37#ifndef STK_IMIXTUREDENSITY_H
38#define STK_IMIXTUREDENSITY_H
45#ifdef STK_MIXTURE_DEBUG
98template<
class Derived>
160 param_.setParametersStep();
171 template<
class Weights>
218template<
class Derived>
221 , nbCluster_(nbCluster)
231template<
class Derived>
233 : param_(
model.param_)
234 , nbCluster_(
model.nbCluster_)
235 , nbSample_(
model.nbSample_)
236 , p_dataij_(
model.p_dataij_)
243template<
class Derived>
253template<
class Derived>
271template<
class Derived>
275 this->setNbSample(p_dataij_->sizeRows());
277 this->asDerived().initializeModelImpl();
In this file we define the enum, constants and utilities functions of the Clustering project.
This file define methods for displaying Arrays and Expressions.
In this file we define the Categorical distribution.
In this file we define the constant and utilities methods used in the project Model.
Base class for all Mixture densities.
void setNbSample(int nbSample)
Set the number of sample of the model (needed by kernel models)
Array const *const & p_data() const
void initializeModel()
Initialize the model before its first use.
void finalizeStepImpl()
default implementation of finalizeStepImpl (do nothing)
hidden::Traits< Array >::Type Type
void setData(Array const &data)
Set the data set.
IMixtureDensity(IMixtureDensity const &model)
copy constructor.
Parameters param_
parameters of the derived mixture model.
Parameters const & param() const
bool initializeStep()
This function will be called at the beginning of the estimation process once the model is created and...
hidden::MixtureTraits< Derived >::Parameters Parameters
~IMixtureDensity()
destructor
int nbCluster_
number of cluster.
hidden::MixtureTraits< Derived >::Array Array
IMixtureDensity(int nbCluster)
Default constructor.
int nbSample_
total available samples
void finalizeStep()
This function will be called once the model is estimated.
bool initializeStepImpl()
default implementation of initializeStepImpl (do nothing and return true)
Type sample(int i, int j, Weights const &tk) const
Array const * p_dataij_
pointer on the data set
void setParametersStep()
set the parameters obtained with the intermediate results and release the intermediate results.
void setData(Array const &data, int nbRow, int nbCol, bool byRow=true)
Set the data set and give dimensions.
Interface base class for all classes implementing the curious recursive template paradigm.
Derived & asDerived()
static cast : return a reference of this with a cast to the derived class.
The MultidimRegression class allows to regress a multidimensional output variable among a multivariat...
double Real
STK fundamental type of Real values.
The namespace STK is the main domain space of the Statistical ToolKit project.
Arithmetic properties of STK fundamental types.
Main class for the mixtures traits policy.