weightedmsecriterion.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.
// 
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// modification, are permitted provided that the following conditions
// are met:
// 1. Redistributions of source code must retain the above copyright
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// 2. Redistributions in binary form must reproduce the above copyright
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#ifndef WEIGHTED_MSE_CRITERION_INC
#define WEIGHTED_MSE_CRITERION_INC

#include "Criterion.h"

namespace Torch {

/** Similar to #MSECriterion#, but you
    can put a weight on each example.

    Options:
    \begin{tabular}{lcll}
      "average frame size"  &  bool  &  divided by the frame size & [true]
    \end{tabular}

    @author Ronan Collobert ([e-mail])
*/
class WeightedMSECriterion : public Criterion
{
  public:
    bool average_frame_size;

    /** Pointer on the weights.
        You can modify the weights when you want.
        
        The length of #weights# \emph{is} the
        #n_real_examples# of #data#.
    */
    real *weights;

    //-----

    /** With this constructor, the weights are allocated
        and initializated to 1.
    */
    WeightedMSECriterion(DataSet *data_);

    /** With this constructor, you provide the #weights#.

       The length of #weights# \emph{must be} the
       #n_real_examples# of #data#.       
    */
    WeightedMSECriterion(DataSet *data_, real *weights_);

    //-----

    virtual void setDataSet(DataSet *data_);
    virtual void frameForward(int t, real *f_inputs, real *f_outputs);
    virtual void frameBackward(int t, real *f_inputs, real *beta_, real *f_outputs, real *alpha_);

    virtual ~WeightedMSECriterion();
};

}

#endif