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// Copyright (C) 2002 Ronan Collobert (collober@iro.umontreal.ca)
//
//
// This file is part of Torch. Release II.
// [The Ultimate Machine Learning Library]
//
// Torch is free software; you can redistribute it and/or modify
// it under the terms of the GNU General Public License as published by
// the Free Software Foundation; either version 2 of the License, or
// (at your option) any later version.
//
// Torch is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU General Public License
// along with Torch; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
#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.
@author Ronan Collobert (collober@iro.umontreal.ca)
*/
class WeightedMseCriterion : public Criterion
{
public:
/** 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;
bool weights_is_allocated;
//-----
/** 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 allocateMemory();
virtual void freeMemory();
virtual void forward(List *inputs);
virtual void backward(List *inputs, real *alpha);
virtual ~WeightedMseCriterion();
};
}
#endif
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