mlpack::ann::BCELoss< InputDataType, OutputDataType > Class Template Reference

The binary-cross-entropy performance function measures the Binary Cross Entropy between the target and the output. More...

#include <binary_cross_entropy_loss.hpp>

Public Member Functions
	BCELoss (const double eps=1e-10, const bool reduction=true)
	Create the BinaryCrossEntropyLoss object. More...
template<typename PredictionType , typename TargetType >
PredictionType::elem_type	Forward (const PredictionType &prediction, const TargetType &target)
	Computes the cross-entropy function. More...
template<typename PredictionType , typename TargetType , typename LossType >
void	Backward (const PredictionType &prediction, const TargetType &target, LossType &loss)
	Ordinary feed backward pass of a neural network. More...
OutputDataType &	OutputParameter () const
	Get the output parameter.
OutputDataType &	OutputParameter ()
	Modify the output parameter.
double	Eps () const
	Get the epsilon.
double &	Eps ()
	Modify the epsilon.
bool	Reduction () const
	Get the reduction.
bool &	Reduction ()
	Set the reduction.
template<typename Archive >
void	serialize (Archive &ar, const uint32_t)
	Serialize the layer.

Detailed Description

template<typename InputDataType = arma::mat, typename OutputDataType = arma::mat>
class mlpack::ann::BCELoss< InputDataType, OutputDataType >

The binary-cross-entropy performance function measures the Binary Cross Entropy between the target and the output.

Template Parameters

InputDataType	Type of the input data (arma::colvec, arma::mat, arma::sp_mat or arma::cube).
OutputDataType	Type of the output data (arma::colvec, arma::mat, arma::sp_mat or arma::cube).

Constructor & Destructor Documentation

BCELoss()

template<typename InputDataType , typename OutputDataType >

mlpack::ann::BCELoss< InputDataType, OutputDataType >::BCELoss	(	const double	eps = 1e-10,
		const bool	reduction = true
	)

Create the BinaryCrossEntropyLoss object.

Parameters

eps	The minimum value used for computing logarithms and denominators in a numerically stable way.
reduction	Reduction type. If true, it returns the mean of the loss. Else, it returns the sum.

Member Function Documentation

Backward()

template<typename InputDataType , typename OutputDataType >

template<typename PredictionType , typename TargetType , typename LossType >

void mlpack::ann::BCELoss< InputDataType, OutputDataType >::Backward	(	const PredictionType &	prediction,
		const TargetType &	target,
		LossType &	loss
	)

Ordinary feed backward pass of a neural network.

Parameters

prediction	Predictions used for evaluating the specified loss function.
target	The target vector.
loss	The calculated error.

Forward()

template<typename InputDataType , typename OutputDataType >

template<typename PredictionType , typename TargetType >

PredictionType::elem_type mlpack::ann::BCELoss< InputDataType, OutputDataType >::Forward	(	const PredictionType &	prediction,
		const TargetType &	target
	)

Computes the cross-entropy function.

Parameters

prediction	Predictions used for evaluating the specified loss function.
target	The target vector.

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

• src/mlpack/methods/ann/loss_functions/binary_cross_entropy_loss.hpp
• src/mlpack/methods/ann/loss_functions/binary_cross_entropy_loss_impl.hpp