cc.mallet.types
Class ExpGain
- java.lang.Object
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- cc.mallet.types.SparseVector
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- cc.mallet.types.FeatureVector
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- cc.mallet.types.RankedFeatureVector
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- cc.mallet.types.ExpGain
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- All Implemented Interfaces:
- AlphabetCarrying, ConstantMatrix, Vector, java.io.Serializable
public class ExpGain extends RankedFeatureVector
- See Also:
- Serialized Form
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Nested Class Summary
Nested Classes Modifier and Type Class and Description static classExpGain.Factory-
Nested classes/interfaces inherited from class cc.mallet.types.RankedFeatureVector
RankedFeatureVector.PerLabelFactory
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Constructor Summary
Constructors Constructor and Description ExpGain(InstanceList ilist, Classification[] classifications, double gaussianPriorVariance)ExpGain(InstanceList ilist, LabelVector[] classifications, double gaussianPriorVariance)
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Method Summary
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Methods inherited from class cc.mallet.types.RankedFeatureVector
getIndexAtRank, getMaxValue, getMaxValuedIndex, getMaxValuedIndexIn, getMaxValuedObject, getMaxValuedObjectIn, getMaxValueIn, getObjectAtRank, getRank, getRank, getValueAtRank, printByRank, printByRank, printLowerK, printTopK, set
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Methods inherited from class cc.mallet.types.FeatureVector
alphabetsMatch, cloneMatrix, cloneMatrixZeroed, contains, getAlphabet, getAlphabets, getObjectIndices, location, newFeatureVector, toSimpFile, toString, toString, value
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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, setAll, setValue, setValueAtLocation, singleIndex, singleSize, singleToIndices, singleValue, timesEquals, timesEqualsSparse, timesEqualsSparse, timesEqualsSparseZero, twoNorm, value, value, valueAtLocation, vectorAdd
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Constructor Detail
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ExpGain
public ExpGain(InstanceList ilist, LabelVector[] classifications, double gaussianPriorVariance)
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ExpGain
public ExpGain(InstanceList ilist, Classification[] classifications, double gaussianPriorVariance)
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