HingeLoss< InputDataType, OutputDataType > Class Template Reference

Computes the hinge loss between and . More...

Public Member Functions
	HingeLoss (const bool reduction=true)
	Create HingeLoss 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 Hinge loss function. More...
OutputDataType &	OutputParameter () const
	Get the output parameter. More...
OutputDataType &	OutputParameter ()
	Modify the output parameter. More...
bool	Reduction () const
	Get the type of reduction used. More...
bool &	Reduction ()
	Modify the type of reduction used. 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::HingeLoss< InputDataType, OutputDataType >

Computes the hinge loss between and .

Expects to be either -1 or 1. If is either 0 or 1, a temporary conversion is made to calculate the loss. The hinge loss is defined as .

Template Parameters

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 37 of file hinge_loss.hpp.

Constructor & Destructor Documentation

HingeLoss()

HingeLoss

(

const bool

reduction = true

)

Create HingeLoss object.

Parameters

reduction

Specifies the reduction to apply to the output. If false, 'mean' reduction is used, where sum of the output will be divided by the number of elements in the output. If true, 'sum' reduction is used and the output will be summed. It is set to true by default.

Member Function Documentation

Backward()

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

Ordinary feed backward pass of a neural network.

Parameters

prediction	Prediction used for evaluating the specified loss function.
target	The target vector.
loss	The calculated error.

Forward()

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

Computes the Hinge loss function.

Parameters

prediction	Prediction used for evaluating the specified loss function.
target	Target data to compare with.

OutputParameter() [1/2]

OutputDataType& OutputParameter ( ) const

inline

Get the output parameter.

Definition at line 76 of file hinge_loss.hpp.

OutputParameter() [2/2]

OutputDataType& OutputParameter ( )

inline

Modify the output parameter.

Definition at line 78 of file hinge_loss.hpp.

Reduction() [1/2]

bool Reduction ( ) const

inline

Get the type of reduction used.

Definition at line 81 of file hinge_loss.hpp.

Reduction() [2/2]

bool& Reduction ( )

inline

Modify the type of reduction used.

Definition at line 83 of file hinge_loss.hpp.

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

serialize()

void serialize	(	Archive &	ar,
		const uint32_t
	)

Serialize the layer.

Referenced by HingeLoss< InputDataType, OutputDataType >::Reduction().

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

• /home/ryan/src/mlpack.org/_src/mlpack-git/src/mlpack/methods/ann/loss_functions/hinge_loss.hpp