STK::SemiSEMPredict Class Reference

Implementation of the SemiSEMPredict algorithm. More...

#include <STK_MixtureAlgoPredict.h>

Inheritance diagram for STK::SemiSEMPredict:

Public Member Functions
	SemiSEMPredict ()
	default constructor
	SemiSEMPredict (SemiSEMPredict const &algo)
	Copy constructor.
virtual	~SemiSEMPredict ()
	destructor
virtual SemiSEMPredict *	clone () const
	clone pattern
virtual bool	run ()
	run the algorithm on the model until the maximal number of iteration is reached.
Public Member Functions inherited from STK::IMixtureAlgoPredict
virtual	~IMixtureAlgoPredict ()
	destructor
int	nbIterBurn () const
int	setNbIterLong () const
int	epsilon () const
void	setModel (IMixtureComposer *p_model)
	set model
void	setNbIterBurn (int nbIterBurn)
	set number of burning iterations
void	setNbIterLong (int nbIterLong)
	set number of long iterations
void	setEpsilon (Real epsilon)
	set tolerance value
Public Member Functions inherited from STK::IRunnerBase
String const &	error () const
	get the last error message.

Additional Inherited Members
Protected Member Functions inherited from STK::IMixtureAlgoPredict
	IMixtureAlgoPredict ()
	default constructor
	IMixtureAlgoPredict (IMixtureAlgoPredict const &algo)
	Copy constructor.
bool	predictBayesClassifier ()
	predict class labels when there is no missing values.
bool	burnStep ()
	Perform burn step using SEM algorithm.
Protected Member Functions inherited from STK::IRunnerBase
	IRunnerBase ()
	default constructor
	IRunnerBase (IRunnerBase const &runner)
	copy constructor
virtual	~IRunnerBase ()
	destructor
virtual void	update ()
	update the runner.
Protected Attributes inherited from STK::IMixtureAlgoPredict
IMixtureComposer *	p_model_
	pointer on the mixture model
int	nbIterBurn_
	Number of burning iterations of the algorithm.
int	nbIterLong_
	maximal number of iterations of the algorithm
Real	epsilon_
	tolerance of the algorithm.
Protected Attributes inherited from STK::IRunnerBase
String	msg_error_
	String with the last error message.
bool	hasRun_
	true if run has been used, false otherwise

Detailed Description

Implementation of the SemiSEMPredict algorithm.

SemiSEMPredict algorithm starts calling an initializationStep and then calls until the number of iteration is reached steps:

• samplingStep()
• eStep()
• storeIntermediateResults(iter). It ends by a call to setParameterStep(). This is the counterpart of SemiSEMSAlgo for prediction.

Definition at line 81 of file STK_MixtureAlgoPredict.h.

Constructor & Destructor Documentation

SemiSEMPredict() [1/2]

STK::SemiSEMPredict::SemiSEMPredict ( )

inline

default constructor

Definition at line 85 of file STK_MixtureAlgoPredict.h.

: IMixtureAlgoPredict() {}

Referenced by clone().

SemiSEMPredict() [2/2]

STK::SemiSEMPredict::SemiSEMPredict ( SemiSEMPredict const &  algo )

inline

Copy constructor.

Parameters

algo	the algorithm to copy

Definition at line 88 of file STK_MixtureAlgoPredict.h.

: IMixtureAlgoPredict(algo) {}

~SemiSEMPredict()

virtual STK::SemiSEMPredict::~SemiSEMPredict ( )

inlinevirtual

destructor

Definition at line 90 of file STK_MixtureAlgoPredict.h.

{}

Member Function Documentation

clone()

virtual SemiSEMPredict * STK::SemiSEMPredict::clone ( ) const

inlinevirtual

clone pattern

Definition at line 92 of file STK_MixtureAlgoPredict.h.

{ return new SemiSEMPredict(*this);}

References SemiSEMPredict().

run()

bool STK::SemiSEMPredict::run ( )

virtual

run the algorithm on the model until the maximal number of iteration is reached.

Returns

true if no error occur, false otherwise.

Implements STK::IRunnerBase.

Definition at line 114 of file STK_MixtureAlgoPredict.cpp.

{
  if (p_model_->computeNbMissingValues() == 0)
  { return predictBayesClassifier();}
 
#ifdef STK_MIXTURE_VERY_VERBOSE
  stk_cout << _T("------------------------------------\n");
  stk_cout << _T("Entering SemiSEMPredict::run() with:\n");
  stk_cout << _T("nbIterBurn_ = ") << nbIterBurn_ << _T("\n")
           << _T("nbIterLong_ = ") << nbIterLong_
           << _T("p_model_->lnLikelihood = ") << p_model_->lnLikelihood() << _T("\n");
#endif
  try
  {
    p_model_->initializeStep();
    if (!burnStep())
    {
      p_model_->mapStep();
      p_model_->finalizeStep();
      return false;
    }
    int iter;
    for (iter = 0; iter < nbIterLong_; ++iter)
    {
      p_model_->samplingStep();
      p_model_->eStep();
      p_model_->storeIntermediateResults(iter+1); // store current parameters
    }
  }
  catch (Clust::exceptions const& error)
  {
    msg_error_ = Clust::exceptionToString(error);
#ifdef STK_MIXTURE_VERBOSE
  stk_cout << _T("An exception occur in SemiSEMPredict::run(): ") << msg_error_ << _T("\n");
#endif
    p_model_->setParametersStep();
    p_model_->mapStep();
    p_model_->finalizeStep();
    return false;
  }
  catch (Exception const& error)
  {
    msg_error_ = error.error();
#ifdef STK_MIXTURE_VERBOSE
    stk_cout << _T("An error occur in SemiSEMPredict::run():\n") << msg_error_ << _T("\n");
#endif
    p_model_->setParametersStep();
    p_model_->mapStep();
    p_model_->finalizeStep();
    return false;
  }
#ifdef STK_MIXTURE_VERBOSE
    stk_cout << _T("In SemiSEMPredict::run() iterations terminated.\n")
             << _T("p_model_->lnLikelihood = ") << p_model_->lnLikelihood() << _T("\n");
#endif
  // set averaged parameters
  p_model_->setParametersStep();
  p_model_->mapStep();
  p_model_->finalizeStep();
#ifdef STK_MIXTURE_VERY_VERBOSE
  stk_cout << _T("Terminating SemiSEMPredict::run()\n");
  stk_cout << _T("---------------------------------\n");
#endif
  return true;
}

References _T, STK::IMixtureAlgoPredict::burnStep(), STK::IMixtureStatModel::computeNbMissingValues(), STK::IRunnerBase::error(), STK::IMixtureComposer::eStep(), STK::Clust::exceptionToString(), STK::IMixtureComposer::finalizeStep(), STK::IMixtureComposer::initializeStep(), STK::IStatModelBase::lnLikelihood(), STK::IMixtureComposer::mapStep(), STK::IRunnerBase::msg_error_, STK::IMixtureAlgoPredict::nbIterBurn_, STK::IMixtureAlgoPredict::nbIterLong_, STK::IMixtureAlgoPredict::p_model_, STK::IMixtureAlgoPredict::predictBayesClassifier(), STK::IMixtureStatModel::samplingStep(), STK::IMixtureStatModel::setParametersStep(), stk_cout, and STK::IMixtureStatModel::storeIntermediateResults().

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The documentation for this class was generated from the following files:

• STK_MixtureAlgoPredict.h
• STK_MixtureAlgoPredict.cpp