classmeasurer.h

强化学习算法（R-Learning）难得的珍贵资料

// Copyright (C) 2003 Ronan Collobert ([e-mail])
//                
// This file is part of Torch 3.
//
// All rights reserved.
// 
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions
// are met:
// 1. Redistributions of source code must retain the above copyright
//    notice, this list of conditions and the following disclaimer.
// 2. Redistributions in binary form must reproduce the above copyright
//    notice, this list of conditions and the following disclaimer in the
//    documentation and/or other materials provided with the distribution.
// 3. The name of the author may not be used to endorse or promote products
//    derived from this software without specific prior written permission.
// 
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// NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
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#ifndef CLASS_MEASURER_INC
#define CLASS_MEASURER_INC

#include "Measurer.h"
#include "ClassFormat.h"

namespace Torch {

/** Compute the classification error (in %)
    of the #inputs# with respect to the #targets# of #data#.

    The format of the class is given with a #ClassFormat#.
    It can print the confusion matrix if specified.

    @author Ronan Collobert ([e-mail])
*/
class ClassMeasurer : public Measurer
{
  public:
    real internal_error;
    int **confusion;
    Sequence *inputs;
    ClassFormat *class_format;
    bool calc_confusion;
    bool calc_confusion_at_each_iter;
    int n_classes;

    //-----

    ///
    ClassMeasurer(Sequence *inputs_, DataSet *data_, ClassFormat *class_format_, XFile *file_,
                  bool calc_confusion_=false, bool calc_confusion_at_each_iter_=false);

    //-----

    void printConfusionMatrix();
    virtual void reset();
    virtual void measureExample();
    virtual void measureIteration();
    virtual void measureEnd();
    void init_();
    void reset_();

    virtual ~ClassMeasurer();
};

}

#endif