The hinge loss function for the linear SVM objective function. More...

Public Member Functions
	LinearSVMFunction (const MatType &dataset, const arma::Row< size_t > &labels, const size_t numClasses, const double lambda=0.0001, const double delta=1.0, const bool fitIntercept=false)
	Construct the Linear SVM objective function with given parameters. More...

const arma::sp_mat &	Dataset () const
	Get the dataset. More...

arma::sp_mat &	Dataset ()
	Modify the dataset. More...

double	Evaluate (const arma::mat &parameters)
	Evaluate the hinge loss function for all the datapoints. More...

double	Evaluate (const arma::mat &parameters, const size_t firstId, const size_t batchSize=1)
	Evaluate the hinge loss function on the specified datapoints. More...

template < typename GradType >
double	EvaluateWithGradient (const arma::mat &parameters, GradType &gradient) const
	Evaluate the gradient of the hinge loss function, following the LinearFunctionType requirements on the Gradient function followed by evaluation of the hinge loss function on all the datapoints. More...

template < typename GradType >
double	EvaluateWithGradient (const arma::mat &parameters, const size_t firstId, GradType &gradient, const size_t batchSize=1) const
	Evaluate the gradient of the hinge loss function, following the LinearFunctionType requirements on the Gradient function followed by evaluation of the hinge loss function on the specified datapoints. More...

bool	FitIntercept () const
	Gets the intercept flag. More...

void	GetGroundTruthMatrix (const arma::Row< size_t > &labels, arma::sp_mat &groundTruth)
	Constructs the ground truth label matrix with the passed labels. More...

template < typename GradType >
void	Gradient (const arma::mat &parameters, GradType &gradient)
	Evaluate the gradient of the hinge loss function following the LinearFunctionType requirements on the Gradient function. More...

template < typename GradType >
void	Gradient (const arma::mat &parameters, const size_t firstId, GradType &gradient, const size_t batchSize=1)
	Evaluate the gradient of the hinge loss function, following the LinearFunctionType requirements on the Gradient function. More...

const arma::mat &	InitialPoint () const
	Return the initial point for the optimization. More...

arma::mat &	InitialPoint ()
	Modify the initial point for the optimization. More...

double &	Lambda ()
	Sets the regularization parameter. More...

double	Lambda () const
	Gets the regularization parameter. More...

size_t	NumFunctions () const
	Return the number of functions. More...

void	Shuffle ()
	Shuffle the dataset. More...

Static Public Member Functions
static void	InitializeWeights (arma::mat &weights, const size_t featureSize, const size_t numClasses, const bool fitIntercept=false)
	Initialize Linear SVM weights (trainable parameters) with the given parameters. More...

Detailed Description

template
<
typename
MatType
=
arma::mat
>

class mlpack::svm::LinearSVMFunction< MatType >

The hinge loss function for the linear SVM objective function.

This is used by various ensmallen optimizers to train the linear SVM model.

Definition at line 28 of file linear_svm_function.hpp.

Constructor & Destructor Documentation

◆ LinearSVMFunction()

LinearSVMFunction	(	const MatType &	dataset,
		const arma::Row< size_t > &	labels,
		const size_t	numClasses,
		const double	lambda = `0.0001`,
		const double	delta = `1.0`,
		const bool	fitIntercept = `false`
	)

Construct the Linear SVM objective function with given parameters.

Parameters

dataset	Input training data, each column associate with one sample
labels	Labels associated with the feature data.
numClasses	Number of classes for classification.
lambda	L2-regularization constant.
delta	Margin of difference between correct class and other classes.
fitIntercept	Intercept term flag.

Member Function Documentation

◆ Dataset() [1/2]

const arma::sp_mat& Dataset ( ) const

inline

Get the dataset.

Definition at line 166 of file linear_svm_function.hpp.

◆ Dataset() [2/2]

arma::sp_mat& Dataset ( )

inline

Modify the dataset.

Definition at line 168 of file linear_svm_function.hpp.

◆ Evaluate() [1/2]

double Evaluate ( const arma::mat & parameters )

Evaluate the hinge loss function for all the datapoints.

Parameters

parameters The parameters of the SVM.

Returns: The value of the loss function for the entire dataset.

◆ Evaluate() [2/2]

double Evaluate	(	const arma::mat &	parameters,
		const size_t	firstId,
		const size_t	batchSize = `1`
	)

Evaluate the hinge loss function on the specified datapoints.

Parameters

parameters	The parameters of the SVM.
firstId	Index of the datapoints to use for function evaluation.
batchSize	Size of batch to process.

Returns: The value of the loss function for the given parameters.

◆ EvaluateWithGradient() [1/2]

double EvaluateWithGradient	(	const arma::mat &	parameters,
		GradType &	gradient
	)		const

Evaluate the gradient of the hinge loss function, following the LinearFunctionType requirements on the Gradient function followed by evaluation of the hinge loss function on all the datapoints.

Template Parameters

GradType Type of the gradient matrix.

Parameters

parameters	The parameters of the SVM.
gradient	Linear matrix to output the gradient into.

Returns: The value of the loss function at the given parameters.

◆ EvaluateWithGradient() [2/2]

double EvaluateWithGradient	(	const arma::mat &	parameters,
		const size_t	firstId,
		GradType &	gradient,
		const size_t	batchSize = `1`
	)		const

Evaluate the gradient of the hinge loss function, following the LinearFunctionType requirements on the Gradient function followed by evaluation of the hinge loss function on the specified datapoints.

Template Parameters

GradType Type of the gradient matrix.

Parameters

parameters	The parameters of the SVM.
firstId	Index of the datapoint to use for the gradient and function evaluation.
gradient	Linear matrix to output the gradient into.
batchSize	Size of the batch to process.

Returns: The value of the loss function at the given parameters.

◆ FitIntercept()

bool FitIntercept ( ) const

inline

Gets the intercept flag.

Definition at line 176 of file linear_svm_function.hpp.

References LinearSVMFunction< MatType >::NumFunctions().

◆ GetGroundTruthMatrix()

void GetGroundTruthMatrix	(	const arma::Row< size_t > &	labels,
		arma::sp_mat &	groundTruth
	)

Constructs the ground truth label matrix with the passed labels.

Parameters

labels	Labels associated with the training data.
groundTruth	Pointer to arma::mat which stores the computed matrix.

◆ Gradient() [1/2]

void Gradient	(	const arma::mat &	parameters,
		GradType &	gradient
	)

Evaluate the gradient of the hinge loss function following the LinearFunctionType requirements on the Gradient function.

Template Parameters

GradType Type of the gradient matrix.

Parameters

parameters	The parameters of the SVM.
gradient	Linear matrix to output the gradient into.

◆ Gradient() [2/2]

void Gradient	(	const arma::mat &	parameters,
		const size_t	firstId,
		GradType &	gradient,
		const size_t	batchSize = `1`
	)

Evaluate the gradient of the hinge loss function, following the LinearFunctionType requirements on the Gradient function.

Template Parameters

GradType Type of the gradient matrix.

Parameters

parameters	The parameters of the SVM.
firstId	Index of the datapoint to use for the gradient evaluation.
gradient	Linear matrix to output the gradient into.
batchSize	Size of the batch to process.

◆ InitializeWeights()

static void InitializeWeights	(	arma::mat &	weights,
		const size_t	featureSize,
		const size_t	numClasses,
		const bool	fitIntercept = `false`
	)

static

Initialize Linear SVM weights (trainable parameters) with the given parameters.

Parameters

weights	This will be filled with the initialized model weights.
featureSize	The number of features in the training set.
numClasses	Number of classes for classification.
fitIntercept	If true, an intercept is fitted.

◆ InitialPoint() [1/2]

const arma::mat& InitialPoint ( ) const

inline

Return the initial point for the optimization.

Definition at line 161 of file linear_svm_function.hpp.

◆ InitialPoint() [2/2]

arma::mat& InitialPoint ( )

inline

Modify the initial point for the optimization.

Definition at line 163 of file linear_svm_function.hpp.

◆ Lambda() [1/2]

double& Lambda ( )

inline

Sets the regularization parameter.

Definition at line 171 of file linear_svm_function.hpp.

◆ Lambda() [2/2]

double Lambda ( ) const

inline

Gets the regularization parameter.

Definition at line 173 of file linear_svm_function.hpp.

◆ NumFunctions()

size_t NumFunctions ( ) const

Return the number of functions.

Referenced by LinearSVMFunction< MatType >::FitIntercept().

◆ Shuffle()

void Shuffle ( )

Shuffle the dataset.

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

/home/ryan/src/mlpack.org/_src/mlpack-git/src/mlpack/methods/linear_svm/linear_svm_function.hpp

Public Member Functions

Static Public Member Functions

Detailed Description

template<typenameMatType=arma::mat> class mlpack::svm::LinearSVMFunction< MatType >

Constructor & Destructor Documentation

◆ LinearSVMFunction()

Member Function Documentation

◆ Dataset() [1/2]

◆ Dataset() [2/2]

◆ Evaluate() [1/2]

◆ Evaluate() [2/2]

◆ EvaluateWithGradient() [1/2]

◆ EvaluateWithGradient() [2/2]

◆ FitIntercept()

◆ GetGroundTruthMatrix()

◆ Gradient() [1/2]

◆ Gradient() [2/2]

◆ InitializeWeights()

◆ InitialPoint() [1/2]

◆ InitialPoint() [2/2]

◆ Lambda() [1/2]

◆ Lambda() [2/2]

◆ NumFunctions()

◆ Shuffle()

template
<
typename
MatType
=
arma::mat
>

class mlpack::svm::LinearSVMFunction< MatType >