class EMTrainer

This class is used to train any distribution using the EM algorithm.

Inheritance:

Public Fields

Distribution* distribution

the distribution to train

real end_accuracy

the stopping criterion regarding the accuracy for EM

int max_iter

the stopping criterion regarding the number of iterations for EM

bool viterbi

when viterbi is true, use Viterbi training instead of EM training

Public Methods

EMTrainer(Distribution* distribution_)

virtual void decode(MeasurerList* measurers)

this method computes the most likely path into the distribution.

Inherited from Trainer:

Public Methods

virtual void train(DataSet* data_, MeasurerList* measurers)

virtual void test(MeasurerList* measurers)

static Allocator* extractMeasurers(MeasurerList* measurers, DataSet* train, DataSet*** datas, Measurer**** meas, int** n_meas, int* n_datas)

virtual void loadXFile(XFile* file)

virtual void saveXFile(XFile* file)

Inherited from Object:

Public Fields

Allocator* allocator

Public Methods

void addOption(const char* name, int size, void* ptr, const char* help="")

void addIOption(const char* name, int* ptr, int init_value, const char* help="")

void addROption(const char* name, real* ptr, real init_value, const char* help="")

void addBOption(const char* name, bool* ptr, bool init_value, const char* help="")

void addOOption(const char* name, Object** ptr, Object* init_value, const char* help="")

void setOption(const char* name, void* ptr)

void setIOption(const char* name, int option)

void setROption(const char* name, real option)

void setBOption(const char* name, bool option)

void setOOption(const char* name, Object* option)

void load(const char* filename)

void save(const char* filename)

void* operator new(size_t size, Allocator* allocator_=NULL)

void* operator new(size_t size, Allocator* allocator_, void* ptr_)

void operator delete(void* ptr)

Documentation

This class is used to train any distribution using the EM algorithm. It can also train using the Viterbi training algorithm.

Distribution* distribution

the distribution to train

real end_accuracy

the stopping criterion regarding the accuracy for EM

int max_iter

the stopping criterion regarding the number of iterations for EM

bool viterbi

when viterbi is true, use Viterbi training instead of EM training

EMTrainer(Distribution* distribution_)

virtual void decode(MeasurerList* measurers)

this method computes the most likely path into the distribution. mainly used for sequential distribution such as HMMs.

This class has no child classes.

Author:

Samy Bengio (bengio@idiap.ch)

Alphabetic index HTML hierarchy of classes or Java