Github user erikerlandson commented on a diff in the pull request:

    https://github.com/apache/spark/pull/13440#discussion_r104822183
  
    --- Diff: 
mllib/src/main/scala/org/apache/spark/mllib/tree/impurity/Impurity.scala ---
    @@ -50,6 +50,50 @@ trait Impurity extends Serializable {
       @Since("1.0.0")
       @DeveloperApi
       def calculate(count: Double, sum: Double, sumSquares: Double): Double
    +
    +  /**
    +   * :: DeveloperApi ::
    +   * Compute a test-statistic p-value quality measure from left and right 
split populations
    +   * @param calcL impurity calculator for the left split population
    +   * @param calcR impurity calculator for the right split population
    +   * @return The p-value for the null hypothesis; that left and right 
split populations
    +   * represent the same distribution
    +   * @note Unless overridden this method will fail with an exception, for 
backward compatability
    +   */
    +  @Since("2.0.0")
    +  @DeveloperApi
    +  def calculate(calcL: ImpurityCalculator, calcR: ImpurityCalculator): 
Double =
    +    throw new UnsupportedOperationException("Impurity.calculate")
    +
    +  /**
    +   * :: DeveloperApi ::
    +   * Determine if this impurity measure is a test-statistic measure
    +   * @return True if this is a split quality measure based on a test 
statistic (i.e. returns a
    +   * p-value) or false otherwise.
    +   * @note Unless overridden this method returns false by default, for 
backward compatability
    +   */
    +  @Since("2.0.0")
    +  @DeveloperApi
    +  def isTestStatistic: Boolean = false
    +}
    +
    +/**
    + * :: DeveloperApi ::
    + * Utility functions for Impurity measures
    + */
    +@Since("2.0.0")
    +@DeveloperApi
    --- End diff --
    
    I don't think so.  I don't recall any specific motivation to keep it 
private, but historically Spark seems to default things to "minimum 
visibility."   The only method currently defined here is an implementation 
detail for hacking p-values into the existing 'gain' system, where larger is 
assumed to be better.


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