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<div class="subTitle">org.apache.spark.mllib.regression</div>
<h2 title="Class IsotonicRegression" class="title">Class IsotonicRegression</h2>
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<li>java.lang.Object</li>
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<pre>public class <span class="strong">IsotonicRegression</span>
extends java.lang.Object
implements java.io.Serializable</pre>
<div class="block">:: Experimental ::
<p>
Isotonic regression.
Currently implemented using parallelized pool adjacent violators algorithm.
Only univariate (single feature) algorithm supported.
<p>
Sequential PAV implementation based on:
Tibshirani, Ryan J., Holger Hoefling, and Robert Tibshirani.
"Nearly-isotonic regression." Technometrics 53.1 (2011): 54-61.
Available from <code>http://www.stat.cmu.edu/~ryantibs/papers/neariso.pdf</code>
<p>
Sequential PAV parallelization based on:
Kearsley, Anthony J., Richard A. Tapia, and Michael W. Trosset.
"An approach to parallelizing isotonic regression."
Applied Mathematics and Parallel Computing. Physica-Verlag HD, 1996. 141-147.
Available from <code>http://softlib.rice.edu/pub/CRPC-TRs/reports/CRPC-TR96640.pdf</code>
<p></div>
<dl><dt><span class="strong">See Also:</span></dt><dd><a href="http://en.wikipedia.org/wiki/Isotonic_regression Isotonic regression (Wikipedia)"/>,
<a href="../../../../../serialized-form.html#org.apache.spark.mllib.regression.IsotonicRegression">Serialized Form</a></dd></dl>
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<td class="colOne"><code><strong><a href="../../../../../org/apache/spark/mllib/regression/IsotonicRegression.html#IsotonicRegression()">IsotonicRegression</a></strong>()</code>
<div class="block">Constructs IsotonicRegression instance with default parameter isotonic = true.</div>
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<td class="colFirst"><code><a href="../../../../../org/apache/spark/mllib/regression/IsotonicRegressionModel.html" title="class in org.apache.spark.mllib.regression">IsotonicRegressionModel</a></code></td>
<td class="colLast"><code><strong><a href="../../../../../org/apache/spark/mllib/regression/IsotonicRegression.html#run(org.apache.spark.api.java.JavaRDD)">run</a></strong>(<a href="../../../../../org/apache/spark/api/java/JavaRDD.html" title="class in org.apache.spark.api.java">JavaRDD</a><scala.Tuple3<java.lang.Double,java.lang.Double,java.lang.Double>> input)</code>
<div class="block">Run pool adjacent violators algorithm to obtain isotonic regression model.</div>
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<td class="colFirst"><code><a href="../../../../../org/apache/spark/mllib/regression/IsotonicRegressionModel.html" title="class in org.apache.spark.mllib.regression">IsotonicRegressionModel</a></code></td>
<td class="colLast"><code><strong><a href="../../../../../org/apache/spark/mllib/regression/IsotonicRegression.html#run(org.apache.spark.rdd.RDD)">run</a></strong>(<a href="../../../../../org/apache/spark/rdd/RDD.html" title="class in org.apache.spark.rdd">RDD</a><scala.Tuple3<java.lang.Object,java.lang.Object,java.lang.Object>> input)</code>
<div class="block">Run IsotonicRegression algorithm to obtain isotonic regression model.</div>
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<td class="colFirst"><code><a href="../../../../../org/apache/spark/mllib/regression/IsotonicRegression.html" title="class in org.apache.spark.mllib.regression">IsotonicRegression</a></code></td>
<td class="colLast"><code><strong><a href="../../../../../org/apache/spark/mllib/regression/IsotonicRegression.html#setIsotonic(boolean)">setIsotonic</a></strong>(boolean isotonic)</code>
<div class="block">Sets the isotonic parameter.</div>
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<h4>IsotonicRegression</h4>
<pre>public IsotonicRegression()</pre>
<div class="block">Constructs IsotonicRegression instance with default parameter isotonic = true.
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<h4>setIsotonic</h4>
<pre>public <a href="../../../../../org/apache/spark/mllib/regression/IsotonicRegression.html" title="class in org.apache.spark.mllib.regression">IsotonicRegression</a> setIsotonic(boolean isotonic)</pre>
<div class="block">Sets the isotonic parameter.
<p></div>
<dl><dt><span class="strong">Parameters:</span></dt><dd><code>isotonic</code> - Isotonic (increasing) or antitonic (decreasing) sequence.</dd>
<dt><span class="strong">Returns:</span></dt><dd>This instance of IsotonicRegression.</dd></dl>
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<pre>public <a href="../../../../../org/apache/spark/mllib/regression/IsotonicRegressionModel.html" title="class in org.apache.spark.mllib.regression">IsotonicRegressionModel</a> run(<a href="../../../../../org/apache/spark/rdd/RDD.html" title="class in org.apache.spark.rdd">RDD</a><scala.Tuple3<java.lang.Object,java.lang.Object,java.lang.Object>> input)</pre>
<div class="block">Run IsotonicRegression algorithm to obtain isotonic regression model.
<p></div>
<dl><dt><span class="strong">Parameters:</span></dt><dd><code>input</code> - RDD of tuples (label, feature, weight) where label is dependent variable
for which we calculate isotonic regression, feature is independent variable
and weight represents number of measures with default 1.
If multiple labels share the same feature value then they are ordered before
the algorithm is executed.</dd>
<dt><span class="strong">Returns:</span></dt><dd>Isotonic regression model.</dd></dl>
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<pre>public <a href="../../../../../org/apache/spark/mllib/regression/IsotonicRegressionModel.html" title="class in org.apache.spark.mllib.regression">IsotonicRegressionModel</a> run(<a href="../../../../../org/apache/spark/api/java/JavaRDD.html" title="class in org.apache.spark.api.java">JavaRDD</a><scala.Tuple3<java.lang.Double,java.lang.Double,java.lang.Double>> input)</pre>
<div class="block">Run pool adjacent violators algorithm to obtain isotonic regression model.
<p></div>
<dl><dt><span class="strong">Parameters:</span></dt><dd><code>input</code> - JavaRDD of tuples (label, feature, weight) where label is dependent variable
for which we calculate isotonic regression, feature is independent variable
and weight represents number of measures with default 1.
If multiple labels share the same feature value then they are ordered before
the algorithm is executed.</dd>
<dt><span class="strong">Returns:</span></dt><dd>Isotonic regression model.</dd></dl>
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