mixmod  3.2.0
Mixture models for clustering and classification
 All Classes Namespaces Files Functions Variables Enumerations Friends
XEM::BinaryModel Class Reference

Base class for Model(s) More...

#include <BinaryModel.h>

Inheritance diagram for XEM::BinaryModel:
Collaboration diagram for XEM::BinaryModel:

Public Member Functions

 BinaryModel ()
 Default constructor.
 
virtual Modelclone ()
 
 BinaryModel (BinaryModel *iModel)
 Constructor.
 
 BinaryModel (ModelType *modelType, int64_t nbCluster, Data *&data, Partition *knownPartition, std::vector< int64_t > const &correspondenceOriginDataToReduceData)
 Constructor.
 
virtual ~BinaryModel ()
 Destructor.
 
const std::vector< int64_t > & getCorrespondenceOriginDataToReduceData () const
 
- Public Member Functions inherited from XEM::Model
 Model ()
 Default constructor.
 
 Model (Model *iModel)
 Constructor.
 
 Model (ModelType *modelType, int64_t nbCluster, Data *&data, Partition *knownPartition)
 Constructor.
 
virtual ~Model ()
 Destructor.
 
void updateForCV (Model *originalModel, CVBlock &CVBlock)
 
ParametergetParameter ()
 Selector. More...
 
GaussianParametergetGaussianParameter ()
 
BinaryParametergetBinaryParameter ()
 
int64_t getNbCluster ()
 Selector. More...
 
DatagetData ()
 Selector. More...
 
GaussianDatagetGaussianData ()
 Return Gaussian data. More...
 
BinaryDatagetBinaryData ()
 Return Binary data. More...
 
ExceptiongetErrorType () const
 Selector. More...
 
ModelType *const & getModelType () const
 Selector. More...
 
int64_t getNbSample ()
 Selector. More...
 
double ** getTabFik ()
 Selector. More...
 
double * getTabSumF ()
 return _tabSumF
 
double ** getTabTik ()
 Selector. More...
 
int64_t ** getTabZikKnown ()
 Selector. More...
 
double ** getTabCik ()
 
bool * getTabZiKnown ()
 getTabZikKnown
 
double * getTabNk ()
 Selector. More...
 
bool getDeleteData ()
 
void computeFik ()
 compute _fik
 
void computeNk ()
 Compute the number of points in each class.
 
double getLogLikelihood (bool fikMustBeComputed)
 Compute the log-likelihood. More...
 
double getLogLikelihoodOne ()
 Compute the log-likelihood with one cluster. More...
 
double getEntropy ()
 Compute the entropy. More...
 
double getCompletedLogLikelihood ()
 Compute the completed log-likelihood. More...
 
double getCompletedLogLikelihoodOrLogLikelihood ()
 
int64_t getFreeParameter ()
 return the number of free parameters
 
double getLogN ()
 Selector. More...
 
void getLabelAndPartitionByMAPOrKnownPartition (int64_t *label, int64_t **partition)
 
int64_t getLabelByMAPOrKnownPartition (int64_t i)
 
int64_t getKnownLabel (int64_t i)
 
double ** getPostProba ()
 getPostProba
 
int64_t computeLabel (int64_t i0)
 Compute the label of the i0-th point of the sample. More...
 
int64_t computeLabel (Sample *x)
 Compute the label of new point x. More...
 
void MAPstep ()
 Maximum a posteriori step method.
 
void Estep ()
 Expectation step method.
 
void Mstep ()
 Maximization step method.
 
void Sstep ()
 Stochastic classification step method.
 
void Cstep ()
 Classification step method.
 
void initRANDOM (int64_t nbTry)
 Random center initialization of the parameters of the model.
 
void randomForInitRANDOMorUSER_PARTITION (bool *tabIndividualCanBeUsedForInitRandom, bool *tabClusterToInitialize)
 random step for init RANDOM or USER_PARTITION
 
void initUSER (Parameter *initParameter)
 User initialization of the parameters of the model.
 
void initUSER_PARTITION (Partition *initPartition, int64_t nbTryInInit=defaultNbTryInInit)
 User partition initialization of the parameters of the model.
 
void setParameter (Parameter *parameter)
 
void setAlgoName (AlgoName algoName)
 
AlgoName getAlgoName ()
 
void setError (Exception &errorType)
 
void FixKnownPartition (Partition *&y)
 Fix label Known.
 
void editDebugInformation ()
 
void editFik ()
 
void editCik ()
 
void editTik ()
 
void editNk ()
 

Detailed Description

Base class for Model(s)

Author
F Langrognet

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