STK_MixtureSemiLearner.h

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/*--------------------------------------------------------------------*/
/*     Copyright (C) 2004-2016  Serge Iovleff
 
    This program is free software; you can redistribute it and/or modify
    it under the terms of the GNU Lesser General Public License as
    published by the Free Software Foundation; either version 2 of the
    License, or (at your option) any later version.
 
    This program 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 Lesser General Public License for more details.
 
    You should have received a copy of the GNU Lesser General Public
    License along with this program; if not, write to the
    Free Software Foundation, Inc.,
    59 Temple Place,
    Suite 330,
    Boston, MA 02111-1307
    USA
 
    Contact : S..._Dot_I..._At_stkpp_Dot_org (see copyright for ...)
*/
 
/*
 * Project:  stkpp::Clustering
 * Author:   iovleff, S..._Dot_I..._At_stkpp_Dot_org (see copyright for ...)
 **/
 
#ifndef STK_MIXTURESEMILEARNER_H
#define STK_MIXTURESEMILEARNER_H
 
#include "STK_MixtureComposer.h"
 
namespace STK
{
 
class MixtureSemiLearner: public MixtureComposer
{
  public:
    MixtureSemiLearner( int nbSample, int nbCluster);
    MixtureSemiLearner( MixtureSemiLearner const& model);
    virtual ~MixtureSemiLearner();
    virtual MixtureSemiLearner* create() const;
    virtual MixtureSemiLearner* clone() const;
    std::vector<int> const& knownLabels() const { return knownLabels_;}
    std::vector<int> const& unknownLabels() const { return unknownLabels_;}
    virtual int cStep();
    virtual int sStep();
    virtual Real eStep();
    virtual void mapStep();
 
    template<class RowVector>
    void setLabels( ExprBase<RowVector> const& zi);
 
  protected:
    virtual void initializeMixtureParameters();
    virtual int randomTik();
    virtual int randomZi();
    void createSemiLearner(MixtureSemiLearner const* const p_learner);
    std::vector<int> knownLabels_;
    std::vector<int> unknownLabels_;
};
 
 
template<class RowVector>
void MixtureSemiLearner::setLabels( ExprBase<RowVector> const& zi)
{
  if (nbSample() != zi.size())
  { STKRUNTIME_ERROR_NO_ARG(MixtureSemiLearner::setKnownLabels,zi must be of size nbSample);}
  int nbUnknown = zi.isNA().count();
#ifdef STK_MIXTURE_DEBUG
  stk_cout << _T("Entering MixtureSemiLearner::setLabels()\n");
  stk_cout << _T("nbUnknown=") << nbUnknown << _T("\n");
#endif
  // clear previous initialization
  unknownLabels_.clear();
  knownLabels_.clear();
  zi_= baseIdx;
  // reserve and set lables
  unknownLabels_.reserve(nbUnknown);
  knownLabels_.reserve(nbSample() - nbUnknown);
  for (int i=zi.begin(); i < zi.end(); ++i)
  {
    if (isNA(zi[i]))
    { unknownLabels_.push_back(i);}
    else
    {
      knownLabels_.push_back(i); zi_[i] = zi[i];
      tik_.row(i) = 0; tik_(i, zi_[i]) = 1.;
    }
  }
#ifdef STK_MIXTURE_DEBUG
  stk_cout << _T("Terminating MixtureSemiLearner::setLabels()\n");
  stk_cout << _T("unknownLabels_.size()=") << unknownLabels_.size() << _T("\n");
  stk_cout << _T("knownLabels_.size()=") << knownLabels_.size() << _T("\n");
#endif
}
 
class MixtureSemiLearnerFixedProp: public MixtureSemiLearner
{
  public:
    MixtureSemiLearnerFixedProp( int nbSample, int nbCluster);
    MixtureSemiLearnerFixedProp( MixtureSemiLearnerFixedProp const& model);
    inline virtual ~MixtureSemiLearnerFixedProp() {}
    virtual MixtureSemiLearnerFixedProp* create() const;
    virtual MixtureSemiLearnerFixedProp* clone() const;
    virtual void pStep();
};
 
 
} // namespace STK
 
#endif /* STK_MIXTURESEMILEARNER_H */