class NLLCriterion

This criterion can be used to train Distribution object using the GMTrainer trainer.

Inheritance:


Public Methods

[more] NLLCriterion()


Inherited from Criterion:

Public Fields

oDataSet* data

Public Methods

ovirtual void setDataSet(DataSet* data_)


Inherited from GradientMachine:

Public Fields

oint n_inputs
oint n_outputs
oParameters* params
oParameters* der_params
oSequence* beta

Public Methods

ovirtual void iterInitialize()
ovirtual void forward(Sequence* inputs)
ovirtual void backward(Sequence* inputs, Sequence* alpha)
ovirtual void setPartialBackprop(bool flag=true)
ovirtual void frameForward(int t, real* f_inputs, real* f_outputs)
ovirtual void frameBackward(int t, real* f_inputs, real* beta_, real* f_outputs, real* alpha_)
ovirtual void loadXFile(XFile* file)
ovirtual void saveXFile(XFile* file)


Inherited from Machine:

Public Fields

oSequence* outputs

Public Methods

ovirtual void reset()


Inherited from Object:

Public Fields

oAllocator* allocator

Public Methods

ovoid addOption(const char* name, int size, void* ptr, const char* help="")
ovoid addIOption(const char* name, int* ptr, int init_value, const char* help="")
ovoid addROption(const char* name, real* ptr, real init_value, const char* help="")
ovoid addBOption(const char* name, bool* ptr, bool init_value, const char* help="")
ovoid addOOption(const char* name, Object** ptr, Object* init_value, const char* help="")
ovoid setOption(const char* name, void* ptr)
ovoid setIOption(const char* name, int option)
ovoid setROption(const char* name, real option)
ovoid setBOption(const char* name, bool option)
ovoid setOOption(const char* name, Object* option)
ovoid load(const char* filename)
ovoid save(const char* filename)
ovoid* operator new(size_t size, Allocator* allocator_=NULL)
ovoid* operator new(size_t size, Allocator* allocator_, void* ptr_)
ovoid operator delete(void* ptr)


Documentation

This criterion can be used to train Distribution object using the GMTrainer trainer. It then maximizes the log likelihood of the data.

The forward method always return its input, which is the negative log likelihood, while the backward method sets the gradient to -1.

o NLLCriterion()


This class has no child classes.
Author:
Samy Bengio (bengio@idiap.ch)

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