STK::SimulAlgo Class Reference

Implementation of the SimulAlgo learning algorithm. More...

#include <STK_MixtureAlgoLearn.h>

Inheritance diagram for STK::SimulAlgo:

Public Member Functions
	SimulAlgo ()
	default constructor
	SimulAlgo (SimulAlgo const &algo)
	Copy constructor.
virtual	~SimulAlgo ()
	destructor
virtual SimulAlgo *	clone () const
	clone pattern
virtual bool	run ()
	run the algorithm on the model calling sStep, mStep and eStep of the model until the maximal number of iteration is reached.
Public Member Functions inherited from STK::IMixtureAlgoLearn
virtual	~IMixtureAlgoLearn ()
	destructor
int	nbIterMax () const
int	epsilon () const
void	setModel (IMixtureLearner *p_model)
	set model
void	setNbIterMax (int nbIterMax)
	set maximal number of 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::IMixtureAlgoLearn
	IMixtureAlgoLearn ()
	default constructor
	IMixtureAlgoLearn (IMixtureAlgoLearn const &algo)
	Copy constructor.
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::IMixtureAlgoLearn
IMixtureLearner *	p_model_
	pointer on the mixture model
int	nbIterMax_
	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 SimulAlgo learning algorithm.

The SimulAlgo algorithm calls alternatively steps:

• samplingStep()
• paramUpdateStep()
• storeIntermediateResults(iter) until the maximum number of iterations is reached.

Definition at line 79 of file STK_MixtureAlgoLearn.h.

Constructor & Destructor Documentation

SimulAlgo() [1/2]

STK::SimulAlgo::SimulAlgo ( )

inline

default constructor

Definition at line 83 of file STK_MixtureAlgoLearn.h.

: IMixtureAlgoLearn() {}

Referenced by clone().

SimulAlgo() [2/2]

STK::SimulAlgo::SimulAlgo ( SimulAlgo const &  algo )

inline

Copy constructor.

Parameters

algo	the algorithm to copy

Definition at line 86 of file STK_MixtureAlgoLearn.h.

: IMixtureAlgoLearn(algo) {}

~SimulAlgo()

virtual STK::SimulAlgo::~SimulAlgo ( )

inlinevirtual

destructor

Definition at line 88 of file STK_MixtureAlgoLearn.h.

{}

Member Function Documentation

clone()

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

inlinevirtual

clone pattern

Definition at line 90 of file STK_MixtureAlgoLearn.h.

{ return new SimulAlgo(*this);}

References SimulAlgo().

run()

bool STK::SimulAlgo::run ( )

virtual

run the algorithm on the model calling sStep, mStep and eStep of the model until the maximal number of iteration is reached.

Returns

true if no error occur, false otherwise.

Implements STK::IRunnerBase.

Definition at line 93 of file STK_MixtureAlgoLearn.cpp.

{
#ifdef STK_MIXTURE_VERBOSE
  stk_cout << _T("-------------------------------\n");
  stk_cout << _T("Entering SimulAlgo::run() with:\n")
           << _T("nbIterMax_ = ") << nbIterMax_ << _T("\n")
           << _T("p_model_->lnLikelihood = ") << p_model_->lnLikelihood() << _T("\n");
#endif
#ifdef STK_MIXTURE_VERY_VERBOSE
  stk_cout << _T("Parameters of the model\n");
  p_model_->writeParameters(stk_cout);
#endif
  bool result = true;
  try
  {
    int iter;
    for (iter = 0; iter < nbIterMax_; ++iter)
    {
      p_model_->samplingStep(); // simulate missing values
      p_model_->paramUpdateStep(); // estimate parameters
      p_model_->storeIntermediateResults(iter+1); // store current parameters
    }
#ifdef STK_MIXTURE_VERBOSE
    stk_cout << _T("In SimulAlgo::run() iterations terminated.\n")
             << _T("p_model_->lnLikelihood = ") << p_model_->lnLikelihood() << _T("\n");
#endif
#ifdef STK_MIXTURE_VERY_VERBOSE
  stk_cout << _T("Parameters of the model\n");
  p_model_->writeParameters(stk_cout);
#endif
  }
  catch (Clust::exceptions const& error)
  {
    msg_error_ = Clust::exceptionToString(error);
    p_model_->finalizeStep();
#ifdef STK_MIXTURE_VERBOSE
    stk_cout << _T("An error occur in SimulAlgo::run(): ") << msg_error_ << _T("\n");
#endif
    result = false;
  }
  if (result)
  {
    // set averaged parameters
    p_model_->finalizeStep();
    p_model_->mapStep();
#ifdef STK_MIXTURE_VERY_VERBOSE
    stk_cout << _T("\nIn SimulAlgo::run(), setParameters done.\n")
             << _T("p_model_->lnLikelihood = ") << p_model_->lnLikelihood() << _T("\n");
#endif
  }
  else
  { p_model_->releaseIntermediateResults();}
#ifdef STK_MIXTURE_VERY_VERBOSE
  stk_cout << _T("Terminating SimulAlgo::run()\n");
  stk_cout << _T("----------------------------\n");
#endif
#ifdef STK_MIXTURE_VERY_VERBOSE
  stk_cout << _T("Parameters of the model\n");
  p_model_->writeParameters(stk_cout);
#endif
  return result;
}

References _T, STK::IRunnerBase::error(), STK::Clust::exceptionToString(), STK::IMixtureStatModel::finalizeStep(), STK::IStatModelBase::lnLikelihood(), STK::IMixtureLearner::mapStep(), STK::IRunnerBase::msg_error_, STK::IMixtureAlgoLearn::nbIterMax_, STK::IMixtureAlgoLearn::p_model_, STK::IMixtureLearner::paramUpdateStep(), STK::IMixtureStatModel::releaseIntermediateResults(), STK::IMixtureStatModel::samplingStep(), stk_cout, STK::IMixtureStatModel::storeIntermediateResults(), and STK::IMixtureStatModel::writeParameters().

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

• STK_MixtureAlgoLearn.h
• STK_MixtureAlgoLearn.cpp