hex.singlenoderf

Class TwoingStatistic

java.lang.Object

hex.singlenoderf.TwoingStatistic

public class TwoingStatistic
extends java.lang.Object

Computes the twoing split statistic. The decrease in (twoing) impurity as the result of a given split is computed as follows: 1 weight left weight right - * ------------ * ------------- * twoing( left, right ) 4 weight total weight total twoing( left, right ) = (\sum(|p_i(left) - p_i(right)|)^2, where p_i( left ) is the fraction of observations in the left node of class i p_i( right ) is the fraction of observations in the right node of class i The split that produces the largest decrease in impurity is selected. Same is done for exclusions, where again left stands for the rows with column value equal to the split value and right for all different ones. ece 11/14

Field Summary

Fields

Modifier and Type	Field and Description
protected int[][][]	_columnDists Column distributions: column x arity x classes Remembers the number of rows of the given column index, encodedValue, class.
protected int[][][]	_columnDistsRegression
protected int[]	_features
protected java.util.Random	_random

Constructor Summary

Constructors

Constructor and Description
TwoingStatistic(Data data, int features, long seed, int exclusiveSplitLimit)

Method Summary

Methods

Modifier and Type	Method and Description
protected hex.singlenoderf.Statistic.Split	eqSplit(int colIndex, Data d, float[] dist, float distWeight, java.util.Random rand)
protected hex.singlenoderf.Statistic.Split	eqSplit(int colIndex, Data d, int[] dist, int distWeight, java.util.Random _)
protected hex.singlenoderf.Statistic.Split	ltSplit(int colIndex, Data d, float[] dist, float distWeight, java.util.Random rand)
protected hex.singlenoderf.Statistic.Split	ltSplit(int col, Data d, int[] dist, int distWeight, java.util.Random _) Returns the best split for a given column

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

_columnDists

protected final int[][][] _columnDists

Column distributions: column x arity x classes Remembers the number of rows of the given column index, encodedValue, class.

_features

protected final int[] _features

_random

protected java.util.Random _random

_columnDistsRegression

protected final int[][][] _columnDistsRegression

Constructor Detail

TwoingStatistic

public TwoingStatistic(Data data,
               int features,
               long seed,
               int exclusiveSplitLimit)

Method Detail

ltSplit

protected hex.singlenoderf.Statistic.Split ltSplit(int col,
                                       Data d,
                                       int[] dist,
                                       int distWeight,
                                       java.util.Random _)

Returns the best split for a given column

eqSplit

protected hex.singlenoderf.Statistic.Split eqSplit(int colIndex,
                                       Data d,
                                       int[] dist,
                                       int distWeight,
                                       java.util.Random _)

ltSplit

protected hex.singlenoderf.Statistic.Split ltSplit(int colIndex,
                                       Data d,
                                       float[] dist,
                                       float distWeight,
                                       java.util.Random rand)

eqSplit

protected hex.singlenoderf.Statistic.Split eqSplit(int colIndex,
                                       Data d,
                                       float[] dist,
                                       float distWeight,
                                       java.util.Random rand)