CrossEntropyError< InputDataType, OutputDataType > Class Template Reference

The cross-entropy performance function measures the network's performance according to the cross-entropy between the input and target distributions. More...

Public Member Functions
	CrossEntropyError (const double eps=1e-10)
	Create the CrossEntropyError object. More...
template < typename InputType , typename TargetType , typename OutputType >
void	Backward (const InputType &&input, const TargetType &&target, OutputType &&output)
	Ordinary feed backward pass of a neural network. More...
double	Eps () const
	Get the epsilon. More...
double &	Eps ()
	Modify the epsilon. More...
template < typename InputType , typename TargetType >
double	Forward (const InputType &&input, const TargetType &&target)
	Computes the cross-entropy function. More...
OutputDataType &	OutputParameter () const
	Get the output parameter. More...
OutputDataType &	OutputParameter ()
	Modify the output parameter. More...
template < typename Archive >
void	serialize (Archive &ar, const unsigned int)
	Serialize the layer. More...

Detailed Description

template

<

typename

InputDataType

=

arma::mat

,

typename

OutputDataType

=

arma::mat

>

class mlpack::ann::CrossEntropyError< InputDataType, OutputDataType >

The cross-entropy performance function measures the network's performance according to the cross-entropy between the input and target distributions.

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).

Definition at line 34 of file cross_entropy_error.hpp.

Constructor & Destructor Documentation

CrossEntropyError()

CrossEntropyError

(

const double

eps = 1e-10

)

Create the CrossEntropyError object.

Parameters

eps	The minimum value used for computing logarithms and denominators in a numerically stable way.

Member Function Documentation

Backward()

void Backward	(	const InputType &&	input,
		const TargetType &&	target,
		OutputType &&	output
	)

Ordinary feed backward pass of a neural network.

Parameters

input	The propagated input activation.
target	The target vector.
output	The calculated error.

Eps() [1/2]

double Eps ( ) const

inline

Get the epsilon.

Definition at line 72 of file cross_entropy_error.hpp.

Eps() [2/2]

double& Eps ( )

inline

Modify the epsilon.

Definition at line 74 of file cross_entropy_error.hpp.

References CrossEntropyError< InputDataType, OutputDataType >::serialize().

Forward()

double Forward	(	const InputType &&	input,
		const TargetType &&	target
	)

Computes the cross-entropy function.

Parameters

input	Input data used for evaluating the specified function.
target	The target vector.

OutputParameter() [1/2]

OutputDataType& OutputParameter ( ) const

inline

Get the output parameter.

Definition at line 67 of file cross_entropy_error.hpp.

OutputParameter() [2/2]

OutputDataType& OutputParameter ( )

inline

Modify the output parameter.

Definition at line 69 of file cross_entropy_error.hpp.

serialize()

void serialize	(	Archive &	ar,
		const unsigned	int
	)

Serialize the layer.

Referenced by CrossEntropyError< InputDataType, OutputDataType >::Eps().

---

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

• /home/jenkins-mlpack/mlpack.org/_src/mlpack-3.2.1/src/mlpack/methods/ann/loss_functions/cross_entropy_error.hpp