| |
| <!DOCTYPE html> |
| |
| <html> |
| <head> |
| <meta charset="utf-8" /> |
| <title>pyspark.ml.base — PySpark 3.3.1 documentation</title> |
| |
| <link rel="stylesheet" href="../../../_static/css/index.73d71520a4ca3b99cfee5594769eaaae.css"> |
| |
| |
| <link rel="stylesheet" |
| href="../../../_static/vendor/fontawesome/5.13.0/css/all.min.css"> |
| <link rel="preload" as="font" type="font/woff2" crossorigin |
| href="../../../_static/vendor/fontawesome/5.13.0/webfonts/fa-solid-900.woff2"> |
| <link rel="preload" as="font" type="font/woff2" crossorigin |
| href="../../../_static/vendor/fontawesome/5.13.0/webfonts/fa-brands-400.woff2"> |
| |
| |
| |
| <link rel="stylesheet" |
| href="../../../_static/vendor/open-sans_all/1.44.1/index.css"> |
| <link rel="stylesheet" |
| href="../../../_static/vendor/lato_latin-ext/1.44.1/index.css"> |
| |
| |
| <link rel="stylesheet" href="../../../_static/basic.css" type="text/css" /> |
| <link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" /> |
| <link rel="stylesheet" type="text/css" href="../../../_static/css/pyspark.css" /> |
| |
| <link rel="preload" as="script" href="../../../_static/js/index.3da636dd464baa7582d2.js"> |
| |
| <script id="documentation_options" data-url_root="../../../" src="../../../_static/documentation_options.js"></script> |
| <script src="../../../_static/jquery.js"></script> |
| <script src="../../../_static/underscore.js"></script> |
| <script src="../../../_static/doctools.js"></script> |
| <script src="../../../_static/language_data.js"></script> |
| <script src="../../../_static/copybutton.js"></script> |
| <script crossorigin="anonymous" integrity="sha256-Ae2Vz/4ePdIu6ZyI/5ZGsYnb+m0JlOmKPjt6XZ9JJkA=" src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.3.4/require.min.js"></script> |
| <script async="async" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/latest.js?config=TeX-AMS-MML_HTMLorMML"></script> |
| <script type="text/x-mathjax-config">MathJax.Hub.Config({"tex2jax": {"inlineMath": [["$", "$"], ["\\(", "\\)"]], "processEscapes": true, "ignoreClass": "document", "processClass": "math|output_area"}})</script> |
| <link rel="search" title="Search" href="../../../search.html" /> |
| <meta name="viewport" content="width=device-width, initial-scale=1" /> |
| <meta name="docsearch:language" content="en" /> |
| </head> |
| <body data-spy="scroll" data-target="#bd-toc-nav" data-offset="80"> |
| |
| <nav class="navbar navbar-light navbar-expand-lg bg-light fixed-top bd-navbar" id="navbar-main"> |
| <div class="container-xl"> |
| |
| <a class="navbar-brand" href="../../../index.html"> |
| |
| <img src="../../../_static/spark-logo-reverse.png" class="logo" alt="logo" /> |
| |
| </a> |
| <button class="navbar-toggler" type="button" data-toggle="collapse" data-target="#navbar-menu" aria-controls="navbar-menu" aria-expanded="false" aria-label="Toggle navigation"> |
| <span class="navbar-toggler-icon"></span> |
| </button> |
| |
| <div id="navbar-menu" class="col-lg-9 collapse navbar-collapse"> |
| <ul id="navbar-main-elements" class="navbar-nav mr-auto"> |
| |
| |
| <li class="nav-item "> |
| <a class="nav-link" href="../../../getting_started/index.html">Getting Started</a> |
| </li> |
| |
| <li class="nav-item "> |
| <a class="nav-link" href="../../../user_guide/index.html">User Guide</a> |
| </li> |
| |
| <li class="nav-item "> |
| <a class="nav-link" href="../../../reference/index.html">API Reference</a> |
| </li> |
| |
| <li class="nav-item "> |
| <a class="nav-link" href="../../../development/index.html">Development</a> |
| </li> |
| |
| <li class="nav-item "> |
| <a class="nav-link" href="../../../migration_guide/index.html">Migration Guide</a> |
| </li> |
| |
| |
| </ul> |
| |
| |
| |
| |
| <ul class="navbar-nav"> |
| |
| |
| </ul> |
| </div> |
| </div> |
| </nav> |
| |
| |
| <div class="container-xl"> |
| <div class="row"> |
| |
| <div class="col-12 col-md-3 bd-sidebar"><form class="bd-search d-flex align-items-center" action="../../../search.html" method="get"> |
| <i class="icon fas fa-search"></i> |
| <input type="search" class="form-control" name="q" id="search-input" placeholder="Search the docs ..." aria-label="Search the docs ..." autocomplete="off" > |
| </form> |
| <nav class="bd-links" id="bd-docs-nav" aria-label="Main navigation"> |
| |
| <div class="bd-toc-item active"> |
| |
| |
| <ul class="nav bd-sidenav"> |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| </ul> |
| |
| </nav> |
| </div> |
| |
| |
| |
| <div class="d-none d-xl-block col-xl-2 bd-toc"> |
| |
| |
| <nav id="bd-toc-nav"> |
| <ul class="nav section-nav flex-column"> |
| |
| </ul> |
| </nav> |
| |
| |
| |
| </div> |
| |
| |
| |
| <main class="col-12 col-md-9 col-xl-7 py-md-5 pl-md-5 pr-md-4 bd-content" role="main"> |
| |
| <div> |
| |
| <h1>Source code for pyspark.ml.base</h1><div class="highlight"><pre> |
| <span></span><span class="c1">#</span> |
| <span class="c1"># Licensed to the Apache Software Foundation (ASF) under one or more</span> |
| <span class="c1"># contributor license agreements. See the NOTICE file distributed with</span> |
| <span class="c1"># this work for additional information regarding copyright ownership.</span> |
| <span class="c1"># The ASF licenses this file to You under the Apache License, Version 2.0</span> |
| <span class="c1"># (the "License"); you may not use this file except in compliance with</span> |
| <span class="c1"># the License. You may obtain a copy of the License at</span> |
| <span class="c1">#</span> |
| <span class="c1"># http://www.apache.org/licenses/LICENSE-2.0</span> |
| <span class="c1">#</span> |
| <span class="c1"># Unless required by applicable law or agreed to in writing, software</span> |
| <span class="c1"># distributed under the License is distributed on an "AS IS" BASIS,</span> |
| <span class="c1"># WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.</span> |
| <span class="c1"># See the License for the specific language governing permissions and</span> |
| <span class="c1"># limitations under the License.</span> |
| <span class="c1">#</span> |
| |
| <span class="kn">from</span> <span class="nn">abc</span> <span class="kn">import</span> <span class="n">ABCMeta</span><span class="p">,</span> <span class="n">abstractmethod</span> |
| |
| <span class="kn">import</span> <span class="nn">copy</span> |
| <span class="kn">import</span> <span class="nn">threading</span> |
| |
| <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="p">(</span> |
| <span class="n">Any</span><span class="p">,</span> |
| <span class="n">Callable</span><span class="p">,</span> |
| <span class="n">Generic</span><span class="p">,</span> |
| <span class="n">Iterator</span><span class="p">,</span> |
| <span class="n">List</span><span class="p">,</span> |
| <span class="n">Optional</span><span class="p">,</span> |
| <span class="n">Sequence</span><span class="p">,</span> |
| <span class="n">Tuple</span><span class="p">,</span> |
| <span class="n">TypeVar</span><span class="p">,</span> |
| <span class="n">Union</span><span class="p">,</span> |
| <span class="n">cast</span><span class="p">,</span> |
| <span class="n">overload</span><span class="p">,</span> |
| <span class="n">TYPE_CHECKING</span><span class="p">,</span> |
| <span class="p">)</span> |
| |
| <span class="kn">from</span> <span class="nn">pyspark</span> <span class="kn">import</span> <span class="n">since</span> |
| <span class="kn">from</span> <span class="nn">pyspark.ml.param</span> <span class="kn">import</span> <span class="n">P</span> |
| <span class="kn">from</span> <span class="nn">pyspark.ml.common</span> <span class="kn">import</span> <span class="n">inherit_doc</span> |
| <span class="kn">from</span> <span class="nn">pyspark.ml.param.shared</span> <span class="kn">import</span> <span class="p">(</span> |
| <span class="n">HasInputCol</span><span class="p">,</span> |
| <span class="n">HasOutputCol</span><span class="p">,</span> |
| <span class="n">HasLabelCol</span><span class="p">,</span> |
| <span class="n">HasFeaturesCol</span><span class="p">,</span> |
| <span class="n">HasPredictionCol</span><span class="p">,</span> |
| <span class="n">Params</span><span class="p">,</span> |
| <span class="p">)</span> |
| <span class="kn">from</span> <span class="nn">pyspark.sql.dataframe</span> <span class="kn">import</span> <span class="n">DataFrame</span> |
| <span class="kn">from</span> <span class="nn">pyspark.sql.functions</span> <span class="kn">import</span> <span class="n">udf</span> |
| <span class="kn">from</span> <span class="nn">pyspark.sql.types</span> <span class="kn">import</span> <span class="n">DataType</span><span class="p">,</span> <span class="n">StructField</span><span class="p">,</span> <span class="n">StructType</span> |
| |
| <span class="k">if</span> <span class="n">TYPE_CHECKING</span><span class="p">:</span> |
| <span class="kn">from</span> <span class="nn">pyspark.ml._typing</span> <span class="kn">import</span> <span class="n">ParamMap</span> |
| |
| <span class="n">T</span> <span class="o">=</span> <span class="n">TypeVar</span><span class="p">(</span><span class="s2">"T"</span><span class="p">)</span> |
| <span class="n">M</span> <span class="o">=</span> <span class="n">TypeVar</span><span class="p">(</span><span class="s2">"M"</span><span class="p">,</span> <span class="n">bound</span><span class="o">=</span><span class="s2">"Transformer"</span><span class="p">)</span> |
| |
| |
| <span class="k">class</span> <span class="nc">_FitMultipleIterator</span><span class="p">(</span><span class="n">Generic</span><span class="p">[</span><span class="n">M</span><span class="p">]):</span> |
| <span class="sd">"""</span> |
| <span class="sd"> Used by default implementation of Estimator.fitMultiple to produce models in a thread safe</span> |
| <span class="sd"> iterator. This class handles the simple case of fitMultiple where each param map should be</span> |
| <span class="sd"> fit independently.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> fitSingleModel : function</span> |
| <span class="sd"> Callable[[int], Transformer] which fits an estimator to a dataset.</span> |
| <span class="sd"> `fitSingleModel` may be called up to `numModels` times, with a unique index each time.</span> |
| <span class="sd"> Each call to `fitSingleModel` with an index should return the Model associated with</span> |
| <span class="sd"> that index.</span> |
| <span class="sd"> numModel : int</span> |
| <span class="sd"> Number of models this iterator should produce.</span> |
| |
| <span class="sd"> Notes</span> |
| <span class="sd"> -----</span> |
| <span class="sd"> See :py:meth:`Estimator.fitMultiple` for more info.</span> |
| <span class="sd"> """</span> |
| |
| <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">fitSingleModel</span><span class="p">:</span> <span class="n">Callable</span><span class="p">[[</span><span class="nb">int</span><span class="p">],</span> <span class="n">M</span><span class="p">],</span> <span class="n">numModels</span><span class="p">:</span> <span class="nb">int</span><span class="p">):</span> |
| <span class="sd">""" """</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">fitSingleModel</span> <span class="o">=</span> <span class="n">fitSingleModel</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">numModel</span> <span class="o">=</span> <span class="n">numModels</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">counter</span> <span class="o">=</span> <span class="mi">0</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">lock</span> <span class="o">=</span> <span class="n">threading</span><span class="o">.</span><span class="n">Lock</span><span class="p">()</span> |
| |
| <span class="k">def</span> <span class="fm">__iter__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></span> <span class="n">Iterator</span><span class="p">[</span><span class="n">Tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="n">M</span><span class="p">]]:</span> |
| <span class="k">return</span> <span class="bp">self</span> |
| |
| <span class="k">def</span> <span class="fm">__next__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></span> <span class="n">Tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="n">M</span><span class="p">]:</span> |
| <span class="k">with</span> <span class="bp">self</span><span class="o">.</span><span class="n">lock</span><span class="p">:</span> |
| <span class="n">index</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">counter</span> |
| <span class="k">if</span> <span class="n">index</span> <span class="o">>=</span> <span class="bp">self</span><span class="o">.</span><span class="n">numModel</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">StopIteration</span><span class="p">(</span><span class="s2">"No models remaining."</span><span class="p">)</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">counter</span> <span class="o">+=</span> <span class="mi">1</span> |
| <span class="k">return</span> <span class="n">index</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">fitSingleModel</span><span class="p">(</span><span class="n">index</span><span class="p">)</span> |
| |
| <span class="k">def</span> <span class="nf">next</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></span> <span class="n">Tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="n">M</span><span class="p">]:</span> |
| <span class="sd">"""For python2 compatibility."""</span> |
| <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="fm">__next__</span><span class="p">()</span> |
| |
| |
| <div class="viewcode-block" id="Estimator"><a class="viewcode-back" href="../../../reference/api/pyspark.ml.Estimator.html#pyspark.ml.Estimator">[docs]</a><span class="nd">@inherit_doc</span> |
| <span class="k">class</span> <span class="nc">Estimator</span><span class="p">(</span><span class="n">Params</span><span class="p">,</span> <span class="n">Generic</span><span class="p">[</span><span class="n">M</span><span class="p">],</span> <span class="n">metaclass</span><span class="o">=</span><span class="n">ABCMeta</span><span class="p">):</span> |
| <span class="sd">"""</span> |
| <span class="sd"> Abstract class for estimators that fit models to data.</span> |
| |
| <span class="sd"> .. versionadded:: 1.3.0</span> |
| <span class="sd"> """</span> |
| |
| <span class="nd">@abstractmethod</span> |
| <span class="k">def</span> <span class="nf">_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">dataset</span><span class="p">:</span> <span class="n">DataFrame</span><span class="p">)</span> <span class="o">-></span> <span class="n">M</span><span class="p">:</span> |
| <span class="sd">"""</span> |
| <span class="sd"> Fits a model to the input dataset. This is called by the default implementation of fit.</span> |
| |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> dataset : :py:class:`pyspark.sql.DataFrame`</span> |
| <span class="sd"> input dataset</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> :class:`Transformer`</span> |
| <span class="sd"> fitted model</span> |
| <span class="sd"> """</span> |
| <span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">()</span> |
| |
| <div class="viewcode-block" id="Estimator.fitMultiple"><a class="viewcode-back" href="../../../reference/api/pyspark.ml.Estimator.html#pyspark.ml.Estimator.fitMultiple">[docs]</a> <span class="k">def</span> <span class="nf">fitMultiple</span><span class="p">(</span> |
| <span class="bp">self</span><span class="p">,</span> <span class="n">dataset</span><span class="p">:</span> <span class="n">DataFrame</span><span class="p">,</span> <span class="n">paramMaps</span><span class="p">:</span> <span class="n">Sequence</span><span class="p">[</span><span class="s2">"ParamMap"</span><span class="p">]</span> |
| <span class="p">)</span> <span class="o">-></span> <span class="n">Iterator</span><span class="p">[</span><span class="n">Tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="n">M</span><span class="p">]]:</span> |
| <span class="sd">"""</span> |
| <span class="sd"> Fits a model to the input dataset for each param map in `paramMaps`.</span> |
| |
| <span class="sd"> .. versionadded:: 2.3.0</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> dataset : :py:class:`pyspark.sql.DataFrame`</span> |
| <span class="sd"> input dataset.</span> |
| <span class="sd"> paramMaps : :py:class:`collections.abc.Sequence`</span> |
| <span class="sd"> A Sequence of param maps.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> :py:class:`_FitMultipleIterator`</span> |
| <span class="sd"> A thread safe iterable which contains one model for each param map. Each</span> |
| <span class="sd"> call to `next(modelIterator)` will return `(index, model)` where model was fit</span> |
| <span class="sd"> using `paramMaps[index]`. `index` values may not be sequential.</span> |
| <span class="sd"> """</span> |
| <span class="n">estimator</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span> |
| |
| <span class="k">def</span> <span class="nf">fitSingleModel</span><span class="p">(</span><span class="n">index</span><span class="p">:</span> <span class="nb">int</span><span class="p">)</span> <span class="o">-></span> <span class="n">M</span><span class="p">:</span> |
| <span class="k">return</span> <span class="n">estimator</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">dataset</span><span class="p">,</span> <span class="n">paramMaps</span><span class="p">[</span><span class="n">index</span><span class="p">])</span> |
| |
| <span class="k">return</span> <span class="n">_FitMultipleIterator</span><span class="p">(</span><span class="n">fitSingleModel</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">paramMaps</span><span class="p">))</span></div> |
| |
| <span class="nd">@overload</span> |
| <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">dataset</span><span class="p">:</span> <span class="n">DataFrame</span><span class="p">,</span> <span class="n">params</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="s2">"ParamMap"</span><span class="p">]</span> <span class="o">=</span> <span class="o">...</span><span class="p">)</span> <span class="o">-></span> <span class="n">M</span><span class="p">:</span> |
| <span class="o">...</span> |
| |
| <span class="nd">@overload</span> |
| <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span> |
| <span class="bp">self</span><span class="p">,</span> <span class="n">dataset</span><span class="p">:</span> <span class="n">DataFrame</span><span class="p">,</span> <span class="n">params</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="n">List</span><span class="p">[</span><span class="s2">"ParamMap"</span><span class="p">],</span> <span class="n">Tuple</span><span class="p">[</span><span class="s2">"ParamMap"</span><span class="p">]]</span> |
| <span class="p">)</span> <span class="o">-></span> <span class="n">List</span><span class="p">[</span><span class="n">M</span><span class="p">]:</span> |
| <span class="o">...</span> |
| |
| <div class="viewcode-block" id="Estimator.fit"><a class="viewcode-back" href="../../../reference/api/pyspark.ml.Estimator.html#pyspark.ml.Estimator.fit">[docs]</a> <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span> |
| <span class="bp">self</span><span class="p">,</span> |
| <span class="n">dataset</span><span class="p">:</span> <span class="n">DataFrame</span><span class="p">,</span> |
| <span class="n">params</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="s2">"ParamMap"</span><span class="p">,</span> <span class="n">List</span><span class="p">[</span><span class="s2">"ParamMap"</span><span class="p">],</span> <span class="n">Tuple</span><span class="p">[</span><span class="s2">"ParamMap"</span><span class="p">]]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> |
| <span class="p">)</span> <span class="o">-></span> <span class="n">Union</span><span class="p">[</span><span class="n">M</span><span class="p">,</span> <span class="n">List</span><span class="p">[</span><span class="n">M</span><span class="p">]]:</span> |
| <span class="sd">"""</span> |
| <span class="sd"> Fits a model to the input dataset with optional parameters.</span> |
| |
| <span class="sd"> .. versionadded:: 1.3.0</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> dataset : :py:class:`pyspark.sql.DataFrame`</span> |
| <span class="sd"> input dataset.</span> |
| <span class="sd"> params : dict or list or tuple, optional</span> |
| <span class="sd"> an optional param map that overrides embedded params. If a list/tuple of</span> |
| <span class="sd"> param maps is given, this calls fit on each param map and returns a list of</span> |
| <span class="sd"> models.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> :py:class:`Transformer` or a list of :py:class:`Transformer`</span> |
| <span class="sd"> fitted model(s)</span> |
| <span class="sd"> """</span> |
| <span class="k">if</span> <span class="n">params</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="n">params</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">()</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">params</span><span class="p">,</span> <span class="p">(</span><span class="nb">list</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">)):</span> |
| <span class="n">models</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="n">Optional</span><span class="p">[</span><span class="n">M</span><span class="p">]]</span> <span class="o">=</span> <span class="p">[</span><span class="kc">None</span><span class="p">]</span> <span class="o">*</span> <span class="nb">len</span><span class="p">(</span><span class="n">params</span><span class="p">)</span> |
| <span class="k">for</span> <span class="n">index</span><span class="p">,</span> <span class="n">model</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">fitMultiple</span><span class="p">(</span><span class="n">dataset</span><span class="p">,</span> <span class="n">params</span><span class="p">):</span> |
| <span class="n">models</span><span class="p">[</span><span class="n">index</span><span class="p">]</span> <span class="o">=</span> <span class="n">model</span> |
| <span class="k">return</span> <span class="n">cast</span><span class="p">(</span><span class="n">List</span><span class="p">[</span><span class="n">M</span><span class="p">],</span> <span class="n">models</span><span class="p">)</span> |
| <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">params</span><span class="p">,</span> <span class="nb">dict</span><span class="p">):</span> |
| <span class="k">if</span> <span class="n">params</span><span class="p">:</span> |
| <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">copy</span><span class="p">(</span><span class="n">params</span><span class="p">)</span><span class="o">.</span><span class="n">_fit</span><span class="p">(</span><span class="n">dataset</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_fit</span><span class="p">(</span><span class="n">dataset</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span> |
| <span class="s2">"Params must be either a param map or a list/tuple of param maps, "</span> |
| <span class="s2">"but got </span><span class="si">%s</span><span class="s2">."</span> <span class="o">%</span> <span class="nb">type</span><span class="p">(</span><span class="n">params</span><span class="p">)</span> |
| <span class="p">)</span></div></div> |
| |
| |
| <div class="viewcode-block" id="Transformer"><a class="viewcode-back" href="../../../reference/api/pyspark.ml.Transformer.html#pyspark.ml.Transformer">[docs]</a><span class="nd">@inherit_doc</span> |
| <span class="k">class</span> <span class="nc">Transformer</span><span class="p">(</span><span class="n">Params</span><span class="p">,</span> <span class="n">metaclass</span><span class="o">=</span><span class="n">ABCMeta</span><span class="p">):</span> |
| <span class="sd">"""</span> |
| <span class="sd"> Abstract class for transformers that transform one dataset into another.</span> |
| |
| <span class="sd"> .. versionadded:: 1.3.0</span> |
| <span class="sd"> """</span> |
| |
| <span class="nd">@abstractmethod</span> |
| <span class="k">def</span> <span class="nf">_transform</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">dataset</span><span class="p">:</span> <span class="n">DataFrame</span><span class="p">)</span> <span class="o">-></span> <span class="n">DataFrame</span><span class="p">:</span> |
| <span class="sd">"""</span> |
| <span class="sd"> Transforms the input dataset.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> dataset : :py:class:`pyspark.sql.DataFrame`</span> |
| <span class="sd"> input dataset.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> :py:class:`pyspark.sql.DataFrame`</span> |
| <span class="sd"> transformed dataset</span> |
| <span class="sd"> """</span> |
| <span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">()</span> |
| |
| <div class="viewcode-block" id="Transformer.transform"><a class="viewcode-back" href="../../../reference/api/pyspark.ml.Transformer.html#pyspark.ml.Transformer.transform">[docs]</a> <span class="k">def</span> <span class="nf">transform</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">dataset</span><span class="p">:</span> <span class="n">DataFrame</span><span class="p">,</span> <span class="n">params</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="s2">"ParamMap"</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-></span> <span class="n">DataFrame</span><span class="p">:</span> |
| <span class="sd">"""</span> |
| <span class="sd"> Transforms the input dataset with optional parameters.</span> |
| |
| <span class="sd"> .. versionadded:: 1.3.0</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> dataset : :py:class:`pyspark.sql.DataFrame`</span> |
| <span class="sd"> input dataset</span> |
| <span class="sd"> params : dict, optional</span> |
| <span class="sd"> an optional param map that overrides embedded params.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> :py:class:`pyspark.sql.DataFrame`</span> |
| <span class="sd"> transformed dataset</span> |
| <span class="sd"> """</span> |
| <span class="k">if</span> <span class="n">params</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="n">params</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">()</span> |
| <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">params</span><span class="p">,</span> <span class="nb">dict</span><span class="p">):</span> |
| <span class="k">if</span> <span class="n">params</span><span class="p">:</span> |
| <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">copy</span><span class="p">(</span><span class="n">params</span><span class="p">)</span><span class="o">.</span><span class="n">_transform</span><span class="p">(</span><span class="n">dataset</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_transform</span><span class="p">(</span><span class="n">dataset</span><span class="p">)</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s2">"Params must be a param map but got </span><span class="si">%s</span><span class="s2">."</span> <span class="o">%</span> <span class="nb">type</span><span class="p">(</span><span class="n">params</span><span class="p">))</span></div></div> |
| |
| |
| <div class="viewcode-block" id="Model"><a class="viewcode-back" href="../../../reference/api/pyspark.ml.Model.html#pyspark.ml.Model">[docs]</a><span class="nd">@inherit_doc</span> |
| <span class="k">class</span> <span class="nc">Model</span><span class="p">(</span><span class="n">Transformer</span><span class="p">,</span> <span class="n">metaclass</span><span class="o">=</span><span class="n">ABCMeta</span><span class="p">):</span> |
| <span class="sd">"""</span> |
| <span class="sd"> Abstract class for models that are fitted by estimators.</span> |
| |
| <span class="sd"> .. versionadded:: 1.4.0</span> |
| <span class="sd"> """</span> |
| |
| <span class="k">pass</span></div> |
| |
| |
| <div class="viewcode-block" id="UnaryTransformer"><a class="viewcode-back" href="../../../reference/api/pyspark.ml.UnaryTransformer.html#pyspark.ml.UnaryTransformer">[docs]</a><span class="nd">@inherit_doc</span> |
| <span class="k">class</span> <span class="nc">UnaryTransformer</span><span class="p">(</span><span class="n">HasInputCol</span><span class="p">,</span> <span class="n">HasOutputCol</span><span class="p">,</span> <span class="n">Transformer</span><span class="p">):</span> |
| <span class="sd">"""</span> |
| <span class="sd"> Abstract class for transformers that take one input column, apply transformation,</span> |
| <span class="sd"> and output the result as a new column.</span> |
| |
| <span class="sd"> .. versionadded:: 2.3.0</span> |
| <span class="sd"> """</span> |
| |
| <div class="viewcode-block" id="UnaryTransformer.setInputCol"><a class="viewcode-back" href="../../../reference/api/pyspark.ml.UnaryTransformer.html#pyspark.ml.UnaryTransformer.setInputCol">[docs]</a> <span class="k">def</span> <span class="nf">setInputCol</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">P</span><span class="p">,</span> <span class="n">value</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-></span> <span class="n">P</span><span class="p">:</span> |
| <span class="sd">"""</span> |
| <span class="sd"> Sets the value of :py:attr:`inputCol`.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_set</span><span class="p">(</span><span class="n">inputCol</span><span class="o">=</span><span class="n">value</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="UnaryTransformer.setOutputCol"><a class="viewcode-back" href="../../../reference/api/pyspark.ml.UnaryTransformer.html#pyspark.ml.UnaryTransformer.setOutputCol">[docs]</a> <span class="k">def</span> <span class="nf">setOutputCol</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">P</span><span class="p">,</span> <span class="n">value</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-></span> <span class="n">P</span><span class="p">:</span> |
| <span class="sd">"""</span> |
| <span class="sd"> Sets the value of :py:attr:`outputCol`.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_set</span><span class="p">(</span><span class="n">outputCol</span><span class="o">=</span><span class="n">value</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="UnaryTransformer.createTransformFunc"><a class="viewcode-back" href="../../../reference/api/pyspark.ml.UnaryTransformer.html#pyspark.ml.UnaryTransformer.createTransformFunc">[docs]</a> <span class="nd">@abstractmethod</span> |
| <span class="k">def</span> <span class="nf">createTransformFunc</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></span> <span class="n">Callable</span><span class="p">[</span><span class="o">...</span><span class="p">,</span> <span class="n">Any</span><span class="p">]:</span> |
| <span class="sd">"""</span> |
| <span class="sd"> Creates the transform function using the given param map. The input param map already takes</span> |
| <span class="sd"> account of the embedded param map. So the param values should be determined</span> |
| <span class="sd"> solely by the input param map.</span> |
| <span class="sd"> """</span> |
| <span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">()</span></div> |
| |
| <div class="viewcode-block" id="UnaryTransformer.outputDataType"><a class="viewcode-back" href="../../../reference/api/pyspark.ml.UnaryTransformer.html#pyspark.ml.UnaryTransformer.outputDataType">[docs]</a> <span class="nd">@abstractmethod</span> |
| <span class="k">def</span> <span class="nf">outputDataType</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></span> <span class="n">DataType</span><span class="p">:</span> |
| <span class="sd">"""</span> |
| <span class="sd"> Returns the data type of the output column.</span> |
| <span class="sd"> """</span> |
| <span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">()</span></div> |
| |
| <div class="viewcode-block" id="UnaryTransformer.validateInputType"><a class="viewcode-back" href="../../../reference/api/pyspark.ml.UnaryTransformer.html#pyspark.ml.UnaryTransformer.validateInputType">[docs]</a> <span class="nd">@abstractmethod</span> |
| <span class="k">def</span> <span class="nf">validateInputType</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">inputType</span><span class="p">:</span> <span class="n">DataType</span><span class="p">)</span> <span class="o">-></span> <span class="kc">None</span><span class="p">:</span> |
| <span class="sd">"""</span> |
| <span class="sd"> Validates the input type. Throw an exception if it is invalid.</span> |
| <span class="sd"> """</span> |
| <span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">()</span></div> |
| |
| <div class="viewcode-block" id="UnaryTransformer.transformSchema"><a class="viewcode-back" href="../../../reference/api/pyspark.ml.UnaryTransformer.html#pyspark.ml.UnaryTransformer.transformSchema">[docs]</a> <span class="k">def</span> <span class="nf">transformSchema</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">schema</span><span class="p">:</span> <span class="n">StructType</span><span class="p">)</span> <span class="o">-></span> <span class="n">StructType</span><span class="p">:</span> |
| <span class="n">inputType</span> <span class="o">=</span> <span class="n">schema</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">getInputCol</span><span class="p">()]</span><span class="o">.</span><span class="n">dataType</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">validateInputType</span><span class="p">(</span><span class="n">inputType</span><span class="p">)</span> |
| <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">getOutputCol</span><span class="p">()</span> <span class="ow">in</span> <span class="n">schema</span><span class="o">.</span><span class="n">names</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">"Output column </span><span class="si">%s</span><span class="s2"> already exists."</span> <span class="o">%</span> <span class="bp">self</span><span class="o">.</span><span class="n">getOutputCol</span><span class="p">())</span> |
| <span class="n">outputFields</span> <span class="o">=</span> <span class="n">copy</span><span class="o">.</span><span class="n">copy</span><span class="p">(</span><span class="n">schema</span><span class="o">.</span><span class="n">fields</span><span class="p">)</span> |
| <span class="n">outputFields</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">StructField</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">getOutputCol</span><span class="p">(),</span> <span class="bp">self</span><span class="o">.</span><span class="n">outputDataType</span><span class="p">(),</span> <span class="n">nullable</span><span class="o">=</span><span class="kc">False</span><span class="p">))</span> |
| <span class="k">return</span> <span class="n">StructType</span><span class="p">(</span><span class="n">outputFields</span><span class="p">)</span></div> |
| |
| <span class="k">def</span> <span class="nf">_transform</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">dataset</span><span class="p">:</span> <span class="n">DataFrame</span><span class="p">)</span> <span class="o">-></span> <span class="n">DataFrame</span><span class="p">:</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">transformSchema</span><span class="p">(</span><span class="n">dataset</span><span class="o">.</span><span class="n">schema</span><span class="p">)</span> |
| <span class="n">transformUDF</span> <span class="o">=</span> <span class="n">udf</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">createTransformFunc</span><span class="p">(),</span> <span class="bp">self</span><span class="o">.</span><span class="n">outputDataType</span><span class="p">())</span> |
| <span class="n">transformedDataset</span> <span class="o">=</span> <span class="n">dataset</span><span class="o">.</span><span class="n">withColumn</span><span class="p">(</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">getOutputCol</span><span class="p">(),</span> <span class="n">transformUDF</span><span class="p">(</span><span class="n">dataset</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">getInputCol</span><span class="p">()])</span> |
| <span class="p">)</span> |
| <span class="k">return</span> <span class="n">transformedDataset</span></div> |
| |
| |
| <span class="nd">@inherit_doc</span> |
| <span class="k">class</span> <span class="nc">_PredictorParams</span><span class="p">(</span><span class="n">HasLabelCol</span><span class="p">,</span> <span class="n">HasFeaturesCol</span><span class="p">,</span> <span class="n">HasPredictionCol</span><span class="p">):</span> |
| <span class="sd">"""</span> |
| <span class="sd"> Params for :py:class:`Predictor` and :py:class:`PredictorModel`.</span> |
| |
| <span class="sd"> .. versionadded:: 3.0.0</span> |
| <span class="sd"> """</span> |
| |
| <span class="k">pass</span> |
| |
| |
| <div class="viewcode-block" id="Predictor"><a class="viewcode-back" href="../../../reference/api/pyspark.ml.Predictor.html#pyspark.ml.Predictor">[docs]</a><span class="nd">@inherit_doc</span> |
| <span class="k">class</span> <span class="nc">Predictor</span><span class="p">(</span><span class="n">Estimator</span><span class="p">[</span><span class="n">M</span><span class="p">],</span> <span class="n">_PredictorParams</span><span class="p">,</span> <span class="n">metaclass</span><span class="o">=</span><span class="n">ABCMeta</span><span class="p">):</span> |
| <span class="sd">"""</span> |
| <span class="sd"> Estimator for prediction tasks (regression and classification).</span> |
| <span class="sd"> """</span> |
| |
| <div class="viewcode-block" id="Predictor.setLabelCol"><a class="viewcode-back" href="../../../reference/api/pyspark.ml.Predictor.html#pyspark.ml.Predictor.setLabelCol">[docs]</a> <span class="nd">@since</span><span class="p">(</span><span class="s2">"3.0.0"</span><span class="p">)</span> |
| <span class="k">def</span> <span class="nf">setLabelCol</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">P</span><span class="p">,</span> <span class="n">value</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-></span> <span class="n">P</span><span class="p">:</span> |
| <span class="sd">"""</span> |
| <span class="sd"> Sets the value of :py:attr:`labelCol`.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_set</span><span class="p">(</span><span class="n">labelCol</span><span class="o">=</span><span class="n">value</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Predictor.setFeaturesCol"><a class="viewcode-back" href="../../../reference/api/pyspark.ml.Predictor.html#pyspark.ml.Predictor.setFeaturesCol">[docs]</a> <span class="nd">@since</span><span class="p">(</span><span class="s2">"3.0.0"</span><span class="p">)</span> |
| <span class="k">def</span> <span class="nf">setFeaturesCol</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">P</span><span class="p">,</span> <span class="n">value</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-></span> <span class="n">P</span><span class="p">:</span> |
| <span class="sd">"""</span> |
| <span class="sd"> Sets the value of :py:attr:`featuresCol`.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_set</span><span class="p">(</span><span class="n">featuresCol</span><span class="o">=</span><span class="n">value</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="Predictor.setPredictionCol"><a class="viewcode-back" href="../../../reference/api/pyspark.ml.Predictor.html#pyspark.ml.Predictor.setPredictionCol">[docs]</a> <span class="nd">@since</span><span class="p">(</span><span class="s2">"3.0.0"</span><span class="p">)</span> |
| <span class="k">def</span> <span class="nf">setPredictionCol</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">P</span><span class="p">,</span> <span class="n">value</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-></span> <span class="n">P</span><span class="p">:</span> |
| <span class="sd">"""</span> |
| <span class="sd"> Sets the value of :py:attr:`predictionCol`.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_set</span><span class="p">(</span><span class="n">predictionCol</span><span class="o">=</span><span class="n">value</span><span class="p">)</span></div></div> |
| |
| |
| <div class="viewcode-block" id="PredictionModel"><a class="viewcode-back" href="../../../reference/api/pyspark.ml.PredictionModel.html#pyspark.ml.PredictionModel">[docs]</a><span class="nd">@inherit_doc</span> |
| <span class="k">class</span> <span class="nc">PredictionModel</span><span class="p">(</span><span class="n">Model</span><span class="p">,</span> <span class="n">_PredictorParams</span><span class="p">,</span> <span class="n">Generic</span><span class="p">[</span><span class="n">T</span><span class="p">],</span> <span class="n">metaclass</span><span class="o">=</span><span class="n">ABCMeta</span><span class="p">):</span> |
| <span class="sd">"""</span> |
| <span class="sd"> Model for prediction tasks (regression and classification).</span> |
| <span class="sd"> """</span> |
| |
| <div class="viewcode-block" id="PredictionModel.setFeaturesCol"><a class="viewcode-back" href="../../../reference/api/pyspark.ml.PredictionModel.html#pyspark.ml.PredictionModel.setFeaturesCol">[docs]</a> <span class="nd">@since</span><span class="p">(</span><span class="s2">"3.0.0"</span><span class="p">)</span> |
| <span class="k">def</span> <span class="nf">setFeaturesCol</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">P</span><span class="p">,</span> <span class="n">value</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-></span> <span class="n">P</span><span class="p">:</span> |
| <span class="sd">"""</span> |
| <span class="sd"> Sets the value of :py:attr:`featuresCol`.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_set</span><span class="p">(</span><span class="n">featuresCol</span><span class="o">=</span><span class="n">value</span><span class="p">)</span></div> |
| |
| <div class="viewcode-block" id="PredictionModel.setPredictionCol"><a class="viewcode-back" href="../../../reference/api/pyspark.ml.PredictionModel.html#pyspark.ml.PredictionModel.setPredictionCol">[docs]</a> <span class="nd">@since</span><span class="p">(</span><span class="s2">"3.0.0"</span><span class="p">)</span> |
| <span class="k">def</span> <span class="nf">setPredictionCol</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">P</span><span class="p">,</span> <span class="n">value</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-></span> <span class="n">P</span><span class="p">:</span> |
| <span class="sd">"""</span> |
| <span class="sd"> Sets the value of :py:attr:`predictionCol`.</span> |
| <span class="sd"> """</span> |
| <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_set</span><span class="p">(</span><span class="n">predictionCol</span><span class="o">=</span><span class="n">value</span><span class="p">)</span></div> |
| |
| <span class="nd">@property</span> <span class="c1"># type: ignore[misc]</span> |
| <span class="nd">@abstractmethod</span> |
| <span class="nd">@since</span><span class="p">(</span><span class="s2">"2.1.0"</span><span class="p">)</span> |
| <span class="k">def</span> <span class="nf">numFeatures</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></span> <span class="nb">int</span><span class="p">:</span> |
| <span class="sd">"""</span> |
| <span class="sd"> Returns the number of features the model was trained on. If unknown, returns -1</span> |
| <span class="sd"> """</span> |
| <span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">()</span> |
| |
| <div class="viewcode-block" id="PredictionModel.predict"><a class="viewcode-back" href="../../../reference/api/pyspark.ml.PredictionModel.html#pyspark.ml.PredictionModel.predict">[docs]</a> <span class="nd">@abstractmethod</span> |
| <span class="nd">@since</span><span class="p">(</span><span class="s2">"3.0.0"</span><span class="p">)</span> |
| <span class="k">def</span> <span class="nf">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">:</span> <span class="n">T</span><span class="p">)</span> <span class="o">-></span> <span class="nb">float</span><span class="p">:</span> |
| <span class="sd">"""</span> |
| <span class="sd"> Predict label for the given features.</span> |
| <span class="sd"> """</span> |
| <span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">()</span></div></div> |
| </pre></div> |
| |
| </div> |
| |
| |
| <div class='prev-next-bottom'> |
| |
| |
| </div> |
| |
| </main> |
| |
| |
| </div> |
| </div> |
| |
| |
| <script src="../../../_static/js/index.3da636dd464baa7582d2.js"></script> |
| |
| |
| <footer class="footer mt-5 mt-md-0"> |
| <div class="container"> |
| <p> |
| © Copyright .<br/> |
| Created using <a href="http://sphinx-doc.org/">Sphinx</a> 3.0.4.<br/> |
| </p> |
| </div> |
| </footer> |
| </body> |
| </html> |
