?? maphmm.h
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// Copyright (C) 2003 Johnny Mariethoz (marietho@idiap.ch)
// and Samy Bengio (bengio@idiap.ch)
//
// 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.
//
// THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR
// IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
// OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
// IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT,
// INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT
// NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
// DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
// THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
// (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF
// THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#ifndef MAP_HMM_INC
#define MAP_HMM_INC
#include "HMM.h"
namespace Torch {
/** This class is a special case of a HMM that implements the
MAP algorithm for HMM transitions probabilities.
@author Samy Bengio (bengio@idiap.ch)
@author Johnny Mariethoz (marietho@idiap.ch)
*/
class MAPHMM : public HMM
{
public:
/// The prior distribution used in MAP
HMM* prior_distribution;
/// The weight to give to the prior parameters during update
real weight_on_prior;
///log(weight_on_prior)
real log_weight_on_prior;
///log(1-weight_on_prior_
real log_1_weight_on_prior;
///
MAPHMM(int n_states_, Distribution **states_, real** transitions_, HMM* prior_distribution_);
void setWeightOnPrior(real weight_on_prior_);
/// map adaptation method for transitions probabilities
virtual void eMUpdate();
virtual ~MAPHMM();
};
}
#endif
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