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

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...

#include <mean_absolute_percentage_error.hpp>

Public Member Functions
	MeanAbsolutePercentageError ()
	Create the MeanAbsolutePercentageError object.
template<typename PredictionType , typename TargetType >
PredictionType::elem_type	Forward (const PredictionType &prediction, const TargetType &target)
	Computes the mean absolute percentage error 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.
template<typename Archive >
void	serialize (Archive &ar, const unsigned int)
	Serialize the layer.

Detailed Description

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

Member Function Documentation

Backward()

template<typename InputDataType , typename OutputDataType >

template<typename PredictionType , typename TargetType , typename LossType >

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

Computes the mean absolute percentage error 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/mean_absolute_percentage_error.hpp
• src/mlpack/methods/ann/loss_functions/mean_absolute_percentage_error_impl.hpp