org.apache.spark.streamdm.classifiers.trees

SplitCriterion

trait SplitCriterion extends Serializable

Trait for computing splitting criteria with respect to distributions of class values. The split criterion is used as a parameter on decision trees and decision stumps. The two split criteria most used are Information Gain and Gini.

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GiniSplitCriterion, InfoGainSplitCriterion, VarianceReductionSplitCriterion
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  1. abstract def merit(pre: Array[Double], post: Array[Array[Double]]): Double

    Computes the merit of splitting for a given distribution before and after the split.

    Computes the merit of splitting for a given distribution before and after the split.

    pre

    the class distribution before the split

    post

    the class distribution after the split

    returns

    value of the merit of splitting

  2. abstract def rangeMerit(pre: Array[Double]): Double

    Computes the range of splitting merit

    Computes the range of splitting merit

    pre

    the class distribution before the split

    returns

    value of the range of splitting merit

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