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

Public Member Functions
	MeanSquaredError ()
	Create the MeanSquaredError object. More...

template
void	Backward (const InputType &input, const TargetType &target, OutputType &output)
	Ordinary feed backward pass of a neural network. More...

template
InputType::elem_type	Forward (const InputType &input, const TargetType &target)
	Computes the mean squared error function. More...

OutputDataType &	OutputParameter () const
	Get the output parameter. More...

OutputDataType &	OutputParameter ()
	Modify the output parameter. More...

template
void	serialize (Archive &ar, const unsigned int)
	Serialize the layer. More...

Detailed Description

template
class mlpack::ann::MeanSquaredError< InputDataType, OutputDataType >

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

Template Parameters

ActivationFunction	Activation function used for the embedding layer.
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).

Definition at line 34 of file mean_squared_error.hpp.

Constructor & Destructor Documentation

◆ MeanSquaredError()

MeanSquaredError ( )

Create the MeanSquaredError object.

Member Function Documentation

◆ Backward()

void Backward	(	const InputType &	input,
		const TargetType &	target,
		OutputType &	output
	)

Ordinary feed backward pass of a neural network.

Parameters

input	The propagated input activation.
target	The target vector.
output	The calculated error.

◆ Forward()

InputType::elem_type Forward	(	const InputType &	input,
		const TargetType &	target
	)

Computes the mean squared error function.

Parameters

input	Input data used for evaluating the specified function.
target	The target vector.

◆ OutputParameter() [1/2]

OutputDataType& OutputParameter ( ) const

inline

Get the output parameter.

Definition at line 65 of file mean_squared_error.hpp.

◆ OutputParameter() [2/2]

OutputDataType& OutputParameter ( )

inline

Modify the output parameter.

Definition at line 67 of file mean_squared_error.hpp.

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

◆ serialize()

void serialize	(	Archive &	ar,
		const unsigned	int
	)

Serialize the layer.

Referenced by MeanSquaredError< InputDataType, OutputDataType >::OutputParameter().

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

/home/jenkins-mlpack/mlpack.org/_src/mlpack-3.4.2/src/mlpack/methods/ann/loss_functions/mean_squared_error.hpp

Public Member Functions