STK++ 0.9.13
Public Member Functions | Protected Member Functions | Private Attributes | List of all members
STK::IMixtureModelBase Class Reference
Clustering using generative models

Base class for all Mixture model. More...

#include <STK_IMixtureModelBase.h>

Inheritance diagram for STK::IMixtureModelBase:
Inheritance graph

Public Member Functions

 IMixtureModelBase (int nbCluster)
 default constructor
 
 IMixtureModelBase (IMixtureModelBase const &model)
 copy constructor.
 
 ~IMixtureModelBase ()
 destructor
 
int nbCluster () const
 
int nbSample () const
 
Real lnNbSample () const
 

Protected Member Functions

void setNbSample (int nbSample)
 Set the number of sample of the model.
 

Private Attributes

int nbCluster_
 number of cluster.
 
int nbSample_
 total available samples
 

Detailed Description

Base class for all Mixture model.

Let X be an arbitrary measurable space and let $ \mathbf{x} =\{{\mathbf x}_1,...,{\mathbf x}_n\}$ be n independent vectors in X. If each ${\mathbf x}_i$ arises from a probability distribution with density

\[ f({\mathbf x}_i|\theta) = \sum_{k=1}^K p_k h({\mathbf x}_{i}| \lambda_{k},\alpha) \]

where the $p_k$'s are the mixing proportions, $h(\cdot| \lambda_{k},\alpha)$ denotes a d-dimensional distribution parameterized by $\lambda_k$ and $\alpha$, it is said that we observe a mixture model..

See also
IMixture, IMixtureModel, MixtureComposer

Definition at line 58 of file STK_IMixtureModelBase.h.

Constructor & Destructor Documentation

◆ IMixtureModelBase() [1/2]

STK::IMixtureModelBase::IMixtureModelBase ( int  nbCluster)

default constructor

Parameters
nbClusternumber of cluster

Definition at line 43 of file STK_IMixtureModelBase.cpp.

44 : nbCluster_(nbCluster)
45 , nbSample_(0)
46{}
STK::IMixtureModelBase::nbSample_
int nbSample_
total available samples
Definition STK_IMixtureModelBase.h:89
STK::IMixtureModelBase::nbCluster_
int nbCluster_
number of cluster.
Definition STK_IMixtureModelBase.h:87

◆ IMixtureModelBase() [2/2]

STK::IMixtureModelBase::IMixtureModelBase ( IMixtureModelBase const &  model)

copy constructor.

Note
the pointer are initialized to 0.
Parameters
modelthe model to clone

Definition at line 53 of file STK_IMixtureModelBase.cpp.

54 : nbCluster_(model.nbCluster_)
55 , nbSample_(model.nbSample_)
56{}

◆ ~IMixtureModelBase()

STK::IMixtureModelBase::~IMixtureModelBase ( )

destructor

Definition at line 59 of file STK_IMixtureModelBase.cpp.

59{}

Member Function Documentation

◆ lnNbSample()

Real STK::IMixtureModelBase::lnNbSample ( ) const
inline
Returns
the Log of the total available observations

Definition at line 76 of file STK_IMixtureModelBase.h.

77 { return (nbSample_ <= 0) ? -Arithmetic<Real>::infinity() : std::log((Real)nbSample_);}
STK::Real
double Real
STK fundamental type of Real values.
Definition STK_Typedefs.h:118

References nbSample_.

◆ nbCluster()

int STK::IMixtureModelBase::nbCluster ( ) const
inline
Returns
the number of cluster

Definition at line 72 of file STK_IMixtureModelBase.h.

72{ return nbCluster_;}

References nbCluster_.

Referenced by STK::IMixtureModel< Derived >::create().

◆ nbSample()

int STK::IMixtureModelBase::nbSample ( ) const
inline
Returns
the total available observations

Definition at line 74 of file STK_IMixtureModelBase.h.

74{ return nbSample_;}

References nbSample_.

Referenced by setNbSample().

◆ setNbSample()

void STK::IMixtureModelBase::setNbSample ( int  nbSample)
inlineprotected

Set the number of sample of the model.

Parameters
nbSamplenumber of sample of the model

Definition at line 83 of file STK_IMixtureModelBase.h.

83{ nbSample_ = nbSample;}

References nbSample(), and nbSample_.

Referenced by STK::IMixtureModel< Derived >::initializeModel().

Member Data Documentation

◆ nbCluster_

int STK::IMixtureModelBase::nbCluster_
private

number of cluster.

Definition at line 87 of file STK_IMixtureModelBase.h.

Referenced by nbCluster().

◆ nbSample_

int STK::IMixtureModelBase::nbSample_
private

total available samples

Definition at line 89 of file STK_IMixtureModelBase.h.

Referenced by lnNbSample(), nbSample(), and setNbSample().

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