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// Copyright (C) 2002 Samy Bengio (bengio@idiap.ch)
//
//
// 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 EMTRAINER_INC
#define EMTRAINER_INC
#include "Trainer.h"
#include "Distribution.h"
#include "SeqDataSet.h"
namespace Torch {
/** This class is used to train any distribution using the EM algorithm.
@author Samy Bengio (bengio@idiap.ch)
*/
class EMTrainer : public Trainer
{
public:
/// the distribution to train
Distribution *distribution;
/// the training set is a SeqDataSet, since we are working with distributions
SeqDataSet *sdata;
/// the stopping criterion regarding the accuracy for EM
real end_accuracy;
/// the stopping criterion regarding the number of iterations for EM
int max_iter;
///
EMTrainer(Distribution *distribution_, SeqDataSet *data_);
virtual void train(List *measurers);
virtual void test(List *measurers);
/** this method computes the most likely path into the distribution.
mainly used for sequential distribution such as HMMs.
*/
virtual void decode(List *measurers);
virtual ~EMTrainer();
};
}
#endif
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