MeanBiasError< InputDataType, OutputDataType > Class Template Reference

The mean bias error performance function measures the network's performance according to the mean of errors. More...

Public Member Functions

 MeanBiasError ()
 Create the MeanBiasError 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 bias 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 uint32_t)
 Serialize the layer. More...

 

Detailed Description


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

class mlpack::ann::MeanBiasError< InputDataType, OutputDataType >

The mean bias error performance function measures the network's performance according to the mean of errors.

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 33 of file mean_bias_error.hpp.

Constructor & Destructor Documentation

◆ MeanBiasError()

Create the MeanBiasError object.

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 bias 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 66 of file mean_bias_error.hpp.

◆ OutputParameter() [2/2]

OutputDataType& OutputParameter ( )
inline

Modify the output parameter.

Definition at line 68 of file mean_bias_error.hpp.

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

◆ serialize()

void serialize ( Archive &  ar,
const uint32_t   
)

The documentation for this class was generated from the following file:
  • /home/jenkins-mlpack/mlpack.org/_src/mlpack-git/src/mlpack/methods/ann/loss_functions/mean_bias_error.hpp