Updating the documentation
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pyFTS.models.multivariate package
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=================================
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Module contents
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---------------
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.. automodule:: pyFTS.models.multivariate
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:members:
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:undoc-members:
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:show-inheritance:
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Submodules
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----------
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@ -43,12 +52,12 @@ pyFTS.models.multivariate.variable module
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:members:
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:undoc-members:
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:show-inheritance:
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pyFTS.models.multivariate.wmvfts module
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--------------------------------------
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Module contents
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---------------
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.. automodule:: pyFTS.models.multivariate
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.. automodule:: pyFTS.models.multivariate.mvfts
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:members:
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:undoc-members:
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:show-inheritance:
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docs/build/html/genindex.html
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docs/build/html/genindex.html
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@ -180,7 +180,7 @@
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</li>
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<li><a href="pyFTS.common.html#pyFTS.common.fts.FTS.append_transformation">append_transformation() (pyFTS.common.fts.FTS method)</a>
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</li>
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<li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.append_variable">append_variable() (pyFTS.models.multivariate.mvfts.MVFTS method)</a>
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<li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.append_variable">append_variable() (pyFTS.models.multivariate.mvfts.MVFTS method)</a>, <a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.append_variable">[1]</a>
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</li>
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<li><a href="pyFTS.common.html#pyFTS.common.tree.FLRGTreeNode.appendChild">appendChild() (pyFTS.common.tree.FLRGTreeNode method)</a>
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</li>
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@ -205,7 +205,7 @@
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<li><a href="pyFTS.common.html#pyFTS.common.fts.FTS.apply_transformations">apply_transformations() (pyFTS.common.fts.FTS method)</a>
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<ul>
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<li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.apply_transformations">(pyFTS.models.multivariate.mvfts.MVFTS method)</a>
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<li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.apply_transformations">(pyFTS.models.multivariate.mvfts.MVFTS method)</a>, <a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.apply_transformations">[1]</a>
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</li>
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<li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.variable.Variable.apply_transformations">(pyFTS.models.multivariate.variable.Variable method)</a>
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</li>
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<li><a href="pyFTS.common.html#pyFTS.common.fts.FTS.clone_parameters">clone_parameters() (pyFTS.common.fts.FTS method)</a>
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<ul>
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<li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.clone_parameters">(pyFTS.models.multivariate.mvfts.MVFTS method)</a>
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<li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.clone_parameters">(pyFTS.models.multivariate.mvfts.MVFTS method)</a>, <a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.clone_parameters">[1]</a>
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</li>
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</ul></li>
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<li><a href="pyFTS.partitioners.html#pyFTS.partitioners.CMeans.CMeansPartitioner">CMeansPartitioner (class in pyFTS.partitioners.CMeans)</a>
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</li>
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<li><a href="pyFTS.models.html#pyFTS.models.ismailefendi.ImprovedWeightedFTS.forecast">(pyFTS.models.ismailefendi.ImprovedWeightedFTS method)</a>
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</li>
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<li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.forecast">(pyFTS.models.multivariate.mvfts.MVFTS method)</a>
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<li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.forecast">(pyFTS.models.multivariate.mvfts.MVFTS method)</a>, <a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.forecast">[1]</a>
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</li>
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<li><a href="pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.cvfts.ConditionalVarianceFTS.forecast">(pyFTS.models.nonstationary.cvfts.ConditionalVarianceFTS method)</a>
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</li>
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<li><a href="pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast_interval">(pyFTS.models.pwfts.ProbabilisticWeightedFTS method)</a>
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</li>
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</ul></li>
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<li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.format_data">format_data() (pyFTS.models.multivariate.mvfts.MVFTS method)</a>
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<li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.format_data">format_data() (pyFTS.models.multivariate.mvfts.MVFTS method)</a>, <a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.format_data">[1]</a>
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</li>
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<li><a href="pyFTS.common.html#pyFTS.common.fts.FTS">FTS (class in pyFTS.common.fts)</a>
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</li>
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<ul>
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<li><a href="pyFTS.models.html#pyFTS.models.ismailefendi.ImprovedWeightedFTS.generate_flrg">(pyFTS.models.ismailefendi.ImprovedWeightedFTS method)</a>
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</li>
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<li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.generate_flrg">(pyFTS.models.multivariate.mvfts.MVFTS method)</a>
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<li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.generate_flrg">(pyFTS.models.multivariate.mvfts.MVFTS method)</a>, <a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.generate_flrg">[1]</a>
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</li>
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<li><a href="pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.cvfts.ConditionalVarianceFTS.generate_flrg">(pyFTS.models.nonstationary.cvfts.ConditionalVarianceFTS method)</a>
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</li>
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</ul></li>
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<li><a href="pyFTS.models.html#pyFTS.models.yu.WeightedFTS.generate_FLRG">generate_FLRG() (pyFTS.models.yu.WeightedFTS method)</a>
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</li>
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<li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.generate_flrs">generate_flrs() (pyFTS.models.multivariate.mvfts.MVFTS method)</a>
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<li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.generate_flrs">generate_flrs() (pyFTS.models.multivariate.mvfts.MVFTS method)</a>, <a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.generate_flrs">[1]</a>
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</li>
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<li><a href="pyFTS.data.html#pyFTS.data.artificial.generate_gaussian_linear">generate_gaussian_linear() (in module pyFTS.data.artificial)</a>
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</li>
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<li><a href="pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFTS.generate_lhs_flrg">(pyFTS.models.pwfts.ProbabilisticWeightedFTS method)</a>
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</li>
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</ul></li>
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<li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.generate_lhs_flrs">generate_lhs_flrs() (pyFTS.models.multivariate.mvfts.MVFTS method)</a>
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<li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.generate_lhs_flrs">generate_lhs_flrs() (pyFTS.models.multivariate.mvfts.MVFTS method)</a>, <a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.generate_lhs_flrs">[1]</a>
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</li>
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<li><a href="pyFTS.common.html#pyFTS.common.FLR.generate_non_recurrent_flrs">generate_non_recurrent_flrs() (in module pyFTS.common.FLR)</a>
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</li>
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</li>
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<li><a href="pyFTS.models.seasonal.html#pyFTS.models.seasonal.msfts.MultiSeasonalFTS">MultiSeasonalFTS (class in pyFTS.models.seasonal.msfts)</a>
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</li>
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<li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS">MVFTS (class in pyFTS.models.multivariate.mvfts)</a>
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<li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS">MVFTS (class in pyFTS.models.multivariate.mvfts)</a>, <a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS">[1]</a>
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</li>
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</ul></td>
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</tr></table>
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</li>
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<li><a href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.flrg">pyFTS.models.multivariate.flrg (module)</a>
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</li>
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<li><a href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.mvfts">pyFTS.models.multivariate.mvfts (module)</a>
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<li><a href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.mvfts">pyFTS.models.multivariate.mvfts (module)</a>, <a href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.mvfts">[1]</a>
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</li>
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<li><a href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.variable">pyFTS.models.multivariate.variable (module)</a>
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</li>
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</li>
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<li><a href="pyFTS.models.html#pyFTS.models.ismailefendi.ImprovedWeightedFTS.train">(pyFTS.models.ismailefendi.ImprovedWeightedFTS method)</a>
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</li>
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<li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.train">(pyFTS.models.multivariate.mvfts.MVFTS method)</a>
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<li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.train">(pyFTS.models.multivariate.mvfts.MVFTS method)</a>, <a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.train">[1]</a>
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</li>
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<li><a href="pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.cvfts.ConditionalVarianceFTS.train">(pyFTS.models.nonstationary.cvfts.ConditionalVarianceFTS method)</a>
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</li>
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</ul>
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</li>
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<li class="toctree-l1"><a class="reference internal" href="pyFTS.models.multivariate.html">pyFTS.models.multivariate package</a><ul>
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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.multivariate.html#submodules">Submodules</a></li>
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<li class="toctree-l2"><a class="reference internal" href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.FLR">pyFTS.models.multivariate.FLR module</a></li>
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<li class="toctree-l2"><a class="reference internal" href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.common">pyFTS.models.multivariate.common module</a></li>
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<li class="toctree-l2"><a class="reference internal" href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.flrg">pyFTS.models.multivariate.flrg module</a></li>
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<li class="toctree-l2"><a class="reference internal" href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.mvfts">pyFTS.models.multivariate.mvfts module</a></li>
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<li class="toctree-l2"><a class="reference internal" href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.variable">pyFTS.models.multivariate.variable module</a></li>
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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.multivariate.html#pyfts-models-multivariate-wmvfts-module">pyFTS.models.multivariate.wmvfts module</a></li>
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</ul>
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</li>
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<li class="toctree-l1"><a class="reference internal" href="pyFTS.models.nonstationary.html">pyFTS.models.nonstationary package</a><ul>
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<h3><a href="index.html">Table Of Contents</a></h3>
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<ul>
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<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>
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<li><a class="reference internal" href="#module-pyFTS.models.multivariate.FLR">pyFTS.models.multivariate.FLR module</a></li>
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<li><a class="reference internal" href="#module-pyFTS.models.multivariate.common">pyFTS.models.multivariate.common module</a></li>
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<li><a class="reference internal" href="#module-pyFTS.models.multivariate.flrg">pyFTS.models.multivariate.flrg module</a></li>
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<li><a class="reference internal" href="#module-pyFTS.models.multivariate.mvfts">pyFTS.models.multivariate.mvfts module</a></li>
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<li><a class="reference internal" href="#module-pyFTS.models.multivariate.variable">pyFTS.models.multivariate.variable module</a></li>
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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="#pyfts-models-multivariate-wmvfts-module">pyFTS.models.multivariate.wmvfts module</a></li>
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</ul>
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</li>
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</ul>
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<div class="section" id="pyfts-models-multivariate-package">
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<h1>pyFTS.models.multivariate package<a class="headerlink" href="#pyfts-models-multivariate-package" title="Permalink to this headline">¶</a></h1>
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<div class="section" id="module-pyFTS.models.multivariate">
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<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-pyFTS.models.multivariate" title="Permalink to this headline">¶</a></h2>
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<p>Multivariate Fuzzy Time Series methods</p>
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</div>
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<div class="section" id="submodules">
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<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this headline">¶</a></h2>
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</div>
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@ -358,9 +363,127 @@ transformations and partitioners.</p>
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</dd></dl>
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</div>
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<div class="section" id="module-pyFTS.models.multivariate">
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<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-pyFTS.models.multivariate" title="Permalink to this headline">¶</a></h2>
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<p>Multivariate Fuzzy Time Series methods</p>
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<div class="section" id="pyfts-models-multivariate-wmvfts-module">
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<h2>pyFTS.models.multivariate.wmvfts module<a class="headerlink" href="#pyfts-models-multivariate-wmvfts-module" title="Permalink to this headline">¶</a></h2>
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<span class="target" id="module-pyFTS.models.multivariate.mvfts"></span><dl class="class">
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<dt>
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<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="reference internal" href="_modules/pyFTS/models/multivariate/mvfts.html#MVFTS"><span class="viewcode-link">[source]</span></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>Multivariate extension of Chen’s ConventionalFTS method</p>
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<dl class="method">
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<dt>
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<code class="descname">append_variable</code><span class="sig-paren">(</span><em>var</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/mvfts.html#MVFTS.append_variable"><span class="viewcode-link">[source]</span></a></dt>
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<dd><p>Append a new endogenous variable to the model</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"><strong>var</strong> – variable object</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"></td>
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</tr>
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</tbody>
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</table>
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</dd></dl>
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<dl class="method">
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<dt>
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<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="reference internal" href="_modules/pyFTS/models/multivariate/mvfts.html#MVFTS.apply_transformations"><span class="viewcode-link">[source]</span></a></dt>
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<dd><p>Apply the data transformations for data preprocessing</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">
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<li><strong>data</strong> – input data</li>
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<li><strong>params</strong> – transformation parameters</li>
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<li><strong>updateUoD</strong> – </li>
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<li><strong>kwargs</strong> – </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">preprocessed data</p>
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</td>
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</tr>
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</tbody>
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</table>
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</dd></dl>
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<dl class="method">
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<dt>
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<code class="descname">clone_parameters</code><span class="sig-paren">(</span><em>model</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/mvfts.html#MVFTS.clone_parameters"><span class="viewcode-link">[source]</span></a></dt>
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<dd><p>Import the parameters values from other model</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"><strong>model</strong> – </td>
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</tr>
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</tbody>
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</table>
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</dd></dl>
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<dl class="method">
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<dt>
|
||||
<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/multivariate/mvfts.html#MVFTS.forecast"><span class="viewcode-link">[source]</span></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>
|
||||
<code class="descname">format_data</code><span class="sig-paren">(</span><em>data</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/mvfts.html#MVFTS.format_data"><span class="viewcode-link">[source]</span></a></dt>
|
||||
<dd></dd></dl>
|
||||
|
||||
<dl class="method">
|
||||
<dt>
|
||||
<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/multivariate/mvfts.html#MVFTS.generate_flrg"><span class="viewcode-link">[source]</span></a></dt>
|
||||
<dd></dd></dl>
|
||||
|
||||
<dl class="method">
|
||||
<dt>
|
||||
<code class="descname">generate_flrs</code><span class="sig-paren">(</span><em>data</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/mvfts.html#MVFTS.generate_flrs"><span class="viewcode-link">[source]</span></a></dt>
|
||||
<dd></dd></dl>
|
||||
|
||||
<dl class="method">
|
||||
<dt>
|
||||
<code class="descname">generate_lhs_flrs</code><span class="sig-paren">(</span><em>data</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/mvfts.html#MVFTS.generate_lhs_flrs"><span class="viewcode-link">[source]</span></a></dt>
|
||||
<dd></dd></dl>
|
||||
|
||||
<dl class="method">
|
||||
<dt>
|
||||
<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/multivariate/mvfts.html#MVFTS.train"><span class="viewcode-link">[source]</span></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>
|
||||
|
||||
|
2
docs/build/html/searchindex.js
vendored
2
docs/build/html/searchindex.js
vendored
File diff suppressed because one or more lines are too long
@ -1,6 +1,15 @@
|
||||
pyFTS.models.multivariate package
|
||||
=================================
|
||||
|
||||
Module contents
|
||||
---------------
|
||||
|
||||
.. automodule:: pyFTS.models.multivariate
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
|
||||
Submodules
|
||||
----------
|
||||
|
||||
@ -43,12 +52,12 @@ pyFTS.models.multivariate.variable module
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.models.multivariate.wmvfts module
|
||||
--------------------------------------
|
||||
|
||||
|
||||
Module contents
|
||||
---------------
|
||||
|
||||
.. automodule:: pyFTS.models.multivariate
|
||||
.. automodule:: pyFTS.models.multivariate.mvfts
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
|
@ -11,7 +11,7 @@ class MVFTS(fts.FTS):
|
||||
Multivariate extension of Chen's ConventionalFTS method
|
||||
"""
|
||||
def __init__(self, **kwargs):
|
||||
super(MVFTS, self).__init__(order=1, **kwargs)
|
||||
super(MVFTS, self).__init__(**kwargs)
|
||||
self.explanatory_variables = []
|
||||
self.target_variable = None
|
||||
self.flrgs = {}
|
||||
|
68
pyFTS/models/multivariate/wmvfts.py
Normal file
68
pyFTS/models/multivariate/wmvfts.py
Normal file
@ -0,0 +1,68 @@
|
||||
from pyFTS.common import fts, FuzzySet, FLR, Membership, tree
|
||||
from pyFTS.partitioners import Grid
|
||||
from pyFTS.models.multivariate import mvfts, FLR as MVFLR, common, flrg as mvflrg
|
||||
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
|
||||
|
||||
class WeightedFLRG(mvflrg.FLRG):
|
||||
"""
|
||||
Weighted Multivariate Fuzzy Logical Rule Group
|
||||
"""
|
||||
|
||||
def __init__(self, **kwargs):
|
||||
super(WeightedFLRG, self).__init__(**kwargs)
|
||||
self.order = kwargs.get('order', 1)
|
||||
self.LHS = kwargs.get('lhs', {})
|
||||
self.RHS = {}
|
||||
self.count = 0.0
|
||||
self.w = None
|
||||
|
||||
def append_rhs(self, fset, **kwargs):
|
||||
if fset not in self.RHS:
|
||||
self.RHS[fset] = 1.0
|
||||
else:
|
||||
self.RHS[fset] += 1.0
|
||||
self.count += 1.0
|
||||
|
||||
def weights(self):
|
||||
if self.w is None:
|
||||
self.w = np.array([self.RHS[c] / self.count for c in self.RHS.keys()])
|
||||
return self.w
|
||||
|
||||
def get_midpoint(self, sets):
|
||||
mp = np.array([sets[c].centroid for c in self.RHS.keys()])
|
||||
return mp.dot(self.weights())
|
||||
|
||||
|
||||
def __str__(self):
|
||||
_str = ""
|
||||
for k in self.RHS.keys():
|
||||
_str += ", " if len(_str) > 0 else ""
|
||||
_str += k + " (" + str(round( self.RHS[k] / self.count, 3)) + ")"
|
||||
|
||||
return self.get_key() + " -> " + _str
|
||||
|
||||
|
||||
class WeightedMVFTS(mvfts.MVFTS):
|
||||
"""
|
||||
Weighted Multivariate FTS
|
||||
"""
|
||||
def __init__(self, **kwargs):
|
||||
super(WeightedMVFTS, self).__init__(order=1, **kwargs)
|
||||
self.explanatory_variables = []
|
||||
self.target_variable = None
|
||||
self.flrgs = {}
|
||||
self.is_multivariate = True
|
||||
self.shortname = "WeightedMVFTS"
|
||||
self.name = "Weighted Multivariate FTS"
|
||||
|
||||
def generate_flrg(self, flrs):
|
||||
for flr in flrs:
|
||||
flrg = WeightedFLRG(lhs=flr.LHS)
|
||||
|
||||
if flrg.get_key() not in self.flrgs:
|
||||
self.flrgs[flrg.get_key()] = flrg
|
||||
|
||||
self.flrgs[flrg.get_key()].append_rhs(flr.RHS)
|
@ -5,7 +5,7 @@ from pyFTS.common import Transformations
|
||||
|
||||
from pyFTS.partitioners import Grid, Util as pUtil
|
||||
from pyFTS.common import Transformations, Util
|
||||
from pyFTS.models.multivariate import common, variable, mvfts
|
||||
from pyFTS.models.multivariate import common, variable, mvfts, wmvfts
|
||||
from pyFTS.models.seasonal import partitioner as seasonal
|
||||
from pyFTS.models.seasonal.common import DateTime
|
||||
|
||||
@ -16,7 +16,7 @@ from pyFTS.models.multivariate import common, variable, mvfts
|
||||
from pyFTS.models.seasonal import partitioner as seasonal
|
||||
from pyFTS.models.seasonal.common import DateTime
|
||||
|
||||
#"""
|
||||
"""
|
||||
from pyFTS.data import Malaysia
|
||||
|
||||
dataset = Malaysia.get_dataframe()
|
||||
@ -71,9 +71,9 @@ for k in [itertools.combinations(var_list, r) for r in range(2,len(var_list))]:
|
||||
model.target_variable = vload
|
||||
model.fit(mv_train)
|
||||
models.append(model)
|
||||
#"""
|
||||
|
||||
"""
|
||||
|
||||
#"""
|
||||
dataset = pd.read_csv('/home/petronio/Downloads/priceHong')
|
||||
dataset['hour'] = dataset.index.values % 24
|
||||
|
||||
@ -92,16 +92,12 @@ vhour = variable.Variable("Hour", data_label="hour", partitioner=seasonal.TimeGr
|
||||
vprice = variable.Variable("Price", data_label="price", partitioner=Grid.GridPartitioner, npart=25,
|
||||
data=train_mv)
|
||||
|
||||
model1 = mvfts.MVFTS()
|
||||
model1 = wmvfts.WeightedMVFTS()
|
||||
model1.shortname += "1"
|
||||
model1.append_variable(vhour)
|
||||
model1.append_variable(vprice)
|
||||
model1.target_variable = vprice
|
||||
model1.fit(train_mv)
|
||||
|
||||
model2 = mvfts.MVFTS()
|
||||
model2.shortname += "2"
|
||||
model2.append_variable(vhour)
|
||||
model2.target_variable = vprice
|
||||
model2.fit(train_mv)
|
||||
"""
|
||||
print(model1)
|
||||
#"""
|
Loading…
Reference in New Issue
Block a user