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org.apache.spark.examples.mllib

DecisionTreeRunner

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object DecisionTreeRunner

An example runner for decision trees and random forests. Run with

./bin/run-example org.apache.spark.examples.mllib.DecisionTreeRunner [options]

If you use it as a template to create your own app, please use spark-submit to submit your app.

Note: This script treats all features as real-valued (not categorical). To include categorical features, modify categoricalFeaturesInfo.

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  1. case class Params(input: String = null, testInput: String = "", dataFormat: String = "libsvm", algo: Algo = Classification, maxDepth: Int = 5, impurity: ImpurityType = Gini, maxBins: Int = 32, minInstancesPerNode: Int = 1, minInfoGain: Double = 0.0, numTrees: Int = 1, featureSubsetStrategy: String = "auto", fracTest: Double = 0.2, useNodeIdCache: Boolean = false, checkpointDir: Option[String] = None, checkpointInterval: Int = 10) extends AbstractParams[Params] with Product with Serializable

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  4. object ImpurityType extends Enumeration

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