12#ifndef MLPACK_METHODS_ANN_LOSS_FUNCTION_MEAN_ABSOLUTE_PERCENTAGE_ERROR_HPP
13#define MLPACK_METHODS_ANN_LOSS_FUNCTION_MEAN_ABSOLUTE_PERCENTAGE_ERROR_HPP
46 typename InputDataType = arma::mat,
47 typename OutputDataType = arma::mat
63 template<
typename InputType,
typename TargetType>
64 typename InputType::elem_type
Forward(
const InputType& input,
65 const TargetType& target);
74 template<
typename InputType,
typename TargetType,
typename OutputType>
76 const TargetType& target,
87 template<
typename Archive>
92 OutputDataType outputParameter;
99#include "mean_absolute_percentage_error_impl.hpp"
The mean absolute percentage error performance function measures the network's performance according ...
MeanAbsolutePercentageError()
Create the MeanAbsolutePercentageError object.
OutputDataType & OutputParameter() const
Get the output parameter.
void Backward(const InputType &input, const TargetType &target, OutputType &output)
Ordinary feed backward pass of a neural network.
InputType::elem_type Forward(const InputType &input, const TargetType &target)
Computes the mean absolute percentage error function.
OutputDataType & OutputParameter()
Modify the output parameter.
void serialize(Archive &ar, const unsigned int)
Serialize the layer.
Linear algebra utility functions, generally performed on matrices or vectors.
The core includes that mlpack expects; standard C++ includes and Armadillo.