Interface base class for predicting algorithms. More...

#include <STK_IMixtureAlgoPredict.h>

Inheritance diagram for STK::IMixtureAlgoPredict:

Public Member Functions
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.

virtual bool	run ()=0
	run the computations.

Protected Member Functions
	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
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

Interface base class for predicting algorithms.

Predicting algorithms are decomposed in two stages :

A burning stage using SEM algorithm
An estimation stage using EM or SemiSEM algorithm If there is no missing values, the algorithm simplify in a posterior allocation stage.

All algorithms are runners applying on a IMixtureComposer model instance given by pointer and have to implement the run method.

Definition at line 57 of file STK_IMixtureAlgoPredict.h.

Constructor & Destructor Documentation

◆ IMixtureAlgoPredict() [1/2]

STK::IMixtureAlgoPredict::IMixtureAlgoPredict ( )

protected

default constructor

Definition at line 42 of file STK_IMixtureAlgoPredict.cpp.

                                        : IRunnerBase()
                                          , p_model_(0)
                                          , nbIterBurn_(0), nbIterLong_(0), epsilon_(0.) {}

◆ IMixtureAlgoPredict() [2/2]

STK::IMixtureAlgoPredict::IMixtureAlgoPredict ( IMixtureAlgoPredict const & algo )

protected

Copy constructor.

Parameters

algo	the algorithm to copy

Definition at line 48 of file STK_IMixtureAlgoPredict.cpp.

                                                                        : IRunnerBase(algo)
                                         , p_model_(algo.p_model_)
                                         , nbIterBurn_(algo.nbIterBurn_)
                                         , nbIterLong_(algo.nbIterLong_)
                                         , epsilon_(algo.epsilon_)
{}

◆ ~IMixtureAlgoPredict()

STK::IMixtureAlgoPredict::~IMixtureAlgoPredict ( )

virtual

destructor

Definition at line 56 of file STK_IMixtureAlgoPredict.cpp.

56{}

Member Function Documentation

◆ burnStep()

bool STK::IMixtureAlgoPredict::burnStep ( )

protected

Perform burn step using SEM algorithm.

initializeStep();
eStep(); // will compute tik and zi values
finalizeStep();

Returns: true if no error occur, false otherwise

Definition at line 101 of file STK_IMixtureAlgoPredict.cpp.

{
#ifdef STK_MIXTURE_VERY_VERBOSE
  stk_cout << _T("-------------------------------\n");
  stk_cout << _T("Entering IMixtureAlgoPredict::burnStep()\n");
#endif
  try
  {
    p_model_->initializeStep();
    for (int iter = 0; iter < nbIterLong_; ++iter)
    {
      p_model_->sStep(); // simulate labels
      p_model_->samplingStep(); // simulate missing values
      p_model_->eStep();   // update tik and lnLikelihood
      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 error occur in IMixtureAlgoPredict::run(): ") << msg_error_ << _T("\n");
#endif
    p_model_->setParametersStep(); // compute current parameters value
    return false;
  }
  p_model_->setParametersStep(); // compute current parameters value
  return true;
}

References _T, STK::IRunnerBase::error(), STK::IMixtureComposer::eStep(), STK::Clust::exceptionToString(), STK::IMixtureComposer::initializeStep(), STK::IRunnerBase::msg_error_, nbIterLong_, p_model_, STK::IMixtureStatModel::samplingStep(), STK::IMixtureStatModel::setParametersStep(), STK::IMixtureComposer::sStep(), stk_cout, and STK::IMixtureStatModel::storeIntermediateResults().

Referenced by STK::EMPredict::run(), and STK::SemiSEMPredict::run().

◆ epsilon()

int STK::IMixtureAlgoPredict::epsilon ( ) const

inline

Returns: the epsilon of the algorithm

Definition at line 76 of file STK_IMixtureAlgoPredict.h.

76{ return epsilon_;}

References epsilon_.

Referenced by setEpsilon().

◆ nbIterBurn()

int STK::IMixtureAlgoPredict::nbIterBurn ( ) const

inline

Returns: the maximal number of iteration of the algorithm

Definition at line 72 of file STK_IMixtureAlgoPredict.h.

72{ return nbIterBurn_; }

References nbIterBurn_.

Referenced by setNbIterBurn().

◆ predictBayesClassifier()

bool STK::IMixtureAlgoPredict::predictBayesClassifier ( )

protected

predict class labels when there is no missing values.

In this case, there is no algorithm to do. Just call:

initializeStep();
eStep(); // will compute tik and zi values
finalizeStep();

Returns: true if no error occur, false otherwise

Definition at line 66 of file STK_IMixtureAlgoPredict.cpp.

{
#ifdef STK_MIXTURE_VERY_VERBOSE
  stk_cout << _T("-------------------------------\n");
  stk_cout << _T("Entering IMixtureAlgoPredict::predictBayesClassifier()\n");
#endif
 
 
  try
  {
    p_model_->initializeStep();
    p_model_->eStep();
    p_model_->mapStep();
    p_model_->finalizeStep();
  }
  catch (Exception const& error)
  {
    msg_error_ = error.error();
#ifdef STK_MIXTURE_VERBOSE
    stk_cout << _T("An error occur in IMixtureAlgoPredict::run():\n") << msg_error_ << _T("\n");
#endif
    return false;
  }
  catch (Clust::exceptions const& error)
  {
    msg_error_ = Clust::exceptionToString(error);
#ifdef STK_MIXTURE_VERBOSE
    stk_cout << _T("An error occur in IMixtureAlgoPredict::run():\n") << msg_error_ << _T("\n");
#endif
    return false;
  }
  return true;
}