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<div class="section" id="rankingevaluator">
<h1>RankingEvaluator<a class="headerlink" href="#rankingevaluator" title="Permalink to this headline"></a></h1>
<dl class="py class">
<dt id="pyspark.ml.evaluation.RankingEvaluator">
<em class="property">class </em><code class="sig-prename descclassname">pyspark.ml.evaluation.</code><code class="sig-name descname">RankingEvaluator</code><span class="sig-paren">(</span><em class="sig-param"><span class="o">*</span></em>, <em class="sig-param"><span class="n">predictionCol</span><span class="p">:</span> <span class="n">str</span> <span class="o">=</span> <span class="default_value">'prediction'</span></em>, <em class="sig-param"><span class="n">labelCol</span><span class="p">:</span> <span class="n">str</span> <span class="o">=</span> <span class="default_value">'label'</span></em>, <em class="sig-param"><span class="n">metricName</span><span class="p">:</span> <span class="n">RankingEvaluatorMetricType</span> <span class="o">=</span> <span class="default_value">'meanAveragePrecision'</span></em>, <em class="sig-param"><span class="n">k</span><span class="p">:</span> <span class="n">int</span> <span class="o">=</span> <span class="default_value">10</span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyspark/ml/evaluation.html#RankingEvaluator"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.ml.evaluation.RankingEvaluator" title="Permalink to this definition"></a></dt>
<dd><p>Evaluator for Ranking, which expects two input
columns: prediction and label.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 3.0.0.</span></p>
</div>
<p class="rubric">Notes</p>
<p>Experimental</p>
<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="n">scoreAndLabels</span> <span class="o">=</span> <span class="p">[([</span><span class="mf">1.0</span><span class="p">,</span> <span class="mf">6.0</span><span class="p">,</span> <span class="mf">2.0</span><span class="p">,</span> <span class="mf">7.0</span><span class="p">,</span> <span class="mf">8.0</span><span class="p">,</span> <span class="mf">3.0</span><span class="p">,</span> <span class="mf">9.0</span><span class="p">,</span> <span class="mf">10.0</span><span class="p">,</span> <span class="mf">4.0</span><span class="p">,</span> <span class="mf">5.0</span><span class="p">],</span>
<span class="gp">... </span> <span class="p">[</span><span class="mf">1.0</span><span class="p">,</span> <span class="mf">2.0</span><span class="p">,</span> <span class="mf">3.0</span><span class="p">,</span> <span class="mf">4.0</span><span class="p">,</span> <span class="mf">5.0</span><span class="p">]),</span>
<span class="gp">... </span> <span class="p">([</span><span class="mf">4.0</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">,</span> <span class="mf">5.0</span><span class="p">,</span> <span class="mf">6.0</span><span class="p">,</span> <span class="mf">2.0</span><span class="p">,</span> <span class="mf">7.0</span><span class="p">,</span> <span class="mf">3.0</span><span class="p">,</span> <span class="mf">8.0</span><span class="p">,</span> <span class="mf">9.0</span><span class="p">,</span> <span class="mf">10.0</span><span class="p">],</span> <span class="p">[</span><span class="mf">1.0</span><span class="p">,</span> <span class="mf">2.0</span><span class="p">,</span> <span class="mf">3.0</span><span class="p">]),</span>
<span class="gp">... </span> <span class="p">([</span><span class="mf">1.0</span><span class="p">,</span> <span class="mf">2.0</span><span class="p">,</span> <span class="mf">3.0</span><span class="p">,</span> <span class="mf">4.0</span><span class="p">,</span> <span class="mf">5.0</span><span class="p">],</span> <span class="p">[])]</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="n">scoreAndLabels</span><span class="p">,</span> <span class="p">[</span><span class="s2">&quot;prediction&quot;</span><span class="p">,</span> <span class="s2">&quot;label&quot;</span><span class="p">])</span>
<span class="gp">...</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">evaluator</span> <span class="o">=</span> <span class="n">RankingEvaluator</span><span class="p">()</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">evaluator</span><span class="o">.</span><span class="n">setPredictionCol</span><span class="p">(</span><span class="s2">&quot;prediction&quot;</span><span class="p">)</span>
<span class="go">RankingEvaluator...</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">dataset</span><span class="p">)</span>
<span class="go">0.35...</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">dataset</span><span class="p">,</span> <span class="p">{</span><span class="n">evaluator</span><span class="o">.</span><span class="n">metricName</span><span class="p">:</span> <span class="s2">&quot;precisionAtK&quot;</span><span class="p">,</span> <span class="n">evaluator</span><span class="o">.</span><span class="n">k</span><span class="p">:</span> <span class="mi">2</span><span class="p">})</span>
<span class="go">0.33...</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">ranke_path</span> <span class="o">=</span> <span class="n">temp_path</span> <span class="o">+</span> <span class="s2">&quot;/ranke&quot;</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">evaluator</span><span class="o">.</span><span class="n">save</span><span class="p">(</span><span class="n">ranke_path</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">evaluator2</span> <span class="o">=</span> <span class="n">RankingEvaluator</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">ranke_path</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="nb">str</span><span class="p">(</span><span class="n">evaluator2</span><span class="o">.</span><span class="n">getPredictionCol</span><span class="p">())</span>
<span class="go">&#39;prediction&#39;</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.evaluation.RankingEvaluator.clear" title="pyspark.ml.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.copy" title="pyspark.ml.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.evaluate" title="pyspark.ml.evaluation.RankingEvaluator.evaluate"><code class="xref py py-obj docutils literal notranslate"><span class="pre">evaluate</span></code></a>(dataset[, params])</p></td>
<td><p>Evaluates the output with optional parameters.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.evaluation.RankingEvaluator.explainParam" title="pyspark.ml.evaluation.RankingEvaluator.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-odd"><td><p><a class="reference internal" href="#pyspark.ml.evaluation.RankingEvaluator.explainParams" title="pyspark.ml.evaluation.RankingEvaluator.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-even"><td><p><a class="reference internal" href="#pyspark.ml.evaluation.RankingEvaluator.extractParamMap" title="pyspark.ml.evaluation.RankingEvaluator.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-odd"><td><p><a class="reference internal" href="#pyspark.ml.evaluation.RankingEvaluator.getK" title="pyspark.ml.evaluation.RankingEvaluator.getK"><code class="xref py py-obj docutils literal notranslate"><span class="pre">getK</span></code></a>()</p></td>
<td><p>Gets the value of k or its default value.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.evaluation.RankingEvaluator.getLabelCol" title="pyspark.ml.evaluation.RankingEvaluator.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-odd"><td><p><a class="reference internal" href="#pyspark.ml.evaluation.RankingEvaluator.getMetricName" title="pyspark.ml.evaluation.RankingEvaluator.getMetricName"><code class="xref py py-obj docutils literal notranslate"><span class="pre">getMetricName</span></code></a>()</p></td>
<td><p>Gets the value of metricName or its default value.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.evaluation.RankingEvaluator.getOrDefault" title="pyspark.ml.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.getParam" title="pyspark.ml.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.getPredictionCol" title="pyspark.ml.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.hasDefault" title="pyspark.ml.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.hasParam" title="pyspark.ml.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.isDefined" title="pyspark.ml.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.isLargerBetter" title="pyspark.ml.evaluation.RankingEvaluator.isLargerBetter"><code class="xref py py-obj docutils literal notranslate"><span class="pre">isLargerBetter</span></code></a>()</p></td>
<td><p>Indicates whether the metric returned by <a class="reference internal" href="#pyspark.ml.evaluation.RankingEvaluator.evaluate" title="pyspark.ml.evaluation.RankingEvaluator.evaluate"><code class="xref py py-meth docutils literal notranslate"><span class="pre">evaluate()</span></code></a> should be maximized (True, default) or minimized (False).</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.evaluation.RankingEvaluator.isSet" title="pyspark.ml.evaluation.RankingEvaluator.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-even"><td><p><a class="reference internal" href="#pyspark.ml.evaluation.RankingEvaluator.load" title="pyspark.ml.evaluation.RankingEvaluator.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-odd"><td><p><a class="reference internal" href="#pyspark.ml.evaluation.RankingEvaluator.read" title="pyspark.ml.evaluation.RankingEvaluator.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-even"><td><p><a class="reference internal" href="#pyspark.ml.evaluation.RankingEvaluator.save" title="pyspark.ml.evaluation.RankingEvaluator.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-odd"><td><p><a class="reference internal" href="#pyspark.ml.evaluation.RankingEvaluator.set" title="pyspark.ml.evaluation.RankingEvaluator.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-even"><td><p><a class="reference internal" href="#pyspark.ml.evaluation.RankingEvaluator.setK" title="pyspark.ml.evaluation.RankingEvaluator.setK"><code class="xref py py-obj docutils literal notranslate"><span class="pre">setK</span></code></a>(value)</p></td>
<td><p>Sets the value of <a class="reference internal" href="#pyspark.ml.evaluation.RankingEvaluator.k" title="pyspark.ml.evaluation.RankingEvaluator.k"><code class="xref py py-attr docutils literal notranslate"><span class="pre">k</span></code></a>.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.evaluation.RankingEvaluator.setLabelCol" title="pyspark.ml.evaluation.RankingEvaluator.setLabelCol"><code class="xref py py-obj docutils literal notranslate"><span class="pre">setLabelCol</span></code></a>(value)</p></td>
<td><p>Sets the value of <a class="reference internal" href="#pyspark.ml.evaluation.RankingEvaluator.labelCol" title="pyspark.ml.evaluation.RankingEvaluator.labelCol"><code class="xref py py-attr docutils literal notranslate"><span class="pre">labelCol</span></code></a>.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.evaluation.RankingEvaluator.setMetricName" title="pyspark.ml.evaluation.RankingEvaluator.setMetricName"><code class="xref py py-obj docutils literal notranslate"><span class="pre">setMetricName</span></code></a>(value)</p></td>
<td><p>Sets the value of <a class="reference internal" href="#pyspark.ml.evaluation.RankingEvaluator.metricName" title="pyspark.ml.evaluation.RankingEvaluator.metricName"><code class="xref py py-attr docutils literal notranslate"><span class="pre">metricName</span></code></a>.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.evaluation.RankingEvaluator.setParams" title="pyspark.ml.evaluation.RankingEvaluator.setParams"><code class="xref py py-obj docutils literal notranslate"><span class="pre">setParams</span></code></a>(self, \*[, predictionCol, labelCol, k])</p></td>
<td><p>Sets params for ranking evaluator.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.evaluation.RankingEvaluator.setPredictionCol" title="pyspark.ml.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.predictionCol" title="pyspark.ml.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.write" title="pyspark.ml.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.k" title="pyspark.ml.evaluation.RankingEvaluator.k"><code class="xref py py-obj docutils literal notranslate"><span class="pre">k</span></code></a></p></td>
<td><p></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.evaluation.RankingEvaluator.labelCol" title="pyspark.ml.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.metricName" title="pyspark.ml.evaluation.RankingEvaluator.metricName"><code class="xref py py-obj docutils literal notranslate"><span class="pre">metricName</span></code></a></p></td>
<td><p></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.evaluation.RankingEvaluator.params" title="pyspark.ml.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.predictionCol" title="pyspark.ml.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.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; JP<a class="headerlink" href="#pyspark.ml.evaluation.RankingEvaluator.copy" title="Permalink to this definition"></a></dt>
<dd><p>Creates a copy of this instance with the same uid and some
extra params. This implementation first calls Params.copy and
then make a copy of the companion Java pipeline component with
extra params. So both the Python wrapper and the Java pipeline
component get copied.</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">JavaParams</span></code></dt><dd><p>Copy of this instance</p>
</dd>
</dl>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.evaluation.RankingEvaluator.evaluate">
<code class="sig-name descname">evaluate</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; float<a class="headerlink" href="#pyspark.ml.evaluation.RankingEvaluator.evaluate" title="Permalink to this definition"></a></dt>
<dd><p>Evaluates the output with optional parameters.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 1.4.0.</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>a dataset that contains labels/observations and predictions</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>float</dt><dd><p>metric</p>
</dd>
</dl>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.getK">
<code class="sig-name descname">getK</code><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; int<a class="reference internal" href="../../_modules/pyspark/ml/evaluation.html#RankingEvaluator.getK"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.ml.evaluation.RankingEvaluator.getK" title="Permalink to this definition"></a></dt>
<dd><p>Gets the value of k or its default value.</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.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.getMetricName">
<code class="sig-name descname">getMetricName</code><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; RankingEvaluatorMetricType<a class="reference internal" href="../../_modules/pyspark/ml/evaluation.html#RankingEvaluator.getMetricName"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.ml.evaluation.RankingEvaluator.getMetricName" title="Permalink to this definition"></a></dt>
<dd><p>Gets the value of metricName or its default value.</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.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.isLargerBetter">
<code class="sig-name descname">isLargerBetter</code><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; bool<a class="headerlink" href="#pyspark.ml.evaluation.RankingEvaluator.isLargerBetter" title="Permalink to this definition"></a></dt>
<dd><p>Indicates whether the metric returned by <a class="reference internal" href="#pyspark.ml.evaluation.RankingEvaluator.evaluate" title="pyspark.ml.evaluation.RankingEvaluator.evaluate"><code class="xref py py-meth docutils literal notranslate"><span class="pre">evaluate()</span></code></a> should be maximized
(True, default) or minimized (False).
A given evaluator may support multiple metrics which may be maximized or minimized.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 1.5.0.</span></p>
</div>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.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.util.JavaMLReader<span class="p">[</span>RL<span class="p">]</span><a class="headerlink" href="#pyspark.ml.evaluation.RankingEvaluator.read" title="Permalink to this definition"></a></dt>
<dd><p>Returns an MLReader instance for this class.</p>
</dd></dl>
<dl class="py method">
<dt id="pyspark.ml.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.setK">
<code class="sig-name descname">setK</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.evaluation.RankingEvaluator" title="pyspark.ml.evaluation.RankingEvaluator">pyspark.ml.evaluation.RankingEvaluator</a><a class="reference internal" href="../../_modules/pyspark/ml/evaluation.html#RankingEvaluator.setK"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.ml.evaluation.RankingEvaluator.setK" title="Permalink to this definition"></a></dt>
<dd><p>Sets the value of <a class="reference internal" href="#pyspark.ml.evaluation.RankingEvaluator.k" title="pyspark.ml.evaluation.RankingEvaluator.k"><code class="xref py py-attr docutils literal notranslate"><span class="pre">k</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.evaluation.RankingEvaluator.setLabelCol">
<code class="sig-name descname">setLabelCol</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; <a class="reference internal" href="#pyspark.ml.evaluation.RankingEvaluator" title="pyspark.ml.evaluation.RankingEvaluator">pyspark.ml.evaluation.RankingEvaluator</a><a class="reference internal" href="../../_modules/pyspark/ml/evaluation.html#RankingEvaluator.setLabelCol"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.ml.evaluation.RankingEvaluator.setLabelCol" title="Permalink to this definition"></a></dt>
<dd><p>Sets the value of <a class="reference internal" href="#pyspark.ml.evaluation.RankingEvaluator.labelCol" title="pyspark.ml.evaluation.RankingEvaluator.labelCol"><code class="xref py py-attr docutils literal notranslate"><span class="pre">labelCol</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.evaluation.RankingEvaluator.setMetricName">
<code class="sig-name descname">setMetricName</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">value</span><span class="p">:</span> <span class="n">RankingEvaluatorMetricType</span></em><span class="sig-paren">)</span> &#x2192; RankingEvaluator<a class="reference internal" href="../../_modules/pyspark/ml/evaluation.html#RankingEvaluator.setMetricName"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.ml.evaluation.RankingEvaluator.setMetricName" title="Permalink to this definition"></a></dt>
<dd><p>Sets the value of <a class="reference internal" href="#pyspark.ml.evaluation.RankingEvaluator.metricName" title="pyspark.ml.evaluation.RankingEvaluator.metricName"><code class="xref py py-attr docutils literal notranslate"><span class="pre">metricName</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.evaluation.RankingEvaluator.setParams">
<code class="sig-name descname">setParams</code><span class="sig-paren">(</span><em class="sig-param">self</em>, <em class="sig-param">\*</em>, <em class="sig-param">predictionCol=&quot;prediction&quot;</em>, <em class="sig-param">labelCol=&quot;label&quot;</em>, <em class="sig-param">metricName=&quot;meanAveragePrecision&quot;</em>, <em class="sig-param">k=10</em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyspark/ml/evaluation.html#RankingEvaluator.setParams"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.ml.evaluation.RankingEvaluator.setParams" title="Permalink to this definition"></a></dt>
<dd><p>Sets params for ranking evaluator.</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.evaluation.RankingEvaluator.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; <a class="reference internal" href="#pyspark.ml.evaluation.RankingEvaluator" title="pyspark.ml.evaluation.RankingEvaluator">pyspark.ml.evaluation.RankingEvaluator</a><a class="reference internal" href="../../_modules/pyspark/ml/evaluation.html#RankingEvaluator.setPredictionCol"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.ml.evaluation.RankingEvaluator.setPredictionCol" title="Permalink to this definition"></a></dt>
<dd><p>Sets the value of <a class="reference internal" href="#pyspark.ml.evaluation.RankingEvaluator.predictionCol" title="pyspark.ml.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.write">
<code class="sig-name descname">write</code><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; pyspark.ml.util.JavaMLWriter<a class="headerlink" href="#pyspark.ml.evaluation.RankingEvaluator.write" title="Permalink to this definition"></a></dt>
<dd><p>Returns an MLWriter instance for this ML instance.</p>
</dd></dl>
<p class="rubric">Attributes Documentation</p>
<dl class="py attribute">
<dt id="pyspark.ml.evaluation.RankingEvaluator.k">
<code class="sig-name descname">k</code><em class="property">: pyspark.ml.param.Param[int]</em><em class="property"> = Param(parent='undefined', name='k', doc='The ranking position value used in meanAveragePrecisionAtK|precisionAtK|ndcgAtK|recallAtK. Must be &gt; 0. The default value is 10.')</em><a class="headerlink" href="#pyspark.ml.evaluation.RankingEvaluator.k" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt id="pyspark.ml.evaluation.RankingEvaluator.labelCol">
<code class="sig-name descname">labelCol</code><em class="property"> = Param(parent='undefined', name='labelCol', doc='label column name.')</em><a class="headerlink" href="#pyspark.ml.evaluation.RankingEvaluator.labelCol" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt id="pyspark.ml.evaluation.RankingEvaluator.metricName">
<code class="sig-name descname">metricName</code><em class="property">: pyspark.ml.param.Param[RankingEvaluatorMetricType]</em><em class="property"> = Param(parent='undefined', name='metricName', doc='metric name in evaluation (meanAveragePrecision|meanAveragePrecisionAtK|precisionAtK|ndcgAtK|recallAtK)')</em><a class="headerlink" href="#pyspark.ml.evaluation.RankingEvaluator.metricName" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt id="pyspark.ml.evaluation.RankingEvaluator.params">
<code class="sig-name descname">params</code><a class="headerlink" href="#pyspark.ml.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.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.evaluation.RankingEvaluator.predictionCol" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
</dd></dl>
</div>
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