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| <div class="section" id="binaryrandomforestclassificationtrainingsummary"> |
| <h1>BinaryRandomForestClassificationTrainingSummary<a class="headerlink" href="#binaryrandomforestclassificationtrainingsummary" title="Permalink to this headline">¶</a></h1> |
| <dl class="py class"> |
| <dt id="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary"> |
| <em class="property">class </em><code class="sig-prename descclassname">pyspark.ml.classification.</code><code class="sig-name descname">BinaryRandomForestClassificationTrainingSummary</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">java_obj</span><span class="p">:</span> <span class="n">Optional<span class="p">[</span>JavaObject<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/classification.html#BinaryRandomForestClassificationTrainingSummary"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary" title="Permalink to this definition">¶</a></dt> |
| <dd><p>BinaryRandomForestClassification training results for a given model.</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 3.1.0.</span></p> |
| </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.classification.BinaryRandomForestClassificationTrainingSummary.fMeasureByLabel" title="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.fMeasureByLabel"><code class="xref py py-obj docutils literal notranslate"><span class="pre">fMeasureByLabel</span></code></a>([beta])</p></td> |
| <td><p>Returns f-measure for each label (category).</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.weightedFMeasure" title="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.weightedFMeasure"><code class="xref py py-obj docutils literal notranslate"><span class="pre">weightedFMeasure</span></code></a>([beta])</p></td> |
| <td><p>Returns weighted averaged f-measure.</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.classification.BinaryRandomForestClassificationTrainingSummary.accuracy" title="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.accuracy"><code class="xref py py-obj docutils literal notranslate"><span class="pre">accuracy</span></code></a></p></td> |
| <td><p>Returns accuracy.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.areaUnderROC" title="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.areaUnderROC"><code class="xref py py-obj docutils literal notranslate"><span class="pre">areaUnderROC</span></code></a></p></td> |
| <td><p>Computes the area under the receiver operating characteristic (ROC) curve.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.fMeasureByThreshold" title="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.fMeasureByThreshold"><code class="xref py py-obj docutils literal notranslate"><span class="pre">fMeasureByThreshold</span></code></a></p></td> |
| <td><p>Returns a dataframe with two fields (threshold, F-Measure) curve with beta = 1.0.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.falsePositiveRateByLabel" title="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.falsePositiveRateByLabel"><code class="xref py py-obj docutils literal notranslate"><span class="pre">falsePositiveRateByLabel</span></code></a></p></td> |
| <td><p>Returns false positive rate for each label (category).</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.labelCol" title="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.labelCol"><code class="xref py py-obj docutils literal notranslate"><span class="pre">labelCol</span></code></a></p></td> |
| <td><p>Field in “predictions” which gives the true label of each instance.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.labels" title="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.labels"><code class="xref py py-obj docutils literal notranslate"><span class="pre">labels</span></code></a></p></td> |
| <td><p>Returns the sequence of labels in ascending order.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.objectiveHistory" title="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.objectiveHistory"><code class="xref py py-obj docutils literal notranslate"><span class="pre">objectiveHistory</span></code></a></p></td> |
| <td><p>Objective function (scaled loss + regularization) at each iteration.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.pr" title="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.pr"><code class="xref py py-obj docutils literal notranslate"><span class="pre">pr</span></code></a></p></td> |
| <td><p>Returns the precision-recall curve, which is a Dataframe containing two fields recall, precision with (0.0, 1.0) prepended to it.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.precisionByLabel" title="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.precisionByLabel"><code class="xref py py-obj docutils literal notranslate"><span class="pre">precisionByLabel</span></code></a></p></td> |
| <td><p>Returns precision for each label (category).</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.precisionByThreshold" title="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.precisionByThreshold"><code class="xref py py-obj docutils literal notranslate"><span class="pre">precisionByThreshold</span></code></a></p></td> |
| <td><p>Returns a dataframe with two fields (threshold, precision) curve.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.predictionCol" title="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.predictionCol"><code class="xref py py-obj docutils literal notranslate"><span class="pre">predictionCol</span></code></a></p></td> |
| <td><p>Field in “predictions” which gives the prediction of each class.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.predictions" title="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.predictions"><code class="xref py py-obj docutils literal notranslate"><span class="pre">predictions</span></code></a></p></td> |
| <td><p>Dataframe outputted by the model’s <cite>transform</cite> method.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.recallByLabel" title="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.recallByLabel"><code class="xref py py-obj docutils literal notranslate"><span class="pre">recallByLabel</span></code></a></p></td> |
| <td><p>Returns recall for each label (category).</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.recallByThreshold" title="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.recallByThreshold"><code class="xref py py-obj docutils literal notranslate"><span class="pre">recallByThreshold</span></code></a></p></td> |
| <td><p>Returns a dataframe with two fields (threshold, recall) curve.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.roc" title="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.roc"><code class="xref py py-obj docutils literal notranslate"><span class="pre">roc</span></code></a></p></td> |
| <td><p>Returns the receiver operating characteristic (ROC) curve, which is a Dataframe having two fields (FPR, TPR) with (0.0, 0.0) prepended and (1.0, 1.0) appended to it.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.scoreCol" title="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.scoreCol"><code class="xref py py-obj docutils literal notranslate"><span class="pre">scoreCol</span></code></a></p></td> |
| <td><p>Field in “predictions” which gives the probability or raw prediction of each class as a vector.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.totalIterations" title="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.totalIterations"><code class="xref py py-obj docutils literal notranslate"><span class="pre">totalIterations</span></code></a></p></td> |
| <td><p>Number of training iterations until termination.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.truePositiveRateByLabel" title="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.truePositiveRateByLabel"><code class="xref py py-obj docutils literal notranslate"><span class="pre">truePositiveRateByLabel</span></code></a></p></td> |
| <td><p>Returns true positive rate for each label (category).</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.weightCol" title="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.weightCol"><code class="xref py py-obj docutils literal notranslate"><span class="pre">weightCol</span></code></a></p></td> |
| <td><p>Field in “predictions” which gives the weight of each instance as a vector.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.weightedFalsePositiveRate" title="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.weightedFalsePositiveRate"><code class="xref py py-obj docutils literal notranslate"><span class="pre">weightedFalsePositiveRate</span></code></a></p></td> |
| <td><p>Returns weighted false positive rate.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.weightedPrecision" title="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.weightedPrecision"><code class="xref py py-obj docutils literal notranslate"><span class="pre">weightedPrecision</span></code></a></p></td> |
| <td><p>Returns weighted averaged precision.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.weightedRecall" title="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.weightedRecall"><code class="xref py py-obj docutils literal notranslate"><span class="pre">weightedRecall</span></code></a></p></td> |
| <td><p>Returns weighted averaged recall.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.weightedTruePositiveRate" title="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.weightedTruePositiveRate"><code class="xref py py-obj docutils literal notranslate"><span class="pre">weightedTruePositiveRate</span></code></a></p></td> |
| <td><p>Returns weighted true positive rate.</p></td> |
| </tr> |
| </tbody> |
| </table> |
| <p class="rubric">Methods Documentation</p> |
| <dl class="py method"> |
| <dt id="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.fMeasureByLabel"> |
| <code class="sig-name descname">fMeasureByLabel</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">beta</span><span class="p">:</span> <span class="n">float</span> <span class="o">=</span> <span class="default_value">1.0</span></em><span class="sig-paren">)</span> → List<span class="p">[</span>float<span class="p">]</span><a class="headerlink" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.fMeasureByLabel" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Returns f-measure for each label (category).</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 3.1.0.</span></p> |
| </div> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.weightedFMeasure"> |
| <code class="sig-name descname">weightedFMeasure</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">beta</span><span class="p">:</span> <span class="n">float</span> <span class="o">=</span> <span class="default_value">1.0</span></em><span class="sig-paren">)</span> → float<a class="headerlink" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.weightedFMeasure" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Returns weighted averaged f-measure.</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 3.1.0.</span></p> |
| </div> |
| </dd></dl> |
| |
| <p class="rubric">Attributes Documentation</p> |
| <dl class="py attribute"> |
| <dt id="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.accuracy"> |
| <code class="sig-name descname">accuracy</code><a class="headerlink" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.accuracy" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Returns accuracy. |
| (equals to the total number of correctly classified instances |
| out of the total number of instances.)</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 3.1.0.</span></p> |
| </div> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.areaUnderROC"> |
| <code class="sig-name descname">areaUnderROC</code><a class="headerlink" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.areaUnderROC" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Computes the area under the receiver operating characteristic |
| (ROC) curve.</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 3.1.0.</span></p> |
| </div> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.fMeasureByThreshold"> |
| <code class="sig-name descname">fMeasureByThreshold</code><a class="headerlink" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.fMeasureByThreshold" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Returns a dataframe with two fields (threshold, F-Measure) curve |
| with beta = 1.0.</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 3.1.0.</span></p> |
| </div> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.falsePositiveRateByLabel"> |
| <code class="sig-name descname">falsePositiveRateByLabel</code><a class="headerlink" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.falsePositiveRateByLabel" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Returns false positive rate for each label (category).</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 3.1.0.</span></p> |
| </div> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.labelCol"> |
| <code class="sig-name descname">labelCol</code><a class="headerlink" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.labelCol" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Field in “predictions” which gives the true label of each |
| instance.</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 3.1.0.</span></p> |
| </div> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.labels"> |
| <code class="sig-name descname">labels</code><a class="headerlink" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.labels" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Returns the sequence of labels in ascending order. This order matches the order used |
| in metrics which are specified as arrays over labels, e.g., truePositiveRateByLabel.</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 3.1.0.</span></p> |
| </div> |
| <p class="rubric">Notes</p> |
| <p>In most cases, it will be values {0.0, 1.0, …, numClasses-1}, However, if the |
| training set is missing a label, then all of the arrays over labels |
| (e.g., from truePositiveRateByLabel) will be of length numClasses-1 instead of the |
| expected numClasses.</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.objectiveHistory"> |
| <code class="sig-name descname">objectiveHistory</code><a class="headerlink" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.objectiveHistory" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Objective function (scaled loss + regularization) at each |
| iteration. It contains one more element, the initial state, |
| than number of iterations.</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 3.1.0.</span></p> |
| </div> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.pr"> |
| <code class="sig-name descname">pr</code><a class="headerlink" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.pr" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Returns the precision-recall curve, which is a Dataframe |
| containing two fields recall, precision with (0.0, 1.0) prepended |
| to it.</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 3.1.0.</span></p> |
| </div> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.precisionByLabel"> |
| <code class="sig-name descname">precisionByLabel</code><a class="headerlink" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.precisionByLabel" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Returns precision for each label (category).</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 3.1.0.</span></p> |
| </div> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.precisionByThreshold"> |
| <code class="sig-name descname">precisionByThreshold</code><a class="headerlink" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.precisionByThreshold" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Returns a dataframe with two fields (threshold, precision) curve. |
| Every possible probability obtained in transforming the dataset |
| are used as thresholds used in calculating the precision.</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 3.1.0.</span></p> |
| </div> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.predictionCol"> |
| <code class="sig-name descname">predictionCol</code><a class="headerlink" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.predictionCol" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Field in “predictions” which gives the prediction of each class.</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 3.1.0.</span></p> |
| </div> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.predictions"> |
| <code class="sig-name descname">predictions</code><a class="headerlink" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.predictions" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Dataframe outputted by the model’s <cite>transform</cite> method.</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 3.1.0.</span></p> |
| </div> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.recallByLabel"> |
| <code class="sig-name descname">recallByLabel</code><a class="headerlink" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.recallByLabel" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Returns recall for each label (category).</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 3.1.0.</span></p> |
| </div> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.recallByThreshold"> |
| <code class="sig-name descname">recallByThreshold</code><a class="headerlink" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.recallByThreshold" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Returns a dataframe with two fields (threshold, recall) curve. |
| Every possible probability obtained in transforming the dataset |
| are used as thresholds used in calculating the recall.</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 3.1.0.</span></p> |
| </div> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.roc"> |
| <code class="sig-name descname">roc</code><a class="headerlink" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.roc" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Returns the receiver operating characteristic (ROC) curve, |
| which is a Dataframe having two fields (FPR, TPR) with |
| (0.0, 0.0) prepended and (1.0, 1.0) appended to it.</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 3.1.0.</span></p> |
| </div> |
| <p class="rubric">Notes</p> |
| <p><a class="reference external" href="http://en.wikipedia.org/wiki/Receiver_operating_characteristic">Wikipedia reference</a></p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.scoreCol"> |
| <code class="sig-name descname">scoreCol</code><a class="headerlink" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.scoreCol" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Field in “predictions” which gives the probability or raw prediction |
| of each class as a vector.</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 3.1.0.</span></p> |
| </div> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.totalIterations"> |
| <code class="sig-name descname">totalIterations</code><a class="headerlink" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.totalIterations" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Number of training iterations until termination.</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 3.1.0.</span></p> |
| </div> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.truePositiveRateByLabel"> |
| <code class="sig-name descname">truePositiveRateByLabel</code><a class="headerlink" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.truePositiveRateByLabel" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Returns true positive rate for each label (category).</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 3.1.0.</span></p> |
| </div> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.weightCol"> |
| <code class="sig-name descname">weightCol</code><a class="headerlink" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.weightCol" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Field in “predictions” which gives the weight of each instance |
| as a vector.</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 3.1.0.</span></p> |
| </div> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.weightedFalsePositiveRate"> |
| <code class="sig-name descname">weightedFalsePositiveRate</code><a class="headerlink" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.weightedFalsePositiveRate" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Returns weighted false positive rate.</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 3.1.0.</span></p> |
| </div> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.weightedPrecision"> |
| <code class="sig-name descname">weightedPrecision</code><a class="headerlink" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.weightedPrecision" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Returns weighted averaged precision.</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 3.1.0.</span></p> |
| </div> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.weightedRecall"> |
| <code class="sig-name descname">weightedRecall</code><a class="headerlink" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.weightedRecall" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Returns weighted averaged recall. |
| (equals to precision, recall and f-measure)</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 3.1.0.</span></p> |
| </div> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.weightedTruePositiveRate"> |
| <code class="sig-name descname">weightedTruePositiveRate</code><a class="headerlink" href="#pyspark.ml.classification.BinaryRandomForestClassificationTrainingSummary.weightedTruePositiveRate" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Returns weighted true positive rate. |
| (equals to precision, recall and f-measure)</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 3.1.0.</span></p> |
| </div> |
| </dd></dl> |
| |
| </dd></dl> |
| |
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