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<div class="section" id="trainvalidationsplit">
<h1>TrainValidationSplit<a class="headerlink" href="#trainvalidationsplit" title="Permalink to this headline"></a></h1>
<dl class="py class">
<dt id="pyspark.ml.tuning.TrainValidationSplit">
<em class="property">class </em><code class="sig-prename descclassname">pyspark.ml.tuning.</code><code class="sig-name descname">TrainValidationSplit</code><span class="sig-paren">(</span><em class="sig-param"><span class="o">*</span></em>, <em class="sig-param"><span class="n">estimator</span><span class="p">:</span> <span class="n">Optional<span class="p">[</span>pyspark.ml.base.Estimator<span class="p">]</span></span> <span class="o">=</span> <span class="default_value">None</span></em>, <em class="sig-param"><span class="n">estimatorParamMaps</span><span class="p">:</span> <span class="n">Optional<span class="p">[</span>List<span class="p">[</span>ParamMap<span class="p">]</span><span class="p">]</span></span> <span class="o">=</span> <span class="default_value">None</span></em>, <em class="sig-param"><span class="n">evaluator</span><span class="p">:</span> <span class="n">Optional<span class="p">[</span><a class="reference internal" href="pyspark.ml.evaluation.Evaluator.html#pyspark.ml.evaluation.Evaluator" title="pyspark.ml.evaluation.Evaluator">pyspark.ml.evaluation.Evaluator</a><span class="p">]</span></span> <span class="o">=</span> <span class="default_value">None</span></em>, <em class="sig-param"><span class="n">trainRatio</span><span class="p">:</span> <span class="n">float</span> <span class="o">=</span> <span class="default_value">0.75</span></em>, <em class="sig-param"><span class="n">parallelism</span><span class="p">:</span> <span class="n">int</span> <span class="o">=</span> <span class="default_value">1</span></em>, <em class="sig-param"><span class="n">collectSubModels</span><span class="p">:</span> <span class="n">bool</span> <span class="o">=</span> <span class="default_value">False</span></em>, <em class="sig-param"><span class="n">seed</span><span class="p">:</span> <span class="n">Optional<span class="p">[</span>int<span class="p">]</span></span> <span class="o">=</span> <span class="default_value">None</span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyspark/ml/tuning.html#TrainValidationSplit"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit" title="Permalink to this definition"></a></dt>
<dd><p>Validation for hyper-parameter tuning. Randomly splits the input dataset into train and
validation sets, and uses evaluation metric on the validation set to select the best model.
Similar to <a class="reference internal" href="pyspark.ml.tuning.CrossValidator.html#pyspark.ml.tuning.CrossValidator" title="pyspark.ml.tuning.CrossValidator"><code class="xref py py-class docutils literal notranslate"><span class="pre">CrossValidator</span></code></a>, but only splits the set once.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 2.0.0.</span></p>
</div>
<p class="rubric">Examples</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">pyspark.ml.classification</span> <span class="kn">import</span> <span class="n">LogisticRegression</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">pyspark.ml.evaluation</span> <span class="kn">import</span> <span class="n">BinaryClassificationEvaluator</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">pyspark.ml.linalg</span> <span class="kn">import</span> <span class="n">Vectors</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">pyspark.ml.tuning</span> <span class="kn">import</span> <span class="n">TrainValidationSplit</span><span class="p">,</span> <span class="n">ParamGridBuilder</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">pyspark.ml.tuning</span> <span class="kn">import</span> <span class="n">TrainValidationSplitModel</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">tempfile</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">dataset</span> <span class="o">=</span> <span class="n">spark</span><span class="o">.</span><span class="n">createDataFrame</span><span class="p">(</span>
<span class="gp">... </span> <span class="p">[(</span><span class="n">Vectors</span><span class="o">.</span><span class="n">dense</span><span class="p">([</span><span class="mf">0.0</span><span class="p">]),</span> <span class="mf">0.0</span><span class="p">),</span>
<span class="gp">... </span> <span class="p">(</span><span class="n">Vectors</span><span class="o">.</span><span class="n">dense</span><span class="p">([</span><span class="mf">0.4</span><span class="p">]),</span> <span class="mf">1.0</span><span class="p">),</span>
<span class="gp">... </span> <span class="p">(</span><span class="n">Vectors</span><span class="o">.</span><span class="n">dense</span><span class="p">([</span><span class="mf">0.5</span><span class="p">]),</span> <span class="mf">0.0</span><span class="p">),</span>
<span class="gp">... </span> <span class="p">(</span><span class="n">Vectors</span><span class="o">.</span><span class="n">dense</span><span class="p">([</span><span class="mf">0.6</span><span class="p">]),</span> <span class="mf">1.0</span><span class="p">),</span>
<span class="gp">... </span> <span class="p">(</span><span class="n">Vectors</span><span class="o">.</span><span class="n">dense</span><span class="p">([</span><span class="mf">1.0</span><span class="p">]),</span> <span class="mf">1.0</span><span class="p">)]</span> <span class="o">*</span> <span class="mi">10</span><span class="p">,</span>
<span class="gp">... </span> <span class="p">[</span><span class="s2">&quot;features&quot;</span><span class="p">,</span> <span class="s2">&quot;label&quot;</span><span class="p">])</span><span class="o">.</span><span class="n">repartition</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">lr</span> <span class="o">=</span> <span class="n">LogisticRegression</span><span class="p">()</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">grid</span> <span class="o">=</span> <span class="n">ParamGridBuilder</span><span class="p">()</span><span class="o">.</span><span class="n">addGrid</span><span class="p">(</span><span class="n">lr</span><span class="o">.</span><span class="n">maxIter</span><span class="p">,</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">])</span><span class="o">.</span><span class="n">build</span><span class="p">()</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">evaluator</span> <span class="o">=</span> <span class="n">BinaryClassificationEvaluator</span><span class="p">()</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">tvs</span> <span class="o">=</span> <span class="n">TrainValidationSplit</span><span class="p">(</span><span class="n">estimator</span><span class="o">=</span><span class="n">lr</span><span class="p">,</span> <span class="n">estimatorParamMaps</span><span class="o">=</span><span class="n">grid</span><span class="p">,</span> <span class="n">evaluator</span><span class="o">=</span><span class="n">evaluator</span><span class="p">,</span>
<span class="gp">... </span> <span class="n">parallelism</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="mi">42</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">tvsModel</span> <span class="o">=</span> <span class="n">tvs</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="gp">&gt;&gt;&gt; </span><span class="n">tvsModel</span><span class="o">.</span><span class="n">getTrainRatio</span><span class="p">()</span>
<span class="go">0.75</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">tvsModel</span><span class="o">.</span><span class="n">validationMetrics</span>
<span class="go">[0.5, ...</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">path</span> <span class="o">=</span> <span class="n">tempfile</span><span class="o">.</span><span class="n">mkdtemp</span><span class="p">()</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">model_path</span> <span class="o">=</span> <span class="n">path</span> <span class="o">+</span> <span class="s2">&quot;/model&quot;</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">tvsModel</span><span class="o">.</span><span class="n">write</span><span class="p">()</span><span class="o">.</span><span class="n">save</span><span class="p">(</span><span class="n">model_path</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">tvsModelRead</span> <span class="o">=</span> <span class="n">TrainValidationSplitModel</span><span class="o">.</span><span class="n">read</span><span class="p">()</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">model_path</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">tvsModelRead</span><span class="o">.</span><span class="n">validationMetrics</span>
<span class="go">[0.5, ...</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">evaluator</span><span class="o">.</span><span class="n">evaluate</span><span class="p">(</span><span class="n">tvsModel</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="go">0.833...</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">evaluator</span><span class="o">.</span><span class="n">evaluate</span><span class="p">(</span><span class="n">tvsModelRead</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="go">0.833...</span>
</pre></div>
</div>
<p class="rubric">Methods</p>
<table class="longtable table autosummary">
<colgroup>
<col style="width: 10%" />
<col style="width: 90%" />
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.clear" title="pyspark.ml.tuning.TrainValidationSplit.clear"><code class="xref py py-obj docutils literal notranslate"><span class="pre">clear</span></code></a>(param)</p></td>
<td><p>Clears a param from the param map if it has been explicitly set.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.copy" title="pyspark.ml.tuning.TrainValidationSplit.copy"><code class="xref py py-obj docutils literal notranslate"><span class="pre">copy</span></code></a>([extra])</p></td>
<td><p>Creates a copy of this instance with a randomly generated uid and some extra params.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.explainParam" title="pyspark.ml.tuning.TrainValidationSplit.explainParam"><code class="xref py py-obj docutils literal notranslate"><span class="pre">explainParam</span></code></a>(param)</p></td>
<td><p>Explains a single param and returns its name, doc, and optional default value and user-supplied value in a string.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.explainParams" title="pyspark.ml.tuning.TrainValidationSplit.explainParams"><code class="xref py py-obj docutils literal notranslate"><span class="pre">explainParams</span></code></a>()</p></td>
<td><p>Returns the documentation of all params with their optionally default values and user-supplied values.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.extractParamMap" title="pyspark.ml.tuning.TrainValidationSplit.extractParamMap"><code class="xref py py-obj docutils literal notranslate"><span class="pre">extractParamMap</span></code></a>([extra])</p></td>
<td><p>Extracts the embedded default param values and user-supplied values, and then merges them with extra values from input into a flat param map, where the latter value is used if there exist conflicts, i.e., with ordering: default param values &lt; user-supplied values &lt; extra.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.fit" title="pyspark.ml.tuning.TrainValidationSplit.fit"><code class="xref py py-obj docutils literal notranslate"><span class="pre">fit</span></code></a>(dataset[, params])</p></td>
<td><p>Fits a model to the input dataset with optional parameters.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.fitMultiple" title="pyspark.ml.tuning.TrainValidationSplit.fitMultiple"><code class="xref py py-obj docutils literal notranslate"><span class="pre">fitMultiple</span></code></a>(dataset, paramMaps)</p></td>
<td><p>Fits a model to the input dataset for each param map in <cite>paramMaps</cite>.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.getCollectSubModels" title="pyspark.ml.tuning.TrainValidationSplit.getCollectSubModels"><code class="xref py py-obj docutils literal notranslate"><span class="pre">getCollectSubModels</span></code></a>()</p></td>
<td><p>Gets the value of collectSubModels or its default value.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.getEstimator" title="pyspark.ml.tuning.TrainValidationSplit.getEstimator"><code class="xref py py-obj docutils literal notranslate"><span class="pre">getEstimator</span></code></a>()</p></td>
<td><p>Gets the value of estimator or its default value.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.getEstimatorParamMaps" title="pyspark.ml.tuning.TrainValidationSplit.getEstimatorParamMaps"><code class="xref py py-obj docutils literal notranslate"><span class="pre">getEstimatorParamMaps</span></code></a>()</p></td>
<td><p>Gets the value of estimatorParamMaps or its default value.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.getEvaluator" title="pyspark.ml.tuning.TrainValidationSplit.getEvaluator"><code class="xref py py-obj docutils literal notranslate"><span class="pre">getEvaluator</span></code></a>()</p></td>
<td><p>Gets the value of evaluator or its default value.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.getOrDefault" title="pyspark.ml.tuning.TrainValidationSplit.getOrDefault"><code class="xref py py-obj docutils literal notranslate"><span class="pre">getOrDefault</span></code></a>(param)</p></td>
<td><p>Gets the value of a param in the user-supplied param map or its default value.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.getParallelism" title="pyspark.ml.tuning.TrainValidationSplit.getParallelism"><code class="xref py py-obj docutils literal notranslate"><span class="pre">getParallelism</span></code></a>()</p></td>
<td><p>Gets the value of parallelism or its default value.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.getParam" title="pyspark.ml.tuning.TrainValidationSplit.getParam"><code class="xref py py-obj docutils literal notranslate"><span class="pre">getParam</span></code></a>(paramName)</p></td>
<td><p>Gets a param by its name.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.getSeed" title="pyspark.ml.tuning.TrainValidationSplit.getSeed"><code class="xref py py-obj docutils literal notranslate"><span class="pre">getSeed</span></code></a>()</p></td>
<td><p>Gets the value of seed or its default value.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.getTrainRatio" title="pyspark.ml.tuning.TrainValidationSplit.getTrainRatio"><code class="xref py py-obj docutils literal notranslate"><span class="pre">getTrainRatio</span></code></a>()</p></td>
<td><p>Gets the value of trainRatio or its default value.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.hasDefault" title="pyspark.ml.tuning.TrainValidationSplit.hasDefault"><code class="xref py py-obj docutils literal notranslate"><span class="pre">hasDefault</span></code></a>(param)</p></td>
<td><p>Checks whether a param has a default value.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.hasParam" title="pyspark.ml.tuning.TrainValidationSplit.hasParam"><code class="xref py py-obj docutils literal notranslate"><span class="pre">hasParam</span></code></a>(paramName)</p></td>
<td><p>Tests whether this instance contains a param with a given (string) name.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.isDefined" title="pyspark.ml.tuning.TrainValidationSplit.isDefined"><code class="xref py py-obj docutils literal notranslate"><span class="pre">isDefined</span></code></a>(param)</p></td>
<td><p>Checks whether a param is explicitly set by user or has a default value.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.isSet" title="pyspark.ml.tuning.TrainValidationSplit.isSet"><code class="xref py py-obj docutils literal notranslate"><span class="pre">isSet</span></code></a>(param)</p></td>
<td><p>Checks whether a param is explicitly set by user.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.load" title="pyspark.ml.tuning.TrainValidationSplit.load"><code class="xref py py-obj docutils literal notranslate"><span class="pre">load</span></code></a>(path)</p></td>
<td><p>Reads an ML instance from the input path, a shortcut of <cite>read().load(path)</cite>.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.read" title="pyspark.ml.tuning.TrainValidationSplit.read"><code class="xref py py-obj docutils literal notranslate"><span class="pre">read</span></code></a>()</p></td>
<td><p>Returns an MLReader instance for this class.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.save" title="pyspark.ml.tuning.TrainValidationSplit.save"><code class="xref py py-obj docutils literal notranslate"><span class="pre">save</span></code></a>(path)</p></td>
<td><p>Save this ML instance to the given path, a shortcut of ‘write().save(path)’.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.set" title="pyspark.ml.tuning.TrainValidationSplit.set"><code class="xref py py-obj docutils literal notranslate"><span class="pre">set</span></code></a>(param, value)</p></td>
<td><p>Sets a parameter in the embedded param map.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.setCollectSubModels" title="pyspark.ml.tuning.TrainValidationSplit.setCollectSubModels"><code class="xref py py-obj docutils literal notranslate"><span class="pre">setCollectSubModels</span></code></a>(value)</p></td>
<td><p>Sets the value of <a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.collectSubModels" title="pyspark.ml.tuning.TrainValidationSplit.collectSubModels"><code class="xref py py-attr docutils literal notranslate"><span class="pre">collectSubModels</span></code></a>.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.setEstimator" title="pyspark.ml.tuning.TrainValidationSplit.setEstimator"><code class="xref py py-obj docutils literal notranslate"><span class="pre">setEstimator</span></code></a>(value)</p></td>
<td><p>Sets the value of <a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.estimator" title="pyspark.ml.tuning.TrainValidationSplit.estimator"><code class="xref py py-attr docutils literal notranslate"><span class="pre">estimator</span></code></a>.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.setEstimatorParamMaps" title="pyspark.ml.tuning.TrainValidationSplit.setEstimatorParamMaps"><code class="xref py py-obj docutils literal notranslate"><span class="pre">setEstimatorParamMaps</span></code></a>(value)</p></td>
<td><p>Sets the value of <a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.estimatorParamMaps" title="pyspark.ml.tuning.TrainValidationSplit.estimatorParamMaps"><code class="xref py py-attr docutils literal notranslate"><span class="pre">estimatorParamMaps</span></code></a>.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.setEvaluator" title="pyspark.ml.tuning.TrainValidationSplit.setEvaluator"><code class="xref py py-obj docutils literal notranslate"><span class="pre">setEvaluator</span></code></a>(value)</p></td>
<td><p>Sets the value of <a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.evaluator" title="pyspark.ml.tuning.TrainValidationSplit.evaluator"><code class="xref py py-attr docutils literal notranslate"><span class="pre">evaluator</span></code></a>.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.setParallelism" title="pyspark.ml.tuning.TrainValidationSplit.setParallelism"><code class="xref py py-obj docutils literal notranslate"><span class="pre">setParallelism</span></code></a>(value)</p></td>
<td><p>Sets the value of <a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.parallelism" title="pyspark.ml.tuning.TrainValidationSplit.parallelism"><code class="xref py py-attr docutils literal notranslate"><span class="pre">parallelism</span></code></a>.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.setParams" title="pyspark.ml.tuning.TrainValidationSplit.setParams"><code class="xref py py-obj docutils literal notranslate"><span class="pre">setParams</span></code></a>(*[, estimator, …])</p></td>
<td><p>setParams(self, *, estimator=None, estimatorParamMaps=None, evaluator=None, trainRatio=0.75, parallelism=1, collectSubModels=False, seed=None): Sets params for the train validation split.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.setSeed" title="pyspark.ml.tuning.TrainValidationSplit.setSeed"><code class="xref py py-obj docutils literal notranslate"><span class="pre">setSeed</span></code></a>(value)</p></td>
<td><p>Sets the value of <a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.seed" title="pyspark.ml.tuning.TrainValidationSplit.seed"><code class="xref py py-attr docutils literal notranslate"><span class="pre">seed</span></code></a>.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.setTrainRatio" title="pyspark.ml.tuning.TrainValidationSplit.setTrainRatio"><code class="xref py py-obj docutils literal notranslate"><span class="pre">setTrainRatio</span></code></a>(value)</p></td>
<td><p>Sets the value of <a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.trainRatio" title="pyspark.ml.tuning.TrainValidationSplit.trainRatio"><code class="xref py py-attr docutils literal notranslate"><span class="pre">trainRatio</span></code></a>.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.write" title="pyspark.ml.tuning.TrainValidationSplit.write"><code class="xref py py-obj docutils literal notranslate"><span class="pre">write</span></code></a>()</p></td>
<td><p>Returns an MLWriter instance for this ML instance.</p></td>
</tr>
</tbody>
</table>
<p class="rubric">Attributes</p>
<table class="longtable table autosummary">
<colgroup>
<col style="width: 10%" />
<col style="width: 90%" />
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.collectSubModels" title="pyspark.ml.tuning.TrainValidationSplit.collectSubModels"><code class="xref py py-obj docutils literal notranslate"><span class="pre">collectSubModels</span></code></a></p></td>
<td><p></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.estimator" title="pyspark.ml.tuning.TrainValidationSplit.estimator"><code class="xref py py-obj docutils literal notranslate"><span class="pre">estimator</span></code></a></p></td>
<td><p></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.estimatorParamMaps" title="pyspark.ml.tuning.TrainValidationSplit.estimatorParamMaps"><code class="xref py py-obj docutils literal notranslate"><span class="pre">estimatorParamMaps</span></code></a></p></td>
<td><p></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.evaluator" title="pyspark.ml.tuning.TrainValidationSplit.evaluator"><code class="xref py py-obj docutils literal notranslate"><span class="pre">evaluator</span></code></a></p></td>
<td><p></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.parallelism" title="pyspark.ml.tuning.TrainValidationSplit.parallelism"><code class="xref py py-obj docutils literal notranslate"><span class="pre">parallelism</span></code></a></p></td>
<td><p></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.params" title="pyspark.ml.tuning.TrainValidationSplit.params"><code class="xref py py-obj docutils literal notranslate"><span class="pre">params</span></code></a></p></td>
<td><p>Returns all params ordered by name.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.seed" title="pyspark.ml.tuning.TrainValidationSplit.seed"><code class="xref py py-obj docutils literal notranslate"><span class="pre">seed</span></code></a></p></td>
<td><p></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.trainRatio" title="pyspark.ml.tuning.TrainValidationSplit.trainRatio"><code class="xref py py-obj docutils literal notranslate"><span class="pre">trainRatio</span></code></a></p></td>
<td><p></p></td>
</tr>
</tbody>
</table>
<p class="rubric">Methods Documentation</p>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.clear">
<code class="sig-name descname">clear</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">param</span><span class="p">:</span> <span class="n"><a class="reference internal" href="pyspark.ml.param.Param.html#pyspark.ml.param.Param" title="pyspark.ml.param.Param">pyspark.ml.param.Param</a></span></em><span class="sig-paren">)</span> &#x2192; None<a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.clear" title="Permalink to this definition"></a></dt>
<dd><p>Clears a param from the param map if it has been explicitly set.</p>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.copy">
<code class="sig-name descname">copy</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">extra</span><span class="p">:</span> <span class="n">Optional<span class="p">[</span>ParamMap<span class="p">]</span></span> <span class="o">=</span> <span class="default_value">None</span></em><span class="sig-paren">)</span> &#x2192; TrainValidationSplit<a class="reference internal" href="../../_modules/pyspark/ml/tuning.html#TrainValidationSplit.copy"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.copy" title="Permalink to this definition"></a></dt>
<dd><p>Creates a copy of this instance with a randomly generated uid
and some extra params. This copies creates a deep copy of
the embedded paramMap, and copies the embedded and extra parameters over.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 2.0.0.</span></p>
</div>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><dl class="simple">
<dt><strong>extra</strong><span class="classifier">dict, optional</span></dt><dd><p>Extra parameters to copy to the new instance</p>
</dd>
</dl>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><dl class="simple">
<dt><a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit" title="pyspark.ml.tuning.TrainValidationSplit"><code class="xref py py-class docutils literal notranslate"><span class="pre">TrainValidationSplit</span></code></a></dt><dd><p>Copy of this instance</p>
</dd>
</dl>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.explainParam">
<code class="sig-name descname">explainParam</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">param</span><span class="p">:</span> <span class="n">Union<span class="p">[</span>str<span class="p">, </span><a class="reference internal" href="pyspark.ml.param.Param.html#pyspark.ml.param.Param" title="pyspark.ml.param.Param">pyspark.ml.param.Param</a><span class="p">]</span></span></em><span class="sig-paren">)</span> &#x2192; str<a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.explainParam" title="Permalink to this definition"></a></dt>
<dd><p>Explains a single param and returns its name, doc, and optional
default value and user-supplied value in a string.</p>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.explainParams">
<code class="sig-name descname">explainParams</code><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; str<a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.explainParams" title="Permalink to this definition"></a></dt>
<dd><p>Returns the documentation of all params with their optionally
default values and user-supplied values.</p>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.extractParamMap">
<code class="sig-name descname">extractParamMap</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">extra</span><span class="p">:</span> <span class="n">Optional<span class="p">[</span>ParamMap<span class="p">]</span></span> <span class="o">=</span> <span class="default_value">None</span></em><span class="sig-paren">)</span> &#x2192; ParamMap<a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.extractParamMap" title="Permalink to this definition"></a></dt>
<dd><p>Extracts the embedded default param values and user-supplied
values, and then merges them with extra values from input into
a flat param map, where the latter value is used if there exist
conflicts, i.e., with ordering: default param values &lt;
user-supplied values &lt; extra.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><dl class="simple">
<dt><strong>extra</strong><span class="classifier">dict, optional</span></dt><dd><p>extra param values</p>
</dd>
</dl>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><dl class="simple">
<dt>dict</dt><dd><p>merged param map</p>
</dd>
</dl>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.fit">
<code class="sig-name descname">fit</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">dataset</span><span class="p">:</span> <span class="n">pyspark.sql.dataframe.DataFrame</span></em>, <em class="sig-param"><span class="n">params</span><span class="p">:</span> <span class="n">Union[ParamMap, List[ParamMap], Tuple[ParamMap], None]</span> <span class="o">=</span> <span class="default_value">None</span></em><span class="sig-paren">)</span> &#x2192; Union<span class="p">[</span>M<span class="p">, </span>List<span class="p">[</span>M<span class="p">]</span><span class="p">]</span><a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.fit" title="Permalink to this definition"></a></dt>
<dd><p>Fits a model to the input dataset with optional parameters.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 1.3.0.</span></p>
</div>
<dl class="field-list">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><dl>
<dt><strong>dataset</strong><span class="classifier"><a class="reference internal" href="../pyspark.sql/api/pyspark.sql.DataFrame.html#pyspark.sql.DataFrame" title="pyspark.sql.DataFrame"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyspark.sql.DataFrame</span></code></a></span></dt><dd><p>input dataset.</p>
</dd>
<dt><strong>params</strong><span class="classifier">dict or list or tuple, optional</span></dt><dd><p>an optional param map that overrides embedded params. If a list/tuple of
param maps is given, this calls fit on each param map and returns a list of
models.</p>
</dd>
</dl>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><dl class="simple">
<dt><code class="xref py py-class docutils literal notranslate"><span class="pre">Transformer</span></code> or a list of <code class="xref py py-class docutils literal notranslate"><span class="pre">Transformer</span></code></dt><dd><p>fitted model(s)</p>
</dd>
</dl>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.fitMultiple">
<code class="sig-name descname">fitMultiple</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">dataset</span><span class="p">:</span> <span class="n">pyspark.sql.dataframe.DataFrame</span></em>, <em class="sig-param"><span class="n">paramMaps</span><span class="p">:</span> <span class="n">Sequence<span class="p">[</span>ParamMap<span class="p">]</span></span></em><span class="sig-paren">)</span> &#x2192; Iterator<span class="p">[</span>Tuple<span class="p">[</span>int<span class="p">, </span>M<span class="p">]</span><span class="p">]</span><a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.fitMultiple" title="Permalink to this definition"></a></dt>
<dd><p>Fits a model to the input dataset for each param map in <cite>paramMaps</cite>.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 2.3.0.</span></p>
</div>
<dl class="field-list">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><dl>
<dt><strong>dataset</strong><span class="classifier"><a class="reference internal" href="../pyspark.sql/api/pyspark.sql.DataFrame.html#pyspark.sql.DataFrame" title="pyspark.sql.DataFrame"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyspark.sql.DataFrame</span></code></a></span></dt><dd><p>input dataset.</p>
</dd>
<dt><strong>paramMaps</strong><span class="classifier"><code class="xref py py-class docutils literal notranslate"><span class="pre">collections.abc.Sequence</span></code></span></dt><dd><p>A Sequence of param maps.</p>
</dd>
</dl>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><dl class="simple">
<dt><code class="xref py py-class docutils literal notranslate"><span class="pre">_FitMultipleIterator</span></code></dt><dd><p>A thread safe iterable which contains one model for each param map. Each
call to <cite>next(modelIterator)</cite> will return <cite>(index, model)</cite> where model was fit
using <cite>paramMaps[index]</cite>. <cite>index</cite> values may not be sequential.</p>
</dd>
</dl>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.getCollectSubModels">
<code class="sig-name descname">getCollectSubModels</code><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; bool<a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.getCollectSubModels" title="Permalink to this definition"></a></dt>
<dd><p>Gets the value of collectSubModels or its default value.</p>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.getEstimator">
<code class="sig-name descname">getEstimator</code><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; pyspark.ml.base.Estimator<a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.getEstimator" title="Permalink to this definition"></a></dt>
<dd><p>Gets the value of estimator or its default value.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 2.0.0.</span></p>
</div>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.getEstimatorParamMaps">
<code class="sig-name descname">getEstimatorParamMaps</code><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; List<span class="p">[</span>ParamMap<span class="p">]</span><a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.getEstimatorParamMaps" title="Permalink to this definition"></a></dt>
<dd><p>Gets the value of estimatorParamMaps or its default value.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 2.0.0.</span></p>
</div>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.getEvaluator">
<code class="sig-name descname">getEvaluator</code><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; <a class="reference internal" href="pyspark.ml.evaluation.Evaluator.html#pyspark.ml.evaluation.Evaluator" title="pyspark.ml.evaluation.Evaluator">pyspark.ml.evaluation.Evaluator</a><a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.getEvaluator" title="Permalink to this definition"></a></dt>
<dd><p>Gets the value of evaluator or its default value.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 2.0.0.</span></p>
</div>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.getOrDefault">
<code class="sig-name descname">getOrDefault</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">param</span><span class="p">:</span> <span class="n">Union<span class="p">[</span>str<span class="p">, </span><a class="reference internal" href="pyspark.ml.param.Param.html#pyspark.ml.param.Param" title="pyspark.ml.param.Param">pyspark.ml.param.Param</a><span class="p">[</span>T<span class="p">]</span><span class="p">]</span></span></em><span class="sig-paren">)</span> &#x2192; Union<span class="p">[</span>Any<span class="p">, </span>T<span class="p">]</span><a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.getOrDefault" title="Permalink to this definition"></a></dt>
<dd><p>Gets the value of a param in the user-supplied param map or its
default value. Raises an error if neither is set.</p>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.getParallelism">
<code class="sig-name descname">getParallelism</code><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; int<a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.getParallelism" title="Permalink to this definition"></a></dt>
<dd><p>Gets the value of parallelism or its default value.</p>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.getParam">
<code class="sig-name descname">getParam</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">paramName</span><span class="p">:</span> <span class="n">str</span></em><span class="sig-paren">)</span> &#x2192; <a class="reference internal" href="pyspark.ml.param.Param.html#pyspark.ml.param.Param" title="pyspark.ml.param.Param">pyspark.ml.param.Param</a><a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.getParam" title="Permalink to this definition"></a></dt>
<dd><p>Gets a param by its name.</p>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.getSeed">
<code class="sig-name descname">getSeed</code><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; int<a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.getSeed" title="Permalink to this definition"></a></dt>
<dd><p>Gets the value of seed or its default value.</p>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.getTrainRatio">
<code class="sig-name descname">getTrainRatio</code><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; float<a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.getTrainRatio" title="Permalink to this definition"></a></dt>
<dd><p>Gets the value of trainRatio or its default value.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 2.0.0.</span></p>
</div>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.hasDefault">
<code class="sig-name descname">hasDefault</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">param</span><span class="p">:</span> <span class="n">Union<span class="p">[</span>str<span class="p">, </span><a class="reference internal" href="pyspark.ml.param.Param.html#pyspark.ml.param.Param" title="pyspark.ml.param.Param">pyspark.ml.param.Param</a><span class="p">[</span>Any<span class="p">]</span><span class="p">]</span></span></em><span class="sig-paren">)</span> &#x2192; bool<a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.hasDefault" title="Permalink to this definition"></a></dt>
<dd><p>Checks whether a param has a default value.</p>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.hasParam">
<code class="sig-name descname">hasParam</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">paramName</span><span class="p">:</span> <span class="n">str</span></em><span class="sig-paren">)</span> &#x2192; bool<a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.hasParam" title="Permalink to this definition"></a></dt>
<dd><p>Tests whether this instance contains a param with a given
(string) name.</p>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.isDefined">
<code class="sig-name descname">isDefined</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">param</span><span class="p">:</span> <span class="n">Union<span class="p">[</span>str<span class="p">, </span><a class="reference internal" href="pyspark.ml.param.Param.html#pyspark.ml.param.Param" title="pyspark.ml.param.Param">pyspark.ml.param.Param</a><span class="p">[</span>Any<span class="p">]</span><span class="p">]</span></span></em><span class="sig-paren">)</span> &#x2192; bool<a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.isDefined" title="Permalink to this definition"></a></dt>
<dd><p>Checks whether a param is explicitly set by user or has
a default value.</p>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.isSet">
<code class="sig-name descname">isSet</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">param</span><span class="p">:</span> <span class="n">Union<span class="p">[</span>str<span class="p">, </span><a class="reference internal" href="pyspark.ml.param.Param.html#pyspark.ml.param.Param" title="pyspark.ml.param.Param">pyspark.ml.param.Param</a><span class="p">[</span>Any<span class="p">]</span><span class="p">]</span></span></em><span class="sig-paren">)</span> &#x2192; bool<a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.isSet" title="Permalink to this definition"></a></dt>
<dd><p>Checks whether a param is explicitly set by user.</p>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.load">
<em class="property">classmethod </em><code class="sig-name descname">load</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">path</span><span class="p">:</span> <span class="n">str</span></em><span class="sig-paren">)</span> &#x2192; RL<a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.load" title="Permalink to this definition"></a></dt>
<dd><p>Reads an ML instance from the input path, a shortcut of <cite>read().load(path)</cite>.</p>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.read">
<em class="property">classmethod </em><code class="sig-name descname">read</code><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; pyspark.ml.tuning.TrainValidationSplitReader<a class="reference internal" href="../../_modules/pyspark/ml/tuning.html#TrainValidationSplit.read"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.read" title="Permalink to this definition"></a></dt>
<dd><p>Returns an MLReader instance for this class.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 2.3.0.</span></p>
</div>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.save">
<code class="sig-name descname">save</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">path</span><span class="p">:</span> <span class="n">str</span></em><span class="sig-paren">)</span> &#x2192; None<a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.save" title="Permalink to this definition"></a></dt>
<dd><p>Save this ML instance to the given path, a shortcut of ‘write().save(path)’.</p>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.set">
<code class="sig-name descname">set</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">param</span><span class="p">:</span> <span class="n"><a class="reference internal" href="pyspark.ml.param.Param.html#pyspark.ml.param.Param" title="pyspark.ml.param.Param">pyspark.ml.param.Param</a></span></em>, <em class="sig-param"><span class="n">value</span><span class="p">:</span> <span class="n">Any</span></em><span class="sig-paren">)</span> &#x2192; None<a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.set" title="Permalink to this definition"></a></dt>
<dd><p>Sets a parameter in the embedded param map.</p>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.setCollectSubModels">
<code class="sig-name descname">setCollectSubModels</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">value</span><span class="p">:</span> <span class="n">bool</span></em><span class="sig-paren">)</span> &#x2192; <a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit" title="pyspark.ml.tuning.TrainValidationSplit">pyspark.ml.tuning.TrainValidationSplit</a><a class="reference internal" href="../../_modules/pyspark/ml/tuning.html#TrainValidationSplit.setCollectSubModels"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.setCollectSubModels" title="Permalink to this definition"></a></dt>
<dd><p>Sets the value of <a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.collectSubModels" title="pyspark.ml.tuning.TrainValidationSplit.collectSubModels"><code class="xref py py-attr docutils literal notranslate"><span class="pre">collectSubModels</span></code></a>.</p>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.setEstimator">
<code class="sig-name descname">setEstimator</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">value</span><span class="p">:</span> <span class="n">pyspark.ml.base.Estimator</span></em><span class="sig-paren">)</span> &#x2192; <a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit" title="pyspark.ml.tuning.TrainValidationSplit">pyspark.ml.tuning.TrainValidationSplit</a><a class="reference internal" href="../../_modules/pyspark/ml/tuning.html#TrainValidationSplit.setEstimator"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.setEstimator" title="Permalink to this definition"></a></dt>
<dd><p>Sets the value of <a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.estimator" title="pyspark.ml.tuning.TrainValidationSplit.estimator"><code class="xref py py-attr docutils literal notranslate"><span class="pre">estimator</span></code></a>.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 2.0.0.</span></p>
</div>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.setEstimatorParamMaps">
<code class="sig-name descname">setEstimatorParamMaps</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">value</span><span class="p">:</span> <span class="n">List<span class="p">[</span>ParamMap<span class="p">]</span></span></em><span class="sig-paren">)</span> &#x2192; TrainValidationSplit<a class="reference internal" href="../../_modules/pyspark/ml/tuning.html#TrainValidationSplit.setEstimatorParamMaps"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.setEstimatorParamMaps" title="Permalink to this definition"></a></dt>
<dd><p>Sets the value of <a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.estimatorParamMaps" title="pyspark.ml.tuning.TrainValidationSplit.estimatorParamMaps"><code class="xref py py-attr docutils literal notranslate"><span class="pre">estimatorParamMaps</span></code></a>.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 2.0.0.</span></p>
</div>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.setEvaluator">
<code class="sig-name descname">setEvaluator</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">value</span><span class="p">:</span> <span class="n"><a class="reference internal" href="pyspark.ml.evaluation.Evaluator.html#pyspark.ml.evaluation.Evaluator" title="pyspark.ml.evaluation.Evaluator">pyspark.ml.evaluation.Evaluator</a></span></em><span class="sig-paren">)</span> &#x2192; <a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit" title="pyspark.ml.tuning.TrainValidationSplit">pyspark.ml.tuning.TrainValidationSplit</a><a class="reference internal" href="../../_modules/pyspark/ml/tuning.html#TrainValidationSplit.setEvaluator"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.setEvaluator" title="Permalink to this definition"></a></dt>
<dd><p>Sets the value of <a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.evaluator" title="pyspark.ml.tuning.TrainValidationSplit.evaluator"><code class="xref py py-attr docutils literal notranslate"><span class="pre">evaluator</span></code></a>.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 2.0.0.</span></p>
</div>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.setParallelism">
<code class="sig-name descname">setParallelism</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">value</span><span class="p">:</span> <span class="n">int</span></em><span class="sig-paren">)</span> &#x2192; <a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit" title="pyspark.ml.tuning.TrainValidationSplit">pyspark.ml.tuning.TrainValidationSplit</a><a class="reference internal" href="../../_modules/pyspark/ml/tuning.html#TrainValidationSplit.setParallelism"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.setParallelism" title="Permalink to this definition"></a></dt>
<dd><p>Sets the value of <a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.parallelism" title="pyspark.ml.tuning.TrainValidationSplit.parallelism"><code class="xref py py-attr docutils literal notranslate"><span class="pre">parallelism</span></code></a>.</p>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.setParams">
<code class="sig-name descname">setParams</code><span class="sig-paren">(</span><em class="sig-param"><span class="o">*</span></em>, <em class="sig-param"><span class="n">estimator</span><span class="p">:</span> <span class="n">Optional<span class="p">[</span>pyspark.ml.base.Estimator<span class="p">]</span></span> <span class="o">=</span> <span class="default_value">None</span></em>, <em class="sig-param"><span class="n">estimatorParamMaps</span><span class="p">:</span> <span class="n">Optional<span class="p">[</span>List<span class="p">[</span>ParamMap<span class="p">]</span><span class="p">]</span></span> <span class="o">=</span> <span class="default_value">None</span></em>, <em class="sig-param"><span class="n">evaluator</span><span class="p">:</span> <span class="n">Optional<span class="p">[</span><a class="reference internal" href="pyspark.ml.evaluation.Evaluator.html#pyspark.ml.evaluation.Evaluator" title="pyspark.ml.evaluation.Evaluator">pyspark.ml.evaluation.Evaluator</a><span class="p">]</span></span> <span class="o">=</span> <span class="default_value">None</span></em>, <em class="sig-param"><span class="n">trainRatio</span><span class="p">:</span> <span class="n">float</span> <span class="o">=</span> <span class="default_value">0.75</span></em>, <em class="sig-param"><span class="n">parallelism</span><span class="p">:</span> <span class="n">int</span> <span class="o">=</span> <span class="default_value">1</span></em>, <em class="sig-param"><span class="n">collectSubModels</span><span class="p">:</span> <span class="n">bool</span> <span class="o">=</span> <span class="default_value">False</span></em>, <em class="sig-param"><span class="n">seed</span><span class="p">:</span> <span class="n">Optional<span class="p">[</span>int<span class="p">]</span></span> <span class="o">=</span> <span class="default_value">None</span></em><span class="sig-paren">)</span> &#x2192; TrainValidationSplit<a class="reference internal" href="../../_modules/pyspark/ml/tuning.html#TrainValidationSplit.setParams"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.setParams" title="Permalink to this definition"></a></dt>
<dd><p>setParams(self, *, estimator=None, estimatorParamMaps=None, evaluator=None, trainRatio=0.75, parallelism=1, collectSubModels=False, seed=None):
Sets params for the train validation split.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 2.0.0.</span></p>
</div>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.setSeed">
<code class="sig-name descname">setSeed</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">value</span><span class="p">:</span> <span class="n">int</span></em><span class="sig-paren">)</span> &#x2192; <a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit" title="pyspark.ml.tuning.TrainValidationSplit">pyspark.ml.tuning.TrainValidationSplit</a><a class="reference internal" href="../../_modules/pyspark/ml/tuning.html#TrainValidationSplit.setSeed"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.setSeed" title="Permalink to this definition"></a></dt>
<dd><p>Sets the value of <a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.seed" title="pyspark.ml.tuning.TrainValidationSplit.seed"><code class="xref py py-attr docutils literal notranslate"><span class="pre">seed</span></code></a>.</p>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.setTrainRatio">
<code class="sig-name descname">setTrainRatio</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">value</span><span class="p">:</span> <span class="n">float</span></em><span class="sig-paren">)</span> &#x2192; <a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit" title="pyspark.ml.tuning.TrainValidationSplit">pyspark.ml.tuning.TrainValidationSplit</a><a class="reference internal" href="../../_modules/pyspark/ml/tuning.html#TrainValidationSplit.setTrainRatio"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.setTrainRatio" title="Permalink to this definition"></a></dt>
<dd><p>Sets the value of <a class="reference internal" href="#pyspark.ml.tuning.TrainValidationSplit.trainRatio" title="pyspark.ml.tuning.TrainValidationSplit.trainRatio"><code class="xref py py-attr docutils literal notranslate"><span class="pre">trainRatio</span></code></a>.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 2.0.0.</span></p>
</div>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.tuning.TrainValidationSplit.write">
<code class="sig-name descname">write</code><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; <a class="reference internal" href="pyspark.ml.util.MLWriter.html#pyspark.ml.util.MLWriter" title="pyspark.ml.util.MLWriter">pyspark.ml.util.MLWriter</a><a class="reference internal" href="../../_modules/pyspark/ml/tuning.html#TrainValidationSplit.write"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.write" title="Permalink to this definition"></a></dt>
<dd><p>Returns an MLWriter instance for this ML instance.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 2.3.0.</span></p>
</div>
</dd></dl>
<p class="rubric">Attributes Documentation</p>
<dl class="py attribute">
<dt id="pyspark.ml.tuning.TrainValidationSplit.collectSubModels">
<code class="sig-name descname">collectSubModels</code><em class="property"> = Param(parent='undefined', name='collectSubModels', doc='Param for whether to collect a list of sub-models trained during tuning. If set to false, then only the single best sub-model will be available after fitting. If set to true, then all sub-models will be available. Warning: For large models, collecting all sub-models can cause OOMs on the Spark driver.')</em><a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.collectSubModels" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt id="pyspark.ml.tuning.TrainValidationSplit.estimator">
<code class="sig-name descname">estimator</code><em class="property"> = Param(parent='undefined', name='estimator', doc='estimator to be cross-validated')</em><a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.estimator" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt id="pyspark.ml.tuning.TrainValidationSplit.estimatorParamMaps">
<code class="sig-name descname">estimatorParamMaps</code><em class="property"> = Param(parent='undefined', name='estimatorParamMaps', doc='estimator param maps')</em><a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.estimatorParamMaps" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt id="pyspark.ml.tuning.TrainValidationSplit.evaluator">
<code class="sig-name descname">evaluator</code><em class="property"> = Param(parent='undefined', name='evaluator', doc='evaluator used to select hyper-parameters that maximize the validator metric')</em><a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.evaluator" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt id="pyspark.ml.tuning.TrainValidationSplit.parallelism">
<code class="sig-name descname">parallelism</code><em class="property"> = Param(parent='undefined', name='parallelism', doc='the number of threads to use when running parallel algorithms (&gt;= 1).')</em><a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.parallelism" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt id="pyspark.ml.tuning.TrainValidationSplit.params">
<code class="sig-name descname">params</code><a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.params" title="Permalink to this definition"></a></dt>
<dd><p>Returns all params ordered by name. The default implementation
uses <code class="xref py py-func docutils literal notranslate"><span class="pre">dir()</span></code> to get all attributes of type
<code class="xref py py-class docutils literal notranslate"><span class="pre">Param</span></code>.</p>
</dd></dl>
<dl class="py attribute">
<dt id="pyspark.ml.tuning.TrainValidationSplit.seed">
<code class="sig-name descname">seed</code><em class="property"> = Param(parent='undefined', name='seed', doc='random seed.')</em><a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.seed" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt id="pyspark.ml.tuning.TrainValidationSplit.trainRatio">
<code class="sig-name descname">trainRatio</code><em class="property"> = Param(parent='undefined', name='trainRatio', doc='Param for ratio between train and validation data. Must be between 0 and 1.')</em><a class="headerlink" href="#pyspark.ml.tuning.TrainValidationSplit.trainRatio" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
</dd></dl>
</div>
</div>
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