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<div class="section" id="module-snap_ml_spark.Metrics">
<span id="metrics"></span><span id="sp-met-doc"></span><h1>Metrics<a class="headerlink" href="#module-snap_ml_spark.Metrics" title="Permalink to this headline">¶</a></h1>
<dl class="function">
<dt id="snap_ml_spark.Metrics.accuracy">
<code class="descclassname">snap_ml_spark.Metrics.</code><code class="descname">accuracy</code><span class="sig-paren">(</span><em>dataWithPredictions</em><span class="sig-paren">)</span><a class="headerlink" href="#snap_ml_spark.Metrics.accuracy" title="Permalink to this definition">¶</a></dt>
<dd><table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>dataWithPredictions</strong> – binary predictions computed by the LogisticRegression or SupportVectorMachine predict() function</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">accuracy computed based on the binary predictions of a classifier (LogisticRegression, SupportVectorMachines)</td>
</tr>
<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">double</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="snap_ml_spark.Metrics.f1score">
<code class="descclassname">snap_ml_spark.Metrics.</code><code class="descname">f1score</code><span class="sig-paren">(</span><em>dataWithPredictions</em><span class="sig-paren">)</span><a class="headerlink" href="#snap_ml_spark.Metrics.f1score" title="Permalink to this definition">¶</a></dt>
<dd><table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>dataWithPredictions</strong> – binary predictions computed by the LogisticRegression or SupportVectorMachine predict() function</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">f1score metric (2*(precision*recall)/(precision+recall)), computed based on the binary predictions of a classifier (LogisticRegression, SupportVectorMachines)</td>
</tr>
<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">double</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="snap_ml_spark.Metrics.logisticLoss">
<code class="descclassname">snap_ml_spark.Metrics.</code><code class="descname">logisticLoss</code><span class="sig-paren">(</span><em>dataWithPredictions</em><span class="sig-paren">)</span><a class="headerlink" href="#snap_ml_spark.Metrics.logisticLoss" title="Permalink to this definition">¶</a></dt>
<dd><table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>dataWithPredictions</strong> – probabilities computed by the LogisticRegression predict_proba() function</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">logistic loss computed by the logistic regression predicted probabilities</td>
</tr>
<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">double</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="snap_ml_spark.Metrics.meanSquaredError">
<code class="descclassname">snap_ml_spark.Metrics.</code><code class="descname">meanSquaredError</code><span class="sig-paren">(</span><em>dataWithPredictions</em><span class="sig-paren">)</span><a class="headerlink" href="#snap_ml_spark.Metrics.meanSquaredError" title="Permalink to this definition">¶</a></dt>
<dd><table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>dataWithPredictions</strong> – linear regression predictions, predicted by the RidgeRegression predict() function</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">mean squared error computed based on the provided dataWithPredictions parameter</td>
</tr>
<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">double</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="snap_ml_spark.Metrics.precision">
<code class="descclassname">snap_ml_spark.Metrics.</code><code class="descname">precision</code><span class="sig-paren">(</span><em>dataWithPredictions</em><span class="sig-paren">)</span><a class="headerlink" href="#snap_ml_spark.Metrics.precision" title="Permalink to this definition">¶</a></dt>
<dd><table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>dataWithPredictions</strong> – binary predictions computed by the LogisticRegression or SupportVectorMachine predict() function</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">precision metric (TP/(TP+FP)), computed based on the binary predictions of a classifier (LogisticRegression, SupportVectorMachines)</td>
</tr>
<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">double</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="function">
<dt id="snap_ml_spark.Metrics.recall">
<code class="descclassname">snap_ml_spark.Metrics.</code><code class="descname">recall</code><span class="sig-paren">(</span><em>dataWithPredictions</em><span class="sig-paren">)</span><a class="headerlink" href="#snap_ml_spark.Metrics.recall" title="Permalink to this definition">¶</a></dt>
<dd><table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>dataWithPredictions</strong> – binary predictions computed by the LogisticRegression or SupportVectorMachine predict() function</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">recall metric (TP/(TP+FN)), computed based on the binary predictions of a classifier (LogisticRegression, SupportVectorMachines)</td>
</tr>
<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">double</td>
</tr>
</tbody>
</table>
</dd></dl>
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