2018-11-01 18:11:20 +04:00
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2019-05-07 23:24:59 +04:00
< title > pyFTS.models.incremental package — pyFTS 1.6 documentation< / title >
2018-11-01 18:11:20 +04:00
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2019-05-07 23:24:59 +04:00
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< li > < a class = "reference internal" href = "#" > pyFTS.models.incremental package< / a > < ul >
< li > < a class = "reference internal" href = "#module-pyFTS.models.incremental" > Module contents< / a > < / li >
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< li > < a class = "reference internal" href = "#module-pyFTS.models.incremental.TimeVariant" > pyFTS.models.incremental.TimeVariant module< / a > < / li >
< li > < a class = "reference internal" href = "#module-pyFTS.models.incremental.IncrementalEnsemble" > pyFTS.models.incremental.IncrementalEnsemble module< / a > < / li >
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< div class = "section" id = "pyfts-models-incremental-package" >
< h1 > pyFTS.models.incremental package< a class = "headerlink" href = "#pyfts-models-incremental-package" title = "Permalink to this headline" > ¶< / a > < / h1 >
< div class = "section" id = "module-pyFTS.models.incremental" >
< span id = "module-contents" > < / span > < h2 > Module contents< a class = "headerlink" href = "#module-pyFTS.models.incremental" title = "Permalink to this headline" > ¶< / a > < / h2 >
< p > FTS methods with incremental/online learning< / p >
< / div >
< div class = "section" id = "submodules" >
< h2 > Submodules< a class = "headerlink" href = "#submodules" title = "Permalink to this headline" > ¶< / a > < / h2 >
< / div >
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< div class = "section" id = "module-pyFTS.models.incremental.TimeVariant" >
< span id = "pyfts-models-incremental-timevariant-module" > < / span > < h2 > pyFTS.models.incremental.TimeVariant module< a class = "headerlink" href = "#module-pyFTS.models.incremental.TimeVariant" title = "Permalink to this headline" > ¶< / a > < / h2 >
< p > Meta model that wraps another FTS method and continously retrain it using a data window with the most recent data< / p >
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< dl class = "class" >
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< dt id = "pyFTS.models.incremental.TimeVariant.Retrainer" >
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< em class = "property" > class < / em > < code class = "descclassname" > pyFTS.models.incremental.TimeVariant.< / code > < code class = "descname" > Retrainer< / code > < span class = "sig-paren" > (< / span > < em > **kwargs< / em > < span class = "sig-paren" > )< / span > < a class = "headerlink" href = "#pyFTS.models.incremental.TimeVariant.Retrainer" title = "Permalink to this definition" > ¶< / a > < / dt >
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< dd > < p > Bases: < a class = "reference internal" href = "pyFTS.common.html#pyFTS.common.fts.FTS" title = "pyFTS.common.fts.FTS" > < code class = "xref py py-class docutils literal notranslate" > < span class = "pre" > pyFTS.common.fts.FTS< / span > < / code > < / a > < / p >
< p > Meta model for incremental/online learning< / p >
< dl class = "method" >
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< dt id = "pyFTS.models.incremental.TimeVariant.Retrainer.forecast" >
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< code class = "descname" > forecast< / code > < span class = "sig-paren" > (< / span > < em > data< / em > , < em > **kwargs< / em > < span class = "sig-paren" > )< / span > < a class = "headerlink" href = "#pyFTS.models.incremental.TimeVariant.Retrainer.forecast" title = "Permalink to this definition" > ¶< / a > < / dt >
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< 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 > – < / li >
< li > < strong > kwargs< / strong > – < / li >
< / ul >
< / td >
< / tr >
< tr class = "field-even field" > < th class = "field-name" > Returns:< / th > < td class = "field-body" > < p class = "first last" > a list with the forecasted values< / p >
< / td >
< / tr >
< / tbody >
< / table >
< / dd > < / dl >
< dl class = "method" >
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< dt id = "pyFTS.models.incremental.TimeVariant.Retrainer.train" >
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< code class = "descname" > train< / code > < span class = "sig-paren" > (< / span > < em > data< / em > , < em > **kwargs< / em > < span class = "sig-paren" > )< / span > < a class = "headerlink" href = "#pyFTS.models.incremental.TimeVariant.Retrainer.train" title = "Permalink to this definition" > ¶< / a > < / dt >
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< 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 > – < / li >
< li > < strong > kwargs< / strong > – < / li >
< / ul >
< / td >
< / tr >
< / tbody >
< / table >
< / dd > < / dl >
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< / dd > < / dl >
< / div >
< div class = "section" id = "module-pyFTS.models.incremental.IncrementalEnsemble" >
< span id = "pyfts-models-incremental-incrementalensemble-module" > < / span > < h2 > pyFTS.models.incremental.IncrementalEnsemble module< a class = "headerlink" href = "#module-pyFTS.models.incremental.IncrementalEnsemble" title = "Permalink to this headline" > ¶< / a > < / h2 >
< p > Time Variant/Incremental Ensemble of FTS methods< / p >
< dl class = "class" >
< dt id = "pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS" >
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< em class = "property" > class < / em > < code class = "descclassname" > pyFTS.models.incremental.IncrementalEnsemble.< / code > < code class = "descname" > IncrementalEnsembleFTS< / code > < span class = "sig-paren" > (< / span > < em > **kwargs< / em > < span class = "sig-paren" > )< / span > < a class = "headerlink" href = "#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS" title = "Permalink to this definition" > ¶< / a > < / dt >
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< dd > < p > Bases: < a class = "reference internal" href = "pyFTS.models.ensemble.html#pyFTS.models.ensemble.ensemble.EnsembleFTS" title = "pyFTS.models.ensemble.ensemble.EnsembleFTS" > < code class = "xref py py-class docutils literal notranslate" > < span class = "pre" > pyFTS.models.ensemble.ensemble.EnsembleFTS< / span > < / code > < / a > < / p >
< p > Time Variant/Incremental Ensemble of FTS methods< / p >
< dl class = "method" >
< dt id = "pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.forecast" >
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< code class = "descname" > forecast< / code > < span class = "sig-paren" > (< / span > < em > data< / em > , < em > **kwargs< / em > < span class = "sig-paren" > )< / span > < a class = "headerlink" href = "#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.forecast" title = "Permalink to this definition" > ¶< / a > < / dt >
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< 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 > – < / li >
< li > < strong > kwargs< / strong > – < / li >
< / ul >
< / td >
< / tr >
< tr class = "field-even field" > < th class = "field-name" > Returns:< / th > < td class = "field-body" > < p class = "first last" > a list with the forecasted values< / p >
< / td >
< / tr >
< / tbody >
< / table >
< / dd > < / dl >
< dl class = "method" >
< dt id = "pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.train" >
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< code class = "descname" > train< / code > < span class = "sig-paren" > (< / span > < em > data< / em > , < em > **kwargs< / em > < span class = "sig-paren" > )< / span > < a class = "headerlink" href = "#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.train" title = "Permalink to this definition" > ¶< / a > < / dt >
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< 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 > – < / li >
< li > < strong > kwargs< / strong > – < / li >
< / ul >
< / td >
< / tr >
< / tbody >
< / table >
< / dd > < / dl >
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< / dd > < / dl >
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