cc.mallet.types
Class GainRatio

java.lang.Object
  cc.mallet.types.SparseVector
      cc.mallet.types.FeatureVector
          cc.mallet.types.RankedFeatureVector
              cc.mallet.types.GainRatio

All Implemented Interfaces:

AlphabetCarrying, ConstantMatrix, Vector, java.io.Serializable

public class GainRatio
extends RankedFeatureVector

List of features along with their thresholds sorted in descending order of the ratio of (1) information gained by splitting instances on the feature at its associated threshold value, to (2) the split information.

The calculations performed do not take into consideration the instance weights.

To create an instance of GainRatio from an InstanceList, one must do the following:

InstanceList ilist = ... ... GainRatio gr = GainRatio.createGainRatio(ilist);

J. R. Quinlan "Improved Use of Continuous Attributes in C4.5" ftp://ftp.cs.cmu.edu/project/jair/volume4/quinlan96a.ps

Author:

Gary Huang ghuang@cs.umass.edu

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from class cc.mallet.types.RankedFeatureVector

RankedFeatureVector.Factory, RankedFeatureVector.PerLabelFactory

Field Summary

static double

log2

Fields inherited from class cc.mallet.types.SparseVector

hasInfinite, indices, values

Constructor Summary

protected

GainRatio(Alphabet dataAlphabet, double[] gainRatios, double[] splitPoints, double baseEntropy, LabelVector baseLabelDistribution, int numSplitPointsForBestFeature, int minNumInsts)

Method Summary

protected static java.lang.Object[]	calcGainRatios(InstanceList ilist, int[] instIndices, int minNumInsts) Calculates gain ratios for all (feature, split point) pairs snd returns array of:
static GainRatio	createGainRatio(InstanceList ilist) Constructs a GainRatio object.
static GainRatio	createGainRatio(InstanceList ilist, int[] instIndices, int minNumInsts) Constructs a GainRatio object
double	getBaseEntropy()
LabelVector	getBaseLabelDistribution()
double	getMaxValuedThreshold()
int	getNumSplitPointsForBestFeature()
double	getThresholdAtRank(int rank)
static int[]	sortInstances(InstanceList ilist, int[] instIndices, int featureIndex)

Methods inherited from class cc.mallet.types.RankedFeatureVector

getIndexAtRank, getMaxValue, getMaxValuedIndex, getMaxValuedIndexIn, getMaxValuedObject, getMaxValuedObjectIn, getMaxValueIn, getObjectAtRank, getRank, getRank, getValueAtRank, printByRank, printByRank, printLowerK, printTopK, set, setRankOrder, setRankOrder, setRankOrder, setReverseRankOrder

Methods inherited from class cc.mallet.types.FeatureVector

alphabetsMatch, cloneMatrix, cloneMatrixZeroed, contains, getAlphabet, getAlphabets, getObjectIndices, location, newFeatureVector, toSimpFile, toString, toString, value

Methods inherited from class cc.mallet.types.SparseVector

absNorm, addTo, addTo, arrayCopyFrom, arrayCopyFrom, arrayCopyInto, dotProduct, dotProduct, dotProduct, dotProduct, extendedDotProduct, extendedDotProduct, getDimensions, getIndices, getNumDimensions, getValues, incrementValue, indexAtLocation, infinityNorm, isBinary, isInfinite, isNaN, isNaNOrInfinite, location, makeBinary, makeNonBinary, map, numLocations, oneNorm, plusEqualsSparse, plusEqualsSparse, print, removeDuplicates, setAll, setValue, setValueAtLocation, singleIndex, singleSize, singleToIndices, singleValue, sortIndices, timesEquals, timesEqualsSparse, timesEqualsSparse, timesEqualsSparseZero, twoNorm, value, value, valueAtLocation, vectorAdd

Methods inherited from class java.lang.Object

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

Field Detail

log2

public static final double log2

Constructor Detail

GainRatio

protected GainRatio(Alphabet dataAlphabet,
                    double[] gainRatios,
                    double[] splitPoints,
                    double baseEntropy,
                    LabelVector baseLabelDistribution,
                    int numSplitPointsForBestFeature,
                    int minNumInsts)

Method Detail

calcGainRatios

protected static java.lang.Object[] calcGainRatios(InstanceList ilist,
                                                   int[] instIndices,
                                                   int minNumInsts)

Calculates gain ratios for all (feature, split point) pairs snd returns array of:

   1.  gain ratios (each element is the max gain ratio of a feature 
 for those split points with at least average gain)
   2.  the optimal split point for each feature
   3.  the overall entropy 
   4.  the overall label distribution of the given instances
   5.  the number of split points of the split feature.
   

sortInstances

public static int[] sortInstances(InstanceList ilist,
                                  int[] instIndices,
                                  int featureIndex)

createGainRatio

public static GainRatio createGainRatio(InstanceList ilist)

Constructs a GainRatio object.

createGainRatio

public static GainRatio createGainRatio(InstanceList ilist,
                                        int[] instIndices,
                                        int minNumInsts)

Constructs a GainRatio object

getMaxValuedThreshold

public double getMaxValuedThreshold()

Returns:

the threshold of the (feature, threshold) pair with with maximum gain ratio

getThresholdAtRank

public double getThresholdAtRank(int rank)

Returns:

the threshold of the (feature, threshold) pair with the given rank

getBaseEntropy

public double getBaseEntropy()

getBaseLabelDistribution

public LabelVector getBaseLabelDistribution()

getNumSplitPointsForBestFeature

public int getNumSplitPointsForBestFeature()