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...

Public Member Functions

 MeanAbsolutePercentageError ()
 Create the MeanAbsolutePercentageError 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 absolute percentage 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 unsigned int)
 Serialize the layer. More...

 

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
InputDataTypeType of the input data (arma::colvec, arma::mat, arma::sp_mat or arma::cube).
OutputDataTypeType 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()

Member Function Documentation

◆ Backward()

void Backward ( const PredictionType &  prediction,
const TargetType &  target,
LossType &  loss 
)

Ordinary feed backward pass of a neural network.

Parameters
predictionPredictions used for evaluating the specified loss function.
targetThe target vector.
lossThe calculated error.

◆ Forward()

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

Computes the mean absolute percentage error function.

Parameters
predictionPredictions used for evaluating the specified loss function.
targetThe target vector.

◆ OutputParameter() [1/2]

OutputDataType& OutputParameter ( ) const
inline

Get the output parameter.

Definition at line 82 of file mean_absolute_percentage_error.hpp.

◆ OutputParameter() [2/2]

OutputDataType& OutputParameter ( )
inline

Modify the output parameter.

Definition at line 84 of file mean_absolute_percentage_error.hpp.

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

◆ serialize()

void serialize ( Archive &  ar,
const unsigned  int 
)

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