class NPTrainer

Trainer for Non Parametric Machines.

Inheritance:

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

Trainer for Non Parametric Machines. This trainer does nothing during training! But it can be used to test Non Parametric models such as KNN or ParzenDistributions or even select a correct hyper-parameter using cross-validation.

This class has no child classes.

Author:

Samy Bengio (bengio@idiap.ch)

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