curfil::InformationGainScore Class Reference

Information Gain calculation using Shannon entropy of the parent and child nodes. More...

#include <score.h>

Inheritance diagram for curfil::InformationGainScore:

Static Public Member Functions
template<class W >
__host__ static __device__ ScoreType	calculateScore (const size_t numLabels, const W *leftClasses, const W *rightClasses, const unsigned int leftRightStride, const W *allClasses, const ScoreType totalLeft, const ScoreType totalRight)

Static Protected Member Functions
__host__ static __device__ ScoreType	entropy (const ScoreType prob)
__host__ static __device__ ScoreType	normalizeScore (const ScoreType score)

Detailed Description

Information Gain calculation using Shannon entropy of the parent and child nodes.

Definition at line 18 of file score.h.

Member Function Documentation

template<class W >

__host__ static __device__ ScoreType curfil::InformationGainScore::calculateScore ( const size_t  numLabels, const W *  leftClasses, const W *  rightClasses, const unsigned int  leftRightStride, const W *  allClasses, const ScoreType  totalLeft, const ScoreType  totalRight  )

inlinestatic

Returns

normalized score calculated after splitting

Reimplemented in curfil::NormalizedInformationGainScore.

Definition at line 62 of file score.h.

__host__ static __device__ ScoreType curfil::InformationGainScore::entropy ( const ScoreType  prob )

inlinestaticprotected

Returns

entropy calculated using the given probability

Definition at line 26 of file score.h.

__host__ static __device__ ScoreType curfil::InformationGainScore::normalizeScore ( const ScoreType  score )

inlinestaticprotected

Returns

score in the interval [0,1]

Definition at line 37 of file score.h.

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The documentation for this class was generated from the following file:

• src/curfil/score.h