The mean absolute percentage error performance function measures the network's performance according to the mean of the absolute difference between input and target divided by target. More...

Public Member Functions
	MeanAbsolutePercentageError ()
	Create the MeanAbsolutePercentageError object. More...

template
void	Backward (const InputType &input, const TargetType &target, OutputType &output)
	Ordinary feed backward pass of a neural network. More...

template
InputType::elem_type	Forward (const InputType &input, const TargetType &target)
	Computes the mean absolute percentage error function. More...

OutputDataType &	OutputParameter () const
	Get the output parameter. More...

OutputDataType &	OutputParameter ()
	Modify the output parameter. More...

template
void	serialize (Archive &ar, const unsigned int)
	Serialize the layer. More...

Detailed Description

template
class mlpack::ann::MeanAbsolutePercentageError< InputDataType, OutputDataType >

The mean absolute percentage error performance function measures the network's performance according to the mean of the absolute difference between input and target divided by target.

For more information, refer to the following paper,

@article{de_Myttenaere_2016,
   author    = {de Myttenaere, Arnaud and Golden, Boris and Le Grand,
                Bénédicte and Rossi, Fabrice},
   title     = {Mean Absolute Percentage Error for regression models},
   journal   = {Neurocomputing},
   volume    = {abs/1605.02541},
   year      = {2016},
   url       = {https://arxiv.org/abs/1605.02541},
   eprint    = {1605.02541},
}

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 49 of file mean_absolute_percentage_error.hpp.

Constructor & Destructor Documentation

◆ MeanAbsolutePercentageError()

MeanAbsolutePercentageError ( )

Create the MeanAbsolutePercentageError object.

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.

◆ Forward()

InputType::elem_type Forward	(	const InputType &	input,
		const TargetType &	target
	)

Computes the mean absolute percentage error 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 80 of file mean_absolute_percentage_error.hpp.

◆ OutputParameter() [2/2]

OutputDataType& OutputParameter ( )

inline

Modify the output parameter.

Definition at line 82 of file mean_absolute_percentage_error.hpp.

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

◆ serialize()

void serialize	(	Archive &	ar,
		const unsigned	int
	)

Serialize the layer.

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

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

/home/jenkins-mlpack/mlpack.org/_src/mlpack-3.4.2/src/mlpack/methods/ann/loss_functions/mean_absolute_percentage_error.hpp

Public Member Functions