NICE_VisLearning/classifier/fpclassifier/randomforest/SplittingCriterion.cpp

/**
 * @file SplittingCriterion.cpp
 * @brief abstract interface for splitting criteria
 * @author Sven Sickert
 * @date 01/12/2017

*/
#include "SplittingCriterion.h"

using namespace OBJREC;

/* default constructor */
SplittingCriterion::SplittingCriterion()
{
    min_examples = 50;
    entropy_cur = 0.0;
    min_entropy = 10e-5;
    min_purity = 10e-7;
}

/* simple constructor */
SplittingCriterion::SplittingCriterion( int _min_examples )
{
    min_examples = _min_examples;
    entropy_cur = 0.0;
    min_entropy = 10e-5;
    min_purity = 10e-7;
}

/* config constructor */
SplittingCriterion::SplittingCriterion( const NICE::Config *conf )
{
    min_examples = conf->gI ( "SplittingCriterion", "min_examples", 50 );
    min_entropy = conf->gD ( "SplittingCriterion", "min_entropy", 10e-5 );
    min_purity = conf->gD ( "SplittingCriterion", "min_purity", 10e-7 );
    entropy_cur = 0.0;
}

/* copy constructor */
SplittingCriterion::SplittingCriterion( const SplittingCriterion &obj )
{
    min_examples = obj.min_examples;
    min_entropy = obj.min_entropy;
    min_purity = obj.min_purity;
    entropy_cur = obj.entropy_cur;
}

/* default destructor */
SplittingCriterion::~SplittingCriterion()
{
}

/* computation of entropy */
double SplittingCriterion::computeEntropy(
        const double* distribution,
        const double count,
        const int maxClassNo )
{
    double e = 0.0;

    for ( int j = 0 ; j <= maxClassNo ; j++ )
        if ( distribution[j] != 0 )
            e -= distribution[j] * log(distribution[j]);

    e /= count;
    e += log(count);

    return e;
}