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<a href="pyspark-module.html">Package pyspark</a> ::
<a href="pyspark.mllib-module.html">Package mllib</a> ::
<a href="pyspark.mllib.regression-module.html">Module regression</a> ::
Class LinearRegressionModel
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<!-- ==================== CLASS DESCRIPTION ==================== -->
<h1 class="epydoc">Class LinearRegressionModel</h1><p class="nomargin-top"><span class="codelink"><a href="pyspark.mllib.regression-pysrc.html#LinearRegressionModel">source code</a></span></p>
<pre class="base-tree">
object --+
|
<a href="pyspark.mllib.regression.LinearModel-class.html">LinearModel</a> --+
|
<a href="pyspark.mllib.regression.LinearRegressionModelBase-class.html">LinearRegressionModelBase</a> --+
|
<strong class="uidshort">LinearRegressionModel</strong>
</pre>
<hr />
<p>A linear regression model derived from a least-squares fit.</p>
<pre class="py-doctest">
<span class="py-prompt">>>> </span><span class="py-keyword">from</span> pyspark.mllib.regression <span class="py-keyword">import</span> LabeledPoint
<span class="py-prompt">>>> </span>data = [
<span class="py-more">... </span> LabeledPoint(0.0, [0.0]),
<span class="py-more">... </span> LabeledPoint(1.0, [1.0]),
<span class="py-more">... </span> LabeledPoint(3.0, [2.0]),
<span class="py-more">... </span> LabeledPoint(2.0, [3.0])
<span class="py-more">... </span>]
<span class="py-prompt">>>> </span>lrm = LinearRegressionWithSGD.train(sc.parallelize(data), initialWeights=array([1.0]))
<span class="py-prompt">>>> </span>abs(lrm.predict(array([0.0])) - 0) < 0.5
<span class="py-output">True</span>
<span class="py-output"></span><span class="py-prompt">>>> </span>abs(lrm.predict(array([1.0])) - 1) < 0.5
<span class="py-output">True</span>
<span class="py-output"></span><span class="py-prompt">>>> </span>abs(lrm.predict(SparseVector(1, {0: 1.0})) - 1) < 0.5
<span class="py-output">True</span>
<span class="py-output"></span><span class="py-prompt">>>> </span>data = [
<span class="py-more">... </span> LabeledPoint(0.0, SparseVector(1, {0: 0.0})),
<span class="py-more">... </span> LabeledPoint(1.0, SparseVector(1, {0: 1.0})),
<span class="py-more">... </span> LabeledPoint(3.0, SparseVector(1, {0: 2.0})),
<span class="py-more">... </span> LabeledPoint(2.0, SparseVector(1, {0: 3.0}))
<span class="py-more">... </span>]
<span class="py-prompt">>>> </span>lrm = LinearRegressionWithSGD.train(sc.parallelize(data), initialWeights=array([1.0]))
<span class="py-prompt">>>> </span>abs(lrm.predict(array([0.0])) - 0) < 0.5
<span class="py-output">True</span>
<span class="py-output"></span><span class="py-prompt">>>> </span>abs(lrm.predict(SparseVector(1, {0: 1.0})) - 1) < 0.5
<span class="py-output">True</span></pre>
<!-- ==================== INSTANCE METHODS ==================== -->
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<p class="indent-wrapped-lines"><b>Inherited from <code><a href="pyspark.mllib.regression.LinearRegressionModelBase-class.html">LinearRegressionModelBase</a></code></b>:
<code><a href="pyspark.mllib.regression.LinearRegressionModelBase-class.html#predict">predict</a></code>
</p>
<p class="indent-wrapped-lines"><b>Inherited from <code><a href="pyspark.mllib.regression.LinearModel-class.html">LinearModel</a></code></b>:
<code><a href="pyspark.mllib.regression.LinearModel-class.html#__init__">__init__</a></code>,
<code><a href="pyspark.mllib.regression.LinearModel-class.html#intercept">intercept</a></code>,
<code><a href="pyspark.mllib.regression.LinearModel-class.html#weights">weights</a></code>
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<p class="indent-wrapped-lines"><b>Inherited from <code>object</code></b>:
<code>__delattr__</code>,
<code>__format__</code>,
<code>__getattribute__</code>,
<code>__hash__</code>,
<code>__new__</code>,
<code>__reduce__</code>,
<code>__reduce_ex__</code>,
<code>__repr__</code>,
<code>__setattr__</code>,
<code>__sizeof__</code>,
<code>__str__</code>,
<code>__subclasshook__</code>
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<p class="indent-wrapped-lines"><b>Inherited from <code>object</code></b>:
<code>__class__</code>
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