.sadaei.ExponentialyWeightedFLRG.weights">
|
||
<code class="descname">weights</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/sadaei.html#ExponentialyWeightedFLRG.weights"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFLRG.weights" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
</dd></dl>
|
||
|
||
<dl class="class">
|
||
<dt id="pyFTS.models.sadaei.ExponentialyWeightedFTS">
|
||
<em class="property">class </em><code class="descclassname">pyFTS.models.sadaei.</code><code class="descname">ExponentialyWeightedFTS</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/sadaei.html#ExponentialyWeightedFTS"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS" title="Permalink to this definition">¶</a></dt>
|
||
<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>First Order Exponentialy Weighted Fuzzy Time Series</p>
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.sadaei.ExponentialyWeightedFTS.forecast">
|
||
<code class="descname">forecast</code><span class="sig-paren">(</span><em>ndata</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/sadaei.html#ExponentialyWeightedFTS.forecast"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.forecast" title="Permalink to this definition">¶</a></dt>
|
||
<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>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.sadaei.ExponentialyWeightedFTS.generate_flrg">
|
||
<code class="descname">generate_flrg</code><span class="sig-paren">(</span><em>flrs</em>, <em>c</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/sadaei.html#ExponentialyWeightedFTS.generate_flrg"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.generate_flrg" title="Permalink to this definition">¶</a></dt>
|
||
<dd></dd></dl>
|
||
|
||
<dl class="method">
|
||
<dt id="pyFTS.models.sadaei.ExponentialyWeightedFTS.train">
|
||
<code class="descname">train</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/sadaei.html#ExponentialyWeightedFTS.train"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.train" title="Permalink to this definition">¶</a></dt>
|
||
<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>
|
||
|
||
</div>
|
||
</div>
|
||
|
||
|
||
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|
||
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|
||
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|
||
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