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| <div class="section" id="streamingkmeans"> |
| <h1>StreamingKMeans<a class="headerlink" href="#streamingkmeans" title="Permalink to this headline">¶</a></h1> |
| <dl class="py class"> |
| <dt id="pyspark.mllib.clustering.StreamingKMeans"> |
| <em class="property">class </em><code class="sig-prename descclassname">pyspark.mllib.clustering.</code><code class="sig-name descname">StreamingKMeans</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">k</span><span class="o">=</span><span class="default_value">2</span></em>, <em class="sig-param"><span class="n">decayFactor</span><span class="o">=</span><span class="default_value">1.0</span></em>, <em class="sig-param"><span class="n">timeUnit</span><span class="o">=</span><span class="default_value">'batches'</span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyspark/mllib/clustering.html#StreamingKMeans"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.mllib.clustering.StreamingKMeans" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Provides methods to set k, decayFactor, timeUnit to configure the |
| KMeans algorithm for fitting and predicting on incoming dstreams. |
| More details on how the centroids are updated are provided under the |
| docs of StreamingKMeansModel.</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 1.5.0.</span></p> |
| </div> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><dl class="simple"> |
| <dt><strong>k</strong><span class="classifier">int, optional</span></dt><dd><p>Number of clusters. |
| (default: 2)</p> |
| </dd> |
| <dt><strong>decayFactor</strong><span class="classifier">float, optional</span></dt><dd><p>Forgetfulness of the previous centroids. |
| (default: 1.0)</p> |
| </dd> |
| <dt><strong>timeUnit</strong><span class="classifier">str, optional</span></dt><dd><p>Can be “batches” or “points”. If points, then the decay factor is |
| raised to the power of number of new points and if batches, then |
| decay factor will be used as is. |
| (default: “batches”)</p> |
| </dd> |
| </dl> |
| </dd> |
| </dl> |
| <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.mllib.clustering.StreamingKMeans.latestModel" title="pyspark.mllib.clustering.StreamingKMeans.latestModel"><code class="xref py py-obj docutils literal notranslate"><span class="pre">latestModel</span></code></a>()</p></td> |
| <td><p>Return the latest model</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyspark.mllib.clustering.StreamingKMeans.predictOn" title="pyspark.mllib.clustering.StreamingKMeans.predictOn"><code class="xref py py-obj docutils literal notranslate"><span class="pre">predictOn</span></code></a>(dstream)</p></td> |
| <td><p>Make predictions on a dstream.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.mllib.clustering.StreamingKMeans.predictOnValues" title="pyspark.mllib.clustering.StreamingKMeans.predictOnValues"><code class="xref py py-obj docutils literal notranslate"><span class="pre">predictOnValues</span></code></a>(dstream)</p></td> |
| <td><p>Make predictions on a keyed dstream.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyspark.mllib.clustering.StreamingKMeans.setDecayFactor" title="pyspark.mllib.clustering.StreamingKMeans.setDecayFactor"><code class="xref py py-obj docutils literal notranslate"><span class="pre">setDecayFactor</span></code></a>(decayFactor)</p></td> |
| <td><p>Set decay factor.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.mllib.clustering.StreamingKMeans.setHalfLife" title="pyspark.mllib.clustering.StreamingKMeans.setHalfLife"><code class="xref py py-obj docutils literal notranslate"><span class="pre">setHalfLife</span></code></a>(halfLife, timeUnit)</p></td> |
| <td><p>Set number of batches after which the centroids of that particular batch has half the weightage.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyspark.mllib.clustering.StreamingKMeans.setInitialCenters" title="pyspark.mllib.clustering.StreamingKMeans.setInitialCenters"><code class="xref py py-obj docutils literal notranslate"><span class="pre">setInitialCenters</span></code></a>(centers, weights)</p></td> |
| <td><p>Set initial centers.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.mllib.clustering.StreamingKMeans.setK" title="pyspark.mllib.clustering.StreamingKMeans.setK"><code class="xref py py-obj docutils literal notranslate"><span class="pre">setK</span></code></a>(k)</p></td> |
| <td><p>Set number of clusters.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyspark.mllib.clustering.StreamingKMeans.setRandomCenters" title="pyspark.mllib.clustering.StreamingKMeans.setRandomCenters"><code class="xref py py-obj docutils literal notranslate"><span class="pre">setRandomCenters</span></code></a>(dim, weight, seed)</p></td> |
| <td><p>Set the initial centers to be random samples from a gaussian population with constant weights.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyspark.mllib.clustering.StreamingKMeans.trainOn" title="pyspark.mllib.clustering.StreamingKMeans.trainOn"><code class="xref py py-obj docutils literal notranslate"><span class="pre">trainOn</span></code></a>(dstream)</p></td> |
| <td><p>Train the model on the incoming dstream.</p></td> |
| </tr> |
| </tbody> |
| </table> |
| <p class="rubric">Methods Documentation</p> |
| <dl class="py method"> |
| <dt id="pyspark.mllib.clustering.StreamingKMeans.latestModel"> |
| <code class="sig-name descname">latestModel</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyspark/mllib/clustering.html#StreamingKMeans.latestModel"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.mllib.clustering.StreamingKMeans.latestModel" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Return the latest model</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.mllib.clustering.StreamingKMeans.predictOn"> |
| <code class="sig-name descname">predictOn</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">dstream</span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyspark/mllib/clustering.html#StreamingKMeans.predictOn"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.mllib.clustering.StreamingKMeans.predictOn" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Make predictions on a dstream. |
| Returns a transformed dstream object</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.mllib.clustering.StreamingKMeans.predictOnValues"> |
| <code class="sig-name descname">predictOnValues</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">dstream</span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyspark/mllib/clustering.html#StreamingKMeans.predictOnValues"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.mllib.clustering.StreamingKMeans.predictOnValues" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Make predictions on a keyed dstream. |
| Returns a transformed dstream object.</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.mllib.clustering.StreamingKMeans.setDecayFactor"> |
| <code class="sig-name descname">setDecayFactor</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">decayFactor</span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyspark/mllib/clustering.html#StreamingKMeans.setDecayFactor"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.mllib.clustering.StreamingKMeans.setDecayFactor" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Set decay factor.</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.mllib.clustering.StreamingKMeans.setHalfLife"> |
| <code class="sig-name descname">setHalfLife</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">halfLife</span></em>, <em class="sig-param"><span class="n">timeUnit</span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyspark/mllib/clustering.html#StreamingKMeans.setHalfLife"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.mllib.clustering.StreamingKMeans.setHalfLife" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Set number of batches after which the centroids of that |
| particular batch has half the weightage.</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.mllib.clustering.StreamingKMeans.setInitialCenters"> |
| <code class="sig-name descname">setInitialCenters</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">centers</span></em>, <em class="sig-param"><span class="n">weights</span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyspark/mllib/clustering.html#StreamingKMeans.setInitialCenters"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.mllib.clustering.StreamingKMeans.setInitialCenters" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Set initial centers. Should be set before calling trainOn.</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.mllib.clustering.StreamingKMeans.setK"> |
| <code class="sig-name descname">setK</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">k</span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyspark/mllib/clustering.html#StreamingKMeans.setK"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.mllib.clustering.StreamingKMeans.setK" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Set number of clusters.</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.mllib.clustering.StreamingKMeans.setRandomCenters"> |
| <code class="sig-name descname">setRandomCenters</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">dim</span></em>, <em class="sig-param"><span class="n">weight</span></em>, <em class="sig-param"><span class="n">seed</span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyspark/mllib/clustering.html#StreamingKMeans.setRandomCenters"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.mllib.clustering.StreamingKMeans.setRandomCenters" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Set the initial centers to be random samples from |
| a gaussian population with constant weights.</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.mllib.clustering.StreamingKMeans.trainOn"> |
| <code class="sig-name descname">trainOn</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">dstream</span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyspark/mllib/clustering.html#StreamingKMeans.trainOn"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.mllib.clustering.StreamingKMeans.trainOn" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Train the model on the incoming dstream.</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 1.5.0.</span></p> |
| </div> |
| </dd></dl> |
| |
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