The mean bias error performance function measures the network's performance according to the mean of errors. More...

Public Member Functions
	MeanBiasError ()
	Create the MeanBiasError object. 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...

template < typename PredictionType , typename TargetType >
PredictionType::elem_type	Forward (const PredictionType &prediction, const TargetType &target)
	Computes the mean bias error 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 uint32_t)
	Serialize the layer. More...

Detailed Description

template
<
typename
InputDataType
=
arma::mat
,
typename
OutputDataType
=
arma::mat
>

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

The mean bias error performance function measures the network's performance according to the mean of errors.

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 33 of file mean_bias_error.hpp.

Constructor & Destructor Documentation

◆ MeanBiasError()

MeanBiasError ( )

Create the MeanBiasError object.

Member Function Documentation

◆ Backward()

void 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()

PredictionType::elem_type Forward	(	const PredictionType &	prediction,
		const TargetType &	target
	)

Computes the mean bias error function.

Parameters

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

◆ OutputParameter() [1/2]

OutputDataType& OutputParameter ( ) const

inline

Get the output parameter.

Definition at line 66 of file mean_bias_error.hpp.

◆ OutputParameter() [2/2]

OutputDataType& OutputParameter ( )

inline

Modify the output parameter.

Definition at line 68 of file mean_bias_error.hpp.

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

◆ serialize()

void serialize	(	Archive &	ar,
		const uint32_t
	)

Serialize the layer.

Referenced by MeanBiasError< InputDataType, OutputDataType >::OutputParameter().

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

/home/ryan/src/mlpack.org/_src/mlpack-git/src/mlpack/methods/ann/loss_functions/mean_bias_error.hpp

Public Member Functions