12 #ifndef MLPACK_METHODS_ANN_LOSS_FUNCTION_MEAN_BIAS_ERROR_HPP 13 #define MLPACK_METHODS_ANN_LOSS_FUNCTION_MEAN_BIAS_ERROR_HPP 30 typename InputDataType = arma::mat,
31 typename OutputDataType = arma::mat
47 template<
typename InputType,
typename TargetType>
48 typename InputType::elem_type
Forward(
const InputType& input,
49 const TargetType& target);
58 template<
typename InputType,
typename TargetType,
typename OutputType>
59 void Backward(
const InputType& input,
60 const TargetType& target,
71 template<
typename Archive>
72 void serialize(Archive& ar,
const unsigned int );
76 OutputDataType outputParameter;
83 #include "mean_bias_error_impl.hpp" OutputDataType & OutputParameter() const
Get the output parameter.
Linear algebra utility functions, generally performed on matrices or vectors.
OutputDataType & OutputParameter()
Modify the output parameter.
The core includes that mlpack expects; standard C++ includes and Armadillo.
void serialize(Archive &ar, const unsigned int)
Serialize the layer.
The mean bias error performance function measures the network's performance according to the mean of ...
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 bias error function.
MeanBiasError()
Create the MeanBiasError object.