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<div class="section" id="predictionmodel">
<h1>PredictionModel<a class="headerlink" href="#predictionmodel" title="Permalink to this headline"></a></h1>
<dl class="py class">
<dt id="pyspark.ml.PredictionModel">
<em class="property">class </em><code class="sig-prename descclassname">pyspark.ml.</code><code class="sig-name descname">PredictionModel</code><a class="reference internal" href="../../_modules/pyspark/ml/base.html#PredictionModel"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.ml.PredictionModel" title="Permalink to this definition"></a></dt>
<dd><p>Model for prediction tasks (regression and classification).</p>
<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.PredictionModel.clear" title="pyspark.ml.PredictionModel.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.PredictionModel.copy" title="pyspark.ml.PredictionModel.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 the same uid and some extra params.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.PredictionModel.explainParam" title="pyspark.ml.PredictionModel.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.PredictionModel.explainParams" title="pyspark.ml.PredictionModel.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.PredictionModel.extractParamMap" title="pyspark.ml.PredictionModel.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.PredictionModel.getFeaturesCol" title="pyspark.ml.PredictionModel.getFeaturesCol"><code class="xref py py-obj docutils literal notranslate"><span class="pre">getFeaturesCol</span></code></a>()</p></td>
<td><p>Gets the value of featuresCol or its default value.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.PredictionModel.getLabelCol" title="pyspark.ml.PredictionModel.getLabelCol"><code class="xref py py-obj docutils literal notranslate"><span class="pre">getLabelCol</span></code></a>()</p></td>
<td><p>Gets the value of labelCol or its default value.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.PredictionModel.getOrDefault" title="pyspark.ml.PredictionModel.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.PredictionModel.getParam" title="pyspark.ml.PredictionModel.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-even"><td><p><a class="reference internal" href="#pyspark.ml.PredictionModel.getPredictionCol" title="pyspark.ml.PredictionModel.getPredictionCol"><code class="xref py py-obj docutils literal notranslate"><span class="pre">getPredictionCol</span></code></a>()</p></td>
<td><p>Gets the value of predictionCol or its default value.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.PredictionModel.hasDefault" title="pyspark.ml.PredictionModel.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.PredictionModel.hasParam" title="pyspark.ml.PredictionModel.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.PredictionModel.isDefined" title="pyspark.ml.PredictionModel.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.PredictionModel.isSet" title="pyspark.ml.PredictionModel.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.PredictionModel.predict" title="pyspark.ml.PredictionModel.predict"><code class="xref py py-obj docutils literal notranslate"><span class="pre">predict</span></code></a>(value)</p></td>
<td><p>Predict label for the given features.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.PredictionModel.set" title="pyspark.ml.PredictionModel.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.PredictionModel.setFeaturesCol" title="pyspark.ml.PredictionModel.setFeaturesCol"><code class="xref py py-obj docutils literal notranslate"><span class="pre">setFeaturesCol</span></code></a>(value)</p></td>
<td><p>Sets the value of <a class="reference internal" href="#pyspark.ml.PredictionModel.featuresCol" title="pyspark.ml.PredictionModel.featuresCol"><code class="xref py py-attr docutils literal notranslate"><span class="pre">featuresCol</span></code></a>.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.PredictionModel.setPredictionCol" title="pyspark.ml.PredictionModel.setPredictionCol"><code class="xref py py-obj docutils literal notranslate"><span class="pre">setPredictionCol</span></code></a>(value)</p></td>
<td><p>Sets the value of <a class="reference internal" href="#pyspark.ml.PredictionModel.predictionCol" title="pyspark.ml.PredictionModel.predictionCol"><code class="xref py py-attr docutils literal notranslate"><span class="pre">predictionCol</span></code></a>.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.PredictionModel.transform" title="pyspark.ml.PredictionModel.transform"><code class="xref py py-obj docutils literal notranslate"><span class="pre">transform</span></code></a>(dataset[, params])</p></td>
<td><p>Transforms the input dataset with optional parameters.</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.PredictionModel.featuresCol" title="pyspark.ml.PredictionModel.featuresCol"><code class="xref py py-obj docutils literal notranslate"><span class="pre">featuresCol</span></code></a></p></td>
<td><p></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.PredictionModel.labelCol" title="pyspark.ml.PredictionModel.labelCol"><code class="xref py py-obj docutils literal notranslate"><span class="pre">labelCol</span></code></a></p></td>
<td><p></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.PredictionModel.numFeatures" title="pyspark.ml.PredictionModel.numFeatures"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numFeatures</span></code></a></p></td>
<td><p>Returns the number of features the model was trained on.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.PredictionModel.params" title="pyspark.ml.PredictionModel.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.PredictionModel.predictionCol" title="pyspark.ml.PredictionModel.predictionCol"><code class="xref py py-obj docutils literal notranslate"><span class="pre">predictionCol</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.PredictionModel.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.PredictionModel.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.PredictionModel.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; P<a class="headerlink" href="#pyspark.ml.PredictionModel.copy" title="Permalink to this definition"></a></dt>
<dd><p>Creates a copy of this instance with the same uid and some
extra params. The default implementation creates a
shallow copy using <code class="xref py py-func docutils literal notranslate"><span class="pre">copy.copy()</span></code>, and then copies the
embedded and extra parameters over and returns the copy.
Subclasses should override this method if the default approach
is not sufficient.</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 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><code class="xref py py-class docutils literal notranslate"><span class="pre">Params</span></code></dt><dd><p>Copy of this instance</p>
</dd>
</dl>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.PredictionModel.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.PredictionModel.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.PredictionModel.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.PredictionModel.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.PredictionModel.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.PredictionModel.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.PredictionModel.getFeaturesCol">
<code class="sig-name descname">getFeaturesCol</code><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; str<a class="headerlink" href="#pyspark.ml.PredictionModel.getFeaturesCol" title="Permalink to this definition"></a></dt>
<dd><p>Gets the value of featuresCol or its default value.</p>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.PredictionModel.getLabelCol">
<code class="sig-name descname">getLabelCol</code><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; str<a class="headerlink" href="#pyspark.ml.PredictionModel.getLabelCol" title="Permalink to this definition"></a></dt>
<dd><p>Gets the value of labelCol or its default value.</p>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.PredictionModel.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.PredictionModel.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.PredictionModel.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.PredictionModel.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.PredictionModel.getPredictionCol">
<code class="sig-name descname">getPredictionCol</code><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; str<a class="headerlink" href="#pyspark.ml.PredictionModel.getPredictionCol" title="Permalink to this definition"></a></dt>
<dd><p>Gets the value of predictionCol or its default value.</p>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.PredictionModel.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.PredictionModel.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.PredictionModel.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.PredictionModel.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.PredictionModel.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.PredictionModel.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.PredictionModel.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.PredictionModel.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.PredictionModel.predict">
<em class="property">abstract </em><code class="sig-name descname">predict</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">value</span><span class="p">:</span> <span class="n">T</span></em><span class="sig-paren">)</span> &#x2192; float<a class="reference internal" href="../../_modules/pyspark/ml/base.html#PredictionModel.predict"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.ml.PredictionModel.predict" title="Permalink to this definition"></a></dt>
<dd><p>Predict label for the given features.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 3.0.0.</span></p>
</div>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.PredictionModel.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.PredictionModel.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.PredictionModel.setFeaturesCol">
<code class="sig-name descname">setFeaturesCol</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">value</span><span class="p">:</span> <span class="n">str</span></em><span class="sig-paren">)</span> &#x2192; P<a class="reference internal" href="../../_modules/pyspark/ml/base.html#PredictionModel.setFeaturesCol"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.ml.PredictionModel.setFeaturesCol" title="Permalink to this definition"></a></dt>
<dd><p>Sets the value of <a class="reference internal" href="#pyspark.ml.PredictionModel.featuresCol" title="pyspark.ml.PredictionModel.featuresCol"><code class="xref py py-attr docutils literal notranslate"><span class="pre">featuresCol</span></code></a>.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 3.0.0.</span></p>
</div>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.PredictionModel.setPredictionCol">
<code class="sig-name descname">setPredictionCol</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">value</span><span class="p">:</span> <span class="n">str</span></em><span class="sig-paren">)</span> &#x2192; P<a class="reference internal" href="../../_modules/pyspark/ml/base.html#PredictionModel.setPredictionCol"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.ml.PredictionModel.setPredictionCol" title="Permalink to this definition"></a></dt>
<dd><p>Sets the value of <a class="reference internal" href="#pyspark.ml.PredictionModel.predictionCol" title="pyspark.ml.PredictionModel.predictionCol"><code class="xref py py-attr docutils literal notranslate"><span class="pre">predictionCol</span></code></a>.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 3.0.0.</span></p>
</div>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.PredictionModel.transform">
<code class="sig-name descname">transform</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">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; pyspark.sql.dataframe.DataFrame<a class="headerlink" href="#pyspark.ml.PredictionModel.transform" title="Permalink to this definition"></a></dt>
<dd><p>Transforms 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, optional</span></dt><dd><p>an optional param map that overrides embedded params.</p>
</dd>
</dl>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><dl class="simple">
<dt><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></dt><dd><p>transformed dataset</p>
</dd>
</dl>
</dd>
</dl>
</dd></dl>
<p class="rubric">Attributes Documentation</p>
<dl class="py attribute">
<dt id="pyspark.ml.PredictionModel.featuresCol">
<code class="sig-name descname">featuresCol</code><em class="property"> = Param(parent='undefined', name='featuresCol', doc='features column name.')</em><a class="headerlink" href="#pyspark.ml.PredictionModel.featuresCol" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt id="pyspark.ml.PredictionModel.labelCol">
<code class="sig-name descname">labelCol</code><em class="property">: Param[str]</em><em class="property"> = Param(parent='undefined', name='labelCol', doc='label column name.')</em><a class="headerlink" href="#pyspark.ml.PredictionModel.labelCol" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt id="pyspark.ml.PredictionModel.numFeatures">
<code class="sig-name descname">numFeatures</code><a class="headerlink" href="#pyspark.ml.PredictionModel.numFeatures" title="Permalink to this definition"></a></dt>
<dd><p>Returns the number of features the model was trained on. If unknown, returns -1</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 2.1.0.</span></p>
</div>
</dd></dl>
<dl class="py attribute">
<dt id="pyspark.ml.PredictionModel.params">
<code class="sig-name descname">params</code><a class="headerlink" href="#pyspark.ml.PredictionModel.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.PredictionModel.predictionCol">
<code class="sig-name descname">predictionCol</code><em class="property"> = Param(parent='undefined', name='predictionCol', doc='prediction column name.')</em><a class="headerlink" href="#pyspark.ml.PredictionModel.predictionCol" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
</dd></dl>
</div>
</div>
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