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ClassifierEvaluator.h

Go to the documentation of this file.

#ifndef Impala_Core_Training_ClassifierEvaluator_h
#define Impala_Core_Training_ClassifierEvaluator_h

#include "Core/Table/Select.h"
#include "Core/Training/ParameterEvaluator.h"
#include "Core/Training/Svm.h"
#include "Core/Training/Evaluation.h"
#include "Core/Training/TrainDataSrc.h"

namespace Impala
{
namespace Core
{
namespace Training
{

class ClassifierEvaluator : public ParameterEvaluator
{
public:
    typedef Table::AnnotationTable AnnotationTable;

    ClassifierEvaluator(Classifier* classifier, TrainDataSrc* src,
                        Evaluation* evaluator)
    {
        mClassifier = classifier;
        mDataSrc = src;
        mEvaluator = evaluator;
    }

    virtual
    ~ClassifierEvaluator()
    {
        delete mClassifier;
        delete mDataSrc;
        delete mEvaluator;
    }

    void
    SetRepetition(int repetition, int total)
    {
        ILOG_DEBUG_NODE("set repetition: "<< repetition);
        mRepetition = repetition;
    }

    void
    SetFold(int fold, int total)
    {
        ILOG_DEBUG_NODE("set fold: "<< fold << ", "<< total);
        mFold = fold;
        mFoldCount = total;
    }

    virtual double
    Evaluate(Util::PropertySet* parameters)
    {
        bool episode = parameters->GetBool("episode-constrained");
        ILOG_DEBUG_NODE("calling TrainDataSrc::FilterTrainFold");
        mDataSrc->FilterTrainFold(mFold, mFoldCount, mRepetition, episode);
        ILOG_DEBUG_NODE("calling Classifier::Train, data size = "
                        << mDataSrc->Size());
        mClassifier->Train(parameters, mDataSrc);
        ILOG_DEBUG_NODE("calling TrainDataSrc::FilterTestFold");
        mDataSrc->FilterTestFold(mFold, mFoldCount, mRepetition, episode);
        ILOG_DEBUG_NODE("calling Classifier::Predict, data size = "
                        << mDataSrc->Size());
        Table::ScoreTable* ranking = mClassifier->Predict(mDataSrc);
        ILOG_DEBUG_NODE("calling Evaluation::Compute");
        double score = mEvaluator->Compute(ranking);
        delete ranking;
        return score;
    }

private:
    int mRepetition;
    int mFold;
    int mFoldCount;
    Evaluation* mEvaluator;
    Classifier* mClassifier;
    TrainDataSrc* mDataSrc;
    ILOG_VAR_DEC;
};

ILOG_VAR_INIT(ClassifierEvaluator, Impala.Core.Training);

}//namespace
}//namespace
}//namespace

#endif

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