C++ main module for mmsd Package  1.0
Public Member Functions | Static Public Member Functions | Static Public Attributes | Protected Member Functions | List of all members
MMSD_Cluster Class Referenceabstract

This class is a geneal MMSD Cluster. More...

#include <MMSD_Cluster.h>

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Public Member Functions

void setWeightInitializationType (const tString &type, const double &shape, const double &rate)
 set the weight initialization type More...
 
void setWeightInitializationType (const tFlag &t, const double &shape, const double &rate)
 set the weight initialization type More...
 
void setWeightInitializationType (const tFlag &t)
 set the weight initialization type More...
 
void setMaxFreedomDegreeValue (const double &v)
 set the max freedom degree value More...
 
double getMaxFreedomDegreeValue () const
 get the max freedom degree value More...
 
double getRate () const
 get rate of the cluster which is the percent of samples in this cluster. More...
 
const MMSD_DoubleFullMatrixgetWeights () const
 get the weight of sample 's property of size NxP More...
 
const MMSD_DoubleVectorgetFreedomDegrees () const
 get the freedom degree of property of size P More...
 
void setLaw (SP::MMSD_Law law)
 set the law More...
 
const MMSD_LawgetLaw () const
 get the law More...
 
tBoolean isEmpty () const
 return true is the cluster is empty More...
 
virtual void restore (const MMSD_DoubleFullMatrix &properties)
 restore the unstored values after a backup More...
 
virtual void initialize (const int &clusterIndex, const MMSD_IntegerVector &clusterIndexSamples, const MMSD_DoubleFullMatrix &properties)
 initialize the cluster More...
 
void updateRate (const MMSD_DoubleVector &clusterProbabilitiesSamples)
 update the rate of the cluster More...
 
void updateWeights (const MMSD_DoubleVector &probs)
 update the weights of the cluster More...
 
void updateLaw (const MMSD_DoubleFullMatrix &properties, const MMSD_DoubleVector &probs)
 update the law parameters More...
 
void updateFreedomDegrees (const MMSD_DoubleVector &probs)
 update the freedom degrees More...
 
void sort ()
 sort the freedom degrees with respect to the law More...
 
void computeMultivariateDensity (double *Pk) const
 compute the probabities of samples to be in cluster This More...
 
void computeMultivariateDensity (MMSD_DoubleVector &Pk) const
 compute the probabities of samples to be in cluster This More...
 
virtual tString toString () const
 turn the class into string More...
 
void setHasBeenLoaded (const tBoolean &v)
 set the if the object has completely been loaded More...
 
tBoolean hasBeenLoaded () const
 return true if the object has completely been loaded More...
 
void getSharedPointer (SP::CORE_Object &p)
 get the shared pointer of this class into p More...
 
void getSharedPointer (SPC::CORE_Object &p) const
 get the shared pointer of this class into p More...
 
tString getClassName () const
 return the class name of the object More...
 
tString getIdentityString () const
 return the identity string of the object of the form className_at_address More...
 
tString getPointerAddress () const
 return the identity string of the object More...
 
template<class T >
tBoolean isInstanceOf () const
 return true if the object is an instance of T More...
 
virtual void print ()
 print the class More...
 
virtual ostream & print (ostream &out) const
 print the class More...
 
virtual void print (const tString &message)
 print the class More...
 
virtual void print (const tInteger &str)
 print More...
 
virtual void print (const tRelativeInteger &str)
 print More...
 
virtual void print (const tReal &str)
 print More...
 
virtual void print (const int &str)
 print More...
 

Static Public Member Functions

static void initSeed (const long int &v)
 init the seed with v value More...
 
static void initSeed ()
 init the seed More...
 
static tString getClassName (const tString &identityString)
 return the class name of the object using only the identity string More...
 
template<class T >
static tString getTypeName ()
 get type name More...
 
static tBoolean is64Architecture ()
 return true if the machine is a 64 bits machine More...
 
static tBoolean is32Architecture ()
 return true if the machine is a 32 bits machine More...
 
static tString pointer2String (const void *obj)
 return the string represantation of a pointer More...
 
static void setOutput (ostream &out)
 set output More...
 
static ostream & getOutput ()
 get output More...
 
static void printObjectsInMemory ()
 print object in memory More...
 
static ostream & print (ostream &out, const tString &message)
 print the class More...
 
static void outputPrint (const tString &message)
 

Static Public Attributes

static tBoolean mIsMemoryTesting =false
 indicator to store all classes created and deleted only for debuging version More...
 

Protected Member Functions

 MMSD_Cluster (void)
 create an object More...
 
virtual ~MMSD_Cluster (void)
 destroy an object. More...
 
virtual void computeMultivariateDensity (const MMSD_DoubleFullMatrix &YP, const MMSD_DoubleFullMatrix &P, const MMSD_DoubleVector &D, const MMSD_DoubleVector &mean, const MMSD_DoubleVector &nu, double *Pk) const =0
 compute the probabities of samples to be in cluster This from law, freedom degrees & weights More...
 
virtual void updateWeights (const MMSD_DoubleFullMatrix &YP, const MMSD_DoubleFullMatrix &P, const MMSD_DoubleVector &D, const MMSD_DoubleVector &mean, const MMSD_DoubleVector &nu, const MMSD_DoubleVector &probs, MMSD_DoubleFullMatrix &W) const =0
 compute the weights from law, freedom degrees & probabilites More...
 
virtual void updateFreedomDegrees (const MMSD_DoubleFullMatrix &W, const MMSD_DoubleVector &probs, const double &maxFD, MMSD_DoubleVector &nus)=0
 update the freedom degrees from weights & probabilities. More...
 
virtual void saveToUIClass (UI_Class &mclass) const
 how to save the object from a mate model class More...
 
virtual void loadFromUIClass (const UI_Class &mclass)
 how to load the object from a Meta Model class More...
 
void setThis (SP::CORE_Object p)
 set this weak shared pointer called toDoAfterThis setting method More...
 
virtual void setType (tString type)
 set the type of the object More...
 
virtual void toDoAfterThisSetting ()
 method called after setThis() method this method can oly be called once. More...
 

Detailed Description

This class is a geneal MMSD Cluster.

A MMSD_Cluster has:

The initialization of the weight needs the Gamma distribution function STAT_GammaDistribution to perform its weight attribute array initialization in case of "gamma" of weight initialisation type MMSD_Cluster::setWeightInitializationType.

Weights , freedom degrees , rate & law are initialized by the MMQSD_Cluster::initialize() method.

Weights , freedom degrees , rate & law are updated, during EM iterations, by the methods:

Author
Stephane Despreaux
Version
1.0

Constructor & Destructor Documentation

MMSD_Cluster::MMSD_Cluster ( void  )
protected

create an object

References CORE_Object::setType().

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MMSD_Cluster::~MMSD_Cluster ( void  )
protectedvirtual

destroy an object.

Member Function Documentation

void MMSD_Cluster::computeMultivariateDensity ( double *  Pk) const
inline

compute the probabities of samples to be in cluster This

Referenced by computeMultivariateDensity(), and MMSD_Model::computeSampleClusterProbabilities().

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void MMSD_Cluster::computeMultivariateDensity ( MMSD_DoubleVector Pk) const
inline

compute the probabities of samples to be in cluster This

References computeMultivariateDensity(), LAP_Vector< T >::getValues(), and LAP_Vector< T >::setSize().

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virtual void MMSD_Cluster::computeMultivariateDensity ( const MMSD_DoubleFullMatrix YP,
const MMSD_DoubleFullMatrix P,
const MMSD_DoubleVector D,
const MMSD_DoubleVector mean,
const MMSD_DoubleVector nu,
double *  Pk 
) const
protectedpure virtual

compute the probabities of samples to be in cluster This from law, freedom degrees & weights

Parameters
YP: Y.P matrix of size NxP
P: P eigen value decomposition matrix of cov(Y) of size PXP
D: D eigen value decomposition diagonal matrix of cov(Y) of size P
mean: mean value of the properties cluster of size P
nu: freedom degrees of the cluster of size P
Pk: output vector which is the probability of the sample i to be in the cluster This. Must be of size N

Implemented in MMSD_GaussianCluster.

static tString CORE_Object::getClassName ( const tString identityString)
inlinestaticinherited

return the class name of the object using only the identity string

Referenced by UI_Class::createVector2D(), LAP_DoublePackedUpperMatrix::matrixProduct(), LAP_DoubleBandedUpperMatrix::matrixProduct(), LAP_DoubleFullUpperMatrix::matrixProduct(), and CORE_Object::printObjectsInMemory().

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tString CORE_Object::getClassName ( ) const
inherited

return the class name of the object

Returns
the class name of the object

References tString.

Referenced by CORE_Object::getIdentityString().

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const MMSD_DoubleVector& MMSD_Cluster::getFreedomDegrees ( ) const
inline

get the freedom degree of property of size P

tString CORE_Object::getIdentityString ( ) const
inlineinherited

return the identity string of the object of the form className_at_address

Returns
the identity string of the object

References CORE_Object::getClassName(), CORE_Object::pointer2String(), and tString.

Referenced by UI_Class::createPrimitiveMap(), UI_Class::saveAssociation(), UI_Class::saveClass(), UI_ClassFactory::saveIntoClass(), MATH_StiefelFunction::toString(), LAP_2DView::toString(), CORE_Object::toString(), MATH_StiefelOptimizer::toString(), and MM_Class::toString().

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const MMSD_Law* MMSD_Cluster::getLaw ( ) const
inline

get the law

double MMSD_Cluster::getMaxFreedomDegreeValue ( ) const
inline

get the max freedom degree value

Referenced by MMSD_GaussianCluster::MMSD_GaussianCluster().

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static ostream& CORE_Object::getOutput ( )
inlinestaticinherited

get output

tString CORE_Object::getPointerAddress ( ) const
inlineinherited

return the identity string of the object

Returns
the identity string of the object

References CORE_Object::pointer2String().

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double MMSD_Cluster::getRate ( ) const
inline

get rate of the cluster which is the percent of samples in this cluster.

Referenced by MMSD_Model::computeSampleClusterProbabilities().

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void CORE_Object::getSharedPointer ( SP::CORE_Object &  p)
inlineinherited
void CORE_Object::getSharedPointer ( SPC::CORE_Object &  p) const
inlineinherited

get the shared pointer of this class into p

template<class T >
static tString CORE_Object::getTypeName ( )
inlinestaticinherited

get type name

References tString.

const MMSD_DoubleFullMatrix& MMSD_Cluster::getWeights ( ) const
inline

get the weight of sample 's property of size NxP

tBoolean UI_Object::hasBeenLoaded ( ) const
inlineinherited

return true if the object has completely been loaded

Referenced by UI_Class::loadAssociation().

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void MMSD_Cluster::initialize ( const int &  clusterIndex,
const MMSD_IntegerVector clusterIndexSamples,
const MMSD_DoubleFullMatrix properties 
)
virtual

initialize the cluster

Parameters
clusterIndexindex of the cluster This
clusters: clusters index of size N for each samples
propertiesmatrix Y of properties of size N x P
  • updates the rate (mRate) of the cluster (number of samples in cluster clusterIndex / N)
  • updates empty attribute of the cluster (mRate==0)
  • creates the law & initialize it ( see MMD_Law::initialize() )
  • creates & initializes freedom degree parameters of size P & set to 20 by default
  • creates & initializes weights of size NxP depending on weight initialization parameters (see MMSD_Cluster::setWeightInitializationType()

References LAP_DoubleFullGeneralMatrix::getColumnsNumber(), LAP_DoubleFullGeneralMatrix::getRowsNumber(), LAP_DoubleMatrix::getStorage(), LAP_DoubleMatrixStorage::getValues(), LAP_Vector< T >::getValues(), STAT_GammaDistribution::New(), null, LAP_DoubleFullGeneralMatrix::setSize(), and LAP_Vector< T >::setSize().

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void MMSD_Object::initSeed ( const long int &  v)
staticinherited

init the seed with v value

References STAT_Distribution::initSeed().

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void MMSD_Object::initSeed ( )
staticinherited

init the seed

References CORE_Time::getTime().

Referenced by MMSD_Object::MMSD_Object(), testGaussianLaw11N(), testGaussianLaw1PN(), and testGaussianLaw2PN().

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static tBoolean CORE_Object::is32Architecture ( )
inlinestaticinherited

return true if the machine is a 32 bits machine

References CORE_Object::is64Architecture().

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tBoolean CORE_Object::is64Architecture ( )
staticinherited

return true if the machine is a 64 bits machine

Referenced by CORE_Object::is32Architecture().

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tBoolean MMSD_Cluster::isEmpty ( ) const
inline

return true is the cluster is empty

Referenced by MMSD_Model::esperanceEvaluation().

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template<class T >
tBoolean CORE_Object::isInstanceOf ( ) const
inlineinherited

return true if the object is an instance of T

References null.

void MMSD_Cluster::loadFromUIClass ( const UI_Class mclass)
protectedvirtual

how to load the object from a Meta Model class

Reimplemented from UI_Object.

References UI_Class::getInterfaceType(), UI_Class::loadAssociation(), UI_Class::loadField(), UI_Class::loadFullMatrixField(), LAP_DoubleFullGeneralMatrix::setValues(), LAP_Vector< T >::setValues(), and tBoolean.

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void CORE_Object::outputPrint ( const tString message)
staticinherited

print on output

References null, and CORE_Object::print().

Referenced by CORE_Exception::CORE_Exception().

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tString CORE_Object::pointer2String ( const void *  obj)
staticinherited

return the string represantation of a pointer

References tString.

Referenced by CORE_Object::CORE_Object(), CORE_Object::getIdentityString(), CORE_Object::getPointerAddress(), and CORE_Object::~CORE_Object().

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virtual void CORE_Object::print ( )
inlinevirtualinherited

print the class

References CORE_Object::toString().

Referenced by CORE_Object::outputPrint(), CORE_Out::print(), CORE_Object::print(), CORE_Out::printInt(), CORE_Out::println(), CORE_Out::printReal(), CORE_Out::printString(), and CORE_Out::setAction().

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virtual ostream& CORE_Object::print ( ostream &  out) const
inlinevirtualinherited

print the class

References CORE_Object::print(), and CORE_Object::toString().

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void CORE_Object::print ( const tString message)
virtualinherited

print the class

Reimplemented in CORE_Out.

References null, and CORE_Object::print().

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void CORE_Object::print ( const tInteger str)
virtualinherited

print

References null.

void CORE_Object::print ( const tRelativeInteger str)
virtualinherited

print

References null.

void CORE_Object::print ( const tReal str)
virtualinherited

print

References null.

void CORE_Object::print ( const int &  str)
virtualinherited

print

References null.

static ostream& CORE_Object::print ( ostream &  out,
const tString message 
)
inlinestaticinherited

print the class

void CORE_Object::printObjectsInMemory ( )
staticinherited

print object in memory

References CORE_Object::getClassName(), CORE_Object::getSharedPointer(), and CORE_Object::mIsMemoryTesting.

Referenced by main().

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void MMSD_Cluster::restore ( const MMSD_DoubleFullMatrix properties)
virtual

restore the unstored values after a backup

void MMSD_Cluster::saveToUIClass ( UI_Class mclass) const
protectedvirtual
void UI_Object::setHasBeenLoaded ( const tBoolean v)
inlineinherited

set the if the object has completely been loaded

Referenced by UI_Class::loadAssociation().

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void MMSD_Cluster::setLaw ( SP::MMSD_Law  law)
inline

set the law

void MMSD_Cluster::setMaxFreedomDegreeValue ( const double &  v)
inline

set the max freedom degree value

Parameters
vmax freedom value

By default set to 299

static void CORE_Object::setOutput ( ostream &  out)
inlinestaticinherited

set output

void CORE_Object::setThis ( SP::CORE_Object  p)
inlineprotectedinherited

set this weak shared pointer called toDoAfterThis setting method

References CORE_Object::toDoAfterThisSetting().

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virtual void CORE_Object::setType ( tString  type)
inlineprotectedvirtualinherited

set the type of the object

Referenced by LAP_IntegerVector::LAP_IntegerVector(), MATH_BetaFunction::MATH_BetaFunction(), MATH_C1Function::MATH_C1Function(), MATH_DigammaFunction::MATH_DigammaFunction(), MATH_EigenFunction::MATH_EigenFunction(), MATH_Equation::MATH_Equation(), MATH_Function::MATH_Function(), MATH_GammaFunction::MATH_GammaFunction(), MATH_KeplerFunction::MATH_KeplerFunction(), MATH_LogGammaFunction::MATH_LogGammaFunction(), MATH_NewtonEquation::MATH_NewtonEquation(), MATH_StiefelFunction::MATH_StiefelFunction(), MATH_StiefelOptimizer::MATH_StiefelOptimizer(), MATH_TranscendentEquation::MATH_TranscendentEquation(), MATH_TrigammaFunction::MATH_TrigammaFunction(), MATH_ZeroEquation::MATH_ZeroEquation(), MATH_ZKeplerFunction::MATH_ZKeplerFunction(), MM_Attribute::MM_Attribute(), MM_Class::MM_Class(), MM_ClassFactory::MM_ClassFactory(), MM_Data::MM_Data(), MM_Structure::MM_Structure(), MMSD_ClassFactory::MMSD_ClassFactory(), MMSD_Cluster(), MMSD_ConstDoubleVector::MMSD_ConstDoubleVector(), MMSD_ConstraintGaussianCluster::MMSD_ConstraintGaussianCluster(), MMSD_ConstraintGaussianModel::MMSD_ConstraintGaussianModel(), MMSD_DataSet::MMSD_DataSet(), MMSD_DataSetClassFactory::MMSD_DataSetClassFactory(), MMSD_DoubleFullMatrix::MMSD_DoubleFullMatrix(), MMSD_DoubleSymmetricMatrix::MMSD_DoubleSymmetricMatrix(), MMSD_DoubleVector::MMSD_DoubleVector(), MMSD_FluryGautschiGaussianLaw::MMSD_FluryGautschiGaussianLaw(), MMSD_GaussianCluster::MMSD_GaussianCluster(), MMSD_GaussianFDFunction::MMSD_GaussianFDFunction(), MMSD_GaussianLaw::MMSD_GaussianLaw(), MMSD_GaussianModel::MMSD_GaussianModel(), MMSD_Law::MMSD_Law(), MMSD_Model::MMSD_Model(), MMSD_ModelClassFactory::MMSD_ModelClassFactory(), MMSD_Object::MMSD_Object(), MMSD_StiefelFunction::MMSD_StiefelFunction(), MMSD_StiefelGaussianLaw::MMSD_StiefelGaussianLaw(), STAT_BernoulliDistribution::STAT_BernoulliDistribution(), STAT_BinomialDistribution::STAT_BinomialDistribution(), STAT_Combinatorial< T >::STAT_Combinatorial(), STAT_DiracDistribution::STAT_DiracDistribution(), STAT_Distribution::STAT_Distribution(), STAT_ExponentialDistribution::STAT_ExponentialDistribution(), STAT_GammaDistribution::STAT_GammaDistribution(), STAT_GeometricDistribution::STAT_GeometricDistribution(), STAT_InverseNormalDistribution::STAT_InverseNormalDistribution(), STAT_NormalDistribution::STAT_NormalDistribution(), STAT_Object::STAT_Object(), STAT_PoissonDistribution::STAT_PoissonDistribution(), STAT_UniformDistribution::STAT_UniformDistribution(), and STAT_UniformLaplaceTransform::STAT_UniformLaplaceTransform().

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void MMSD_Cluster::setWeightInitializationType ( const tString type,
const double &  shape,
const double &  rate 
)
inline

set the weight initialization type

Parameters
typeof weight initialization ["gamma" or "constant"]
shape: parameter for statistic function weight initialization
rate: parameter for statistic function weight initialization

References CORE_String::toLower(), and tString.

Referenced by setWeightInitializationType().

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void MMSD_Cluster::setWeightInitializationType ( const tFlag t,
const double &  shape,
const double &  rate 
)
inline

set the weight initialization type

Parameters
typeof weight initialization MMSD_Cluster::GAMMA_WEIGHT_INITIALIZATION, MMSD_Cluster::CONSTANT_WEIGHT_INITIALIZATION
shape: parameter for statistic function weight initialization
rate: parameter for statistic function weight initialization
void MMSD_Cluster::setWeightInitializationType ( const tFlag t)
inline

set the weight initialization type

Parameters
typeof weight initialization MMSD_Cluster::GAMMA_WEIGHT_INITIALIZATION, MMSD_Cluster::CONSTANT_WEIGHT_INITIALIZATION

References setWeightInitializationType().

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void MMSD_Cluster::sort ( )
inline

sort the freedom degrees with respect to the law

Referenced by MMSD_Model::esperanceMaximization().

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virtual void CORE_Object::toDoAfterThisSetting ( )
inlineprotectedvirtualinherited

method called after setThis() method this method can oly be called once.

Reimplemented in STAT_UniformLaplaceTransform.

Referenced by CORE_Object::setThis(), and STAT_UniformLaplaceTransform::toDoAfterThisSetting().

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virtual tString MMSD_Cluster::toString ( ) const
inlinevirtual

turn the class into string

Reimplemented from CORE_Object.

Reimplemented in MMSD_GaussianCluster, and MMSD_ConstraintGaussianCluster.

References CORE_Object::toString(), and tString.

Referenced by MMSD_GaussianCluster::toString().

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void MMSD_Cluster::updateFreedomDegrees ( const MMSD_DoubleVector probs)
inline

update the freedom degrees

Referenced by MMSD_Model::esperanceMaximization().

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virtual void MMSD_Cluster::updateFreedomDegrees ( const MMSD_DoubleFullMatrix W,
const MMSD_DoubleVector probs,
const double &  maxFD,
MMSD_DoubleVector nus 
)
protectedpure virtual

update the freedom degrees from weights & probabilities.

Parameters
Wweights of the cluster of size NxP
probs: probability of each sample to be in This cluster of size N
maxFDmax value of freedom degrees see MMSD_Cluster::setMaxFreedomDegreeValue()
nusoutput value of freedom degrees of size P

Implemented in MMSD_GaussianCluster, and MMSD_ConstraintGaussianCluster.

void MMSD_Cluster::updateLaw ( const MMSD_DoubleFullMatrix properties,
const MMSD_DoubleVector probs 
)
inline

update the law parameters

Referenced by MMSD_Model::esperanceMaximization().

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void MMSD_Cluster::updateRate ( const MMSD_DoubleVector clusterProbabilitiesSamples)

update the rate of the cluster

Parameters
clusterProbabilitiesSamplesprobability of each sample to be in this cluster

References LAP_Vector< T >::getSize(), and LAP_Vector< T >::getValues().

Referenced by MMSD_Model::esperanceEvaluation().

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void MMSD_Cluster::updateWeights ( const MMSD_DoubleVector probs)
inline

update the weights of the cluster

Referenced by MMSD_Model::esperanceEvaluation().

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virtual void MMSD_Cluster::updateWeights ( const MMSD_DoubleFullMatrix YP,
const MMSD_DoubleFullMatrix P,
const MMSD_DoubleVector D,
const MMSD_DoubleVector mean,
const MMSD_DoubleVector nu,
const MMSD_DoubleVector probs,
MMSD_DoubleFullMatrix W 
) const
protectedpure virtual

compute the weights from law, freedom degrees & probabilites

Parameters
YP: Y.P matrix of size NxP
P: P eigen value decomposition matrix of cov(Y) of size PXP
D: D eigen value decomposition diagonal matrix of cov(Y) of size P
mean: mean value of the properties cluster of size P
nu: freedom degrees of the cluster of size P
probs: probability of the sample i in(0,N[ to be in the cluster This.
W: output weight matrix of size NxP

Implemented in MMSD_GaussianCluster.

Member Data Documentation

tBoolean CORE_Object::mIsMemoryTesting =false
staticinherited

indicator to store all classes created and deleted only for debuging version

Referenced by CORE_Object::CORE_Object(), main(), CORE_Object::printObjectsInMemory(), and CORE_Object::~CORE_Object().


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