Information gain normalized by the sum of the classification and split entropies see formula (11) in [Wehenkel1991] and appendix A in [Geurts2006]. More...
#include <score.h>
Static Public Member Functions | |
template<class W > | |
__host__ static __device__ ScoreType | calculateScore (const size_t numClasses, 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 | splitEntropy (const ScoreType total, const ScoreType totalLeft, const ScoreType totalRight) |
template<class W > | |
__host__ static __device__ ScoreType | classificationEntropy (const size_t numLabels, const W *allClasses, const ScoreType total) |
Static Protected Member Functions inherited from curfil::InformationGainScore | |
__host__ static __device__ ScoreType | entropy (const ScoreType prob) |
__host__ static __device__ ScoreType | normalizeScore (const ScoreType score) |
Information gain normalized by the sum of the classification and split entropies see formula (11) in [Wehenkel1991] and appendix A in [Geurts2006].
|
inlinestatic |
Reimplemented from curfil::InformationGainScore.
|
inlinestaticprotected |
|
inlinestaticprotected |