STK::CategoricalBase< Derived > Class Template Reference

Base class for the Categorical models. More...

#include <STK_CategoricalBase.h>

Inheritance diagram for STK::CategoricalBase< Derived >:

Public Member Functions
PointXi const &	nbModalities () const
Range const &	modalities () const
Real	proba (int k, int j, int l) const
CVectorX	proba (int k, int j) const
void	initializeModelImpl ()
	Initialize the model.
Real	lnComponentProbability (int i, int k) const
template<class Weights >
int	impute (int i, int j, Weights const &tk) const
int	rand (int i, int j, int k) const
template<class Array >
void	getParameters (Array &params) const
	This function is used in order to get the current values of the parameters in an array.
void	writeParameters (CArrayXX const *p_tik, ostream &os) const
	This function can be used to write summary of parameters to the output stream.
Public Member Functions inherited from STK::IMixtureDensity< Derived >
	~IMixtureDensity ()
	destructor
int	nbCluster () const
int	nbSample () const
Real	lnNbSample () const
Array const *const &	p_data () const
Parameters const &	param () const
void	setData (Array const &data)
	Set the data set.
void	setData (Array const &data, int nbRow, int nbCol, bool byRow=true)
	Set the data set and give dimensions.
bool	initializeStep ()
	This function will be called at the beginning of the estimation process once the model is created and data is set.
void	setParametersStep ()
	set the parameters obtained with the intermediate results and release the intermediate results.
void	finalizeStep ()
	This function will be called once the model is estimated.
template<class Weights >
Type	sample (int i, int j, Weights const &tk) const
Public Member Functions inherited from STK::IRecursiveTemplate< Derived >
Derived &	asDerived ()
	static cast : return a reference of this with a cast to the derived class.
Derived const &	asDerived () const
	static cast : return a const reference of this with a cast to the derived class.
Derived *	asPtrDerived ()
	static cast : return a ptr on a Derived of this with a cast to the derived class.
Derived const *	asPtrDerived () const
	static cast : return a ptr on a constant Derived of this with a cast to the derived class.
Derived *	clone () const
	create a leaf using the copy constructor of the Derived class.
Derived *	clone (bool isRef) const
	create a leaf using the copy constructor of the Derived class and a flag determining if the clone is a reference or not.

Protected Types
typedef IMixtureDensity< Derived >	Base

Protected Member Functions
	CategoricalBase (int nbCluster)
	default constructor
	CategoricalBase (CategoricalBase const &model)
	copy constructor
	~CategoricalBase ()
	destructor
Array const *const &	p_data () const
Protected Member Functions inherited from STK::IMixtureDensity< Derived >
	IMixtureDensity (int nbCluster)
	Default constructor.
	IMixtureDensity (IMixtureDensity const &model)
	copy constructor.
void	initializeModel ()
	Initialize the model before its first use.
bool	initializeStepImpl ()
	default implementation of initializeStepImpl (do nothing and return true)
void	finalizeStepImpl ()
	default implementation of finalizeStepImpl (do nothing)
void	setNbSample (int nbSample)
	Set the number of sample of the model (needed by kernel models)
Protected Member Functions inherited from STK::IRecursiveTemplate< Derived >
	IRecursiveTemplate ()
	constructor.
	~IRecursiveTemplate ()
	destructor.

Protected Attributes
PointXi	nbModalities_
	Array with the number of modalities of each columns of the data set.
Range	modalities_
	range of the modalities
Parameters	param_
	parameters of the derived mixture model.
Protected Attributes inherited from STK::IMixtureDensity< Derived >
Parameters	param_
	parameters of the derived mixture model.

Additional Inherited Members
Public Types inherited from STK::IMixtureDensity< Derived >
typedef hidden::MixtureTraits< Derived >::Array	Array
typedef hidden::MixtureTraits< Derived >::Parameters	Parameters
typedef hidden::Traits< Array >::Type	Type

Detailed Description

template<class Derived>
class STK::CategoricalBase< Derived >

Base class for the Categorical models.

Definition at line 50 of file STK_CategoricalBase.h.

Member Typedef Documentation

Base

template<class Derived >

typedef IMixtureDensity<Derived> STK::CategoricalBase< Derived >::Base

protected

Definition at line 53 of file STK_CategoricalBase.h.

Constructor & Destructor Documentation

CategoricalBase() [1/2]

template<class Derived >

STK::CategoricalBase< Derived >::CategoricalBase ( int  nbCluster )

inlineprotected

default constructor

Parameters

nbCluster

number of cluster in the model

Definition at line 60 of file STK_CategoricalBase.h.

: Base(nbCluster) {}

CategoricalBase() [2/2]

template<class Derived >

STK::CategoricalBase< Derived >::CategoricalBase ( CategoricalBase< Derived > const &  model )

inlineprotected

copy constructor

Parameters

model

The model to copy

Definition at line 64 of file STK_CategoricalBase.h.

                         : Base(model), modalities_(model.modalities_)
    {}

~CategoricalBase()

template<class Derived >

STK::CategoricalBase< Derived >::~CategoricalBase ( )

inlineprotected

destructor

Definition at line 68 of file STK_CategoricalBase.h.

{}

Member Function Documentation

getParameters()

template<class Derived >

template<class Array >

void STK::CategoricalBase< Derived >::getParameters

(

Array &

params

)

const

This function is used in order to get the current values of the parameters in an array.

Parameters

[out]

params

the array with the parameters of the mixture.

Definition at line 195 of file STK_CategoricalBase.h.

{
    int nbCluster    = this->nbCluster();
    int nbModalities = modalities().size();
 
    params.resize(nbModalities * nbCluster, p_data()->cols());
    for (int k = 0; k < nbCluster; ++k)
    {
      for (int j = p_data()->beginCols(); j < p_data()->endCols(); ++j)
      {
        for (int l = 0; l < nbModalities; ++l)
        { params(baseIdx+k * nbModalities + l, j) = proba(baseIdx+k, j, modalities().begin() + l);}
      }
    }
}

References STK::baseIdx.

impute()

template<class Derived >

template<class Weights >

int STK::CategoricalBase< Derived >::impute	(	int	i,
		int	j,
		Weights const &	tk
	)		const

Returns

an imputation value for the jth variable of the ith sample

Parameters

i,j	indexes of the data to impute
tk	the probabilities of each class for the ith individual

Definition at line 155 of file STK_CategoricalBase.h.

{
  int lmax = modalities_.begin();
  Real pmax = -Arithmetic<Real>::max();
  // compute for each modality the pondered probability of occurrence
  for (int l=modalities_.begin(); l< modalities_.end(); ++l)
  {
    Real p = 0.;
    for (int k= tk.begin(); k < tk.end(); ++k)
    { p += tk[k] * proba(k, j, l);}
 
    if (pmax < p) { pmax = p; lmax = l;}
  }
  return lmax;
}

initializeModelImpl()

template<class Derived >

void STK::CategoricalBase< Derived >::initializeModelImpl ( )

inline

Initialize the model.

Resize the probability arrays of each component and compute the number and range of modalities of each variables.

Definition at line 82 of file STK_CategoricalBase.h.

    {
      // compute the maximal number of modalities
      nbModalities_.resize(p_data()->cols());
      int amin = Arithmetic<int>::max(), amax = Arithmetic<int>::min();
      for (int j= p_data()->beginCols(); j < p_data()->endCols(); ++j)
      {
        int min = p_data()->col(j).minElt(), max = p_data()->col(j).maxElt();
        amin = std::min(amin, min); amax = std::max(amax, max);
        nbModalities_[j] = max-min+1;
      }
      // set range of the modalities
      modalities_ = _R(amin, amax);
      // resize vectors of probabilities
      param_.resize(modalities_,p_data()->cols());
#ifdef STK_MIXTURE_VERBOSE
      stk_cout << _T("In CatagoricalBase::initializeModelImpl. modalities_ = ")
               << modalities_ << _T("\n");
#endif
    }

References _R, _T, STK::max(), STK::min(), STK::CategoricalBase< Derived >::modalities_, STK::CategoricalBase< Derived >::nbModalities_, STK::CategoricalBase< Derived >::p_data(), STK::CategoricalBase< Derived >::param_, STK::IArray2D< Derived >::resize(), and stk_cout.

lnComponentProbability()

template<class Derived >

Real STK::CategoricalBase< Derived >::lnComponentProbability ( int  i, int  k  ) const

inline

Returns

the value of the probability of the i-th sample in the k-th component.

Parameters

i,k	indexes of the sample and of the component

Definition at line 140 of file STK_CategoricalBase.h.

{
  Real sum =0.;
  for (int j=p_data()->beginCols(); j<p_data()->endCols(); ++j)
  { // what to do if the probability is zero but a sample get this modality
    // for now, just ignore it (it's possible if tik_(i,k) == 0)
    Real prob= proba(k, j, p_data()->elt(i,j));
    if (prob) { sum += std::log(prob);}
   }
  return sum;
}

References STK::sum().

modalities()

template<class Derived >

Range const & STK::CategoricalBase< Derived >::modalities ( ) const

inline

Returns

the range of the modalities

Definition at line 74 of file STK_CategoricalBase.h.

{ return modalities_;}

References STK::CategoricalBase< Derived >::modalities_.

nbModalities()

template<class Derived >

PointXi const & STK::CategoricalBase< Derived >::nbModalities ( ) const

inline

Returns

the array with the number of modalities of each columns in data set

Definition at line 72 of file STK_CategoricalBase.h.

{ return nbModalities_;}

References STK::CategoricalBase< Derived >::nbModalities_.

p_data()

template<class Derived >

Array const *const & STK::IMixtureDensity< Derived >::p_data ( ) const

inlineprotected

Returns

a pointer on the current data set

Definition at line 131 of file STK_IMixtureDensity.h.

{ return p_dataij_;}

Referenced by STK::CategoricalBase< Derived >::initializeModelImpl().

proba() [1/2]

template<class Derived >

CVectorX STK::CategoricalBase< Derived >::proba ( int  k, int  j  ) const

inline

Returns

the probabilities of the kth cluster for the jth variable

Definition at line 78 of file STK_CategoricalBase.h.

{ return param_.proba(k,j);}

References STK::CategoricalBase< Derived >::param_.

proba() [2/2]

template<class Derived >

Real STK::CategoricalBase< Derived >::proba ( int  k, int  j, int  l  ) const

inline

Returns

the probability of the kth cluster, jth variable, lth modality

Definition at line 76 of file STK_CategoricalBase.h.

{ return param_.proba(k,j,l);}

References STK::CategoricalBase< Derived >::param_.

Referenced by STK::CategoricalBase< Derived >::rand().

rand()

template<class Derived >

int STK::CategoricalBase< Derived >::rand ( int  i, int  j, int  k  ) const

inline

Returns

a simulated value for the jth variable of the ith sample in the kth cluster

Parameters

i,j,k

indexes of the data to simulate

Definition at line 115 of file STK_CategoricalBase.h.

    { return Law::Categorical::rand(proba(k,j));}

References STK::CategoricalBase< Derived >::proba(), and STK::Law::Categorical::rand().

writeParameters()

template<class Derived >

void STK::CategoricalBase< Derived >::writeParameters	(	CArrayXX const *	p_tik,
		ostream &	os
	)		const

This function can be used to write summary of parameters to the output stream.

Parameters

p_tik	a constant pointer on the posterior probabilities
os	Stream where you want to write the summary of parameters.

Definition at line 176 of file STK_CategoricalBase.h.

{
  ArrayXX p(modalities(), p_data()->cols());
  for (int k= p_tik->beginCols(); k < p_tik->endCols(); ++k)
  {
    // store proba values in an array for a nice output
    for (int j= p.beginCols();  j < p.endCols(); ++j)
    {
      for (int l= modalities().begin(); l < modalities().end(); ++l)
      { p(l, j) = proba(k,j,l);}
    }
    os << _T("---> Component ") << k << _T("\n");
    os << _T("probabilities =\n") << p  << _T("\n");
  }
 
}

References _T.

Member Data Documentation

modalities_

template<class Derived >

Range STK::CategoricalBase< Derived >::modalities_

protected

range of the modalities

Definition at line 133 of file STK_CategoricalBase.h.

Referenced by STK::CategoricalBase< Derived >::initializeModelImpl(), and STK::CategoricalBase< Derived >::modalities().

nbModalities_

template<class Derived >

PointXi STK::CategoricalBase< Derived >::nbModalities_

protected

Array with the number of modalities of each columns of the data set.

Definition at line 131 of file STK_CategoricalBase.h.

Referenced by STK::CategoricalBase< Derived >::initializeModelImpl(), and STK::CategoricalBase< Derived >::nbModalities().

param_

template<class Derived >

Parameters STK::IMixtureDensity< Derived >::param_

protected

parameters of the derived mixture model.

Should be an instance of the STK::ModelParameters struct.

See also

STK::ModelParameters

Definition at line 180 of file STK_IMixtureDensity.h.

Referenced by STK::CategoricalBase< Derived >::initializeModelImpl(), STK::CategoricalBase< Derived >::proba(), and STK::CategoricalBase< Derived >::proba().

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

• STK_CategoricalBase.h