0-1-loss for classification. More...

#include <shark/ObjectiveFunctions/Loss/ZeroOneLoss.h>

Inheritance diagram for shark::ZeroOneLoss< LabelType, OutputType >:

Public Types
typedef base_type::BatchLabelType	BatchLabelType

typedef base_type::BatchOutputType	BatchOutputType

Public Types inherited from shark::AbstractLoss< LabelT, OutputT >
typedef OutputT	OutputType

typedef LabelT	LabelType

typedef RealMatrix	MatrixType

typedef Batch< OutputType >::type	BatchOutputType

typedef Batch< LabelType >::type	BatchLabelType

typedef ConstProxyReference< LabelTypeconst >::type	ConstLabelReference
	Const references to LabelType.

typedef ConstProxyReference< OutputTypeconst >::type	ConstOutputReference
	Const references to OutputType.

Public Types inherited from shark::AbstractCost< LabelT, OutputT >
enum	Feature { HAS_FIRST_DERIVATIVE = 1 , HAS_SECOND_DERIVATIVE = 2 , IS_LOSS_FUNCTION = 4 }
	list of features a cost function can have More...

typedef OutputT	OutputType

typedef LabelT	LabelType

typedef Batch< OutputType >::type	BatchOutputType

typedef Batch< LabelType >::type	BatchLabelType

typedef TypedFlags< Feature >	Features

typedef TypedFeatureNotAvailableException< Feature >	FeatureNotAvailableException

Public Member Functions
	ZeroOneLoss ()
	constructor

std::string	name () const
	From INameable: return the class name.

double	eval (BatchLabelType const &labels, BatchOutputType const &predictions) const
	Return zero if labels == predictions and one otherwise.

virtual double	eval (BatchLabelType const &target, BatchOutputType const &prediction) const=0
	evaluate the loss for a batch of targets and a prediction

virtual double	eval (ConstLabelReference target, ConstOutputReference prediction) const
	evaluate the loss for a target and a prediction

double	eval (Data< LabelType > const &targets, Data< OutputType > const &predictions) const

Public Member Functions inherited from shark::AbstractLoss< LabelT, OutputT >
	AbstractLoss ()

virtual double	evalDerivative (ConstLabelReference target, ConstOutputReference prediction, OutputType &gradient) const
	evaluate the loss and its derivative for a target and a prediction

virtual double	evalDerivative (ConstLabelReference target, ConstOutputReference prediction, OutputType &gradient, MatrixType &hessian) const
	evaluate the loss and its first and second derivative for a target and a prediction

virtual double	evalDerivative (BatchLabelType const &target, BatchOutputType const &prediction, BatchOutputType &gradient) const
	evaluate the loss and the derivative w.r.t. the prediction

double	operator() (LabelType const &target, OutputType const &prediction) const
	evaluate the loss for a target and a prediction

double	operator() (BatchLabelType const &target, BatchOutputType const &prediction) const

Public Member Functions inherited from shark::AbstractCost< LabelT, OutputT >
virtual	~AbstractCost ()

const Features &	features () const

virtual void	updateFeatures ()

bool	hasFirstDerivative () const
	returns true when the first parameter derivative is implemented

bool	isLossFunction () const
	returns true when the cost function is in fact a loss function

double	operator() (Data< LabelType > const &targets, Data< OutputType > const &predictions) const

Public Member Functions inherited from shark::INameable
virtual	~INameable ()

Additional Inherited Members
Protected Attributes inherited from shark::AbstractCost< LabelT, OutputT >
Features	m_features

Detailed Description

template<class LabelType = unsigned int, class OutputType = LabelType>
class shark::ZeroOneLoss< LabelType, OutputType >

0-1-loss for classification.

The ZeroOneLoss requires the existence of the comparison operator == for its LabelType template parameter. The loss function returns zero of the predictions exactly matches the label, and one otherwise.

Definition at line 51 of file ZeroOneLoss.h.

Member Typedef Documentation

◆ BatchLabelType

template<class LabelType = unsigned int, class OutputType = LabelType>

typedef base_type::BatchLabelType shark::ZeroOneLoss< LabelType, OutputType >::BatchLabelType

Definition at line 55 of file ZeroOneLoss.h.

◆ BatchOutputType

template<class LabelType = unsigned int, class OutputType = LabelType>

typedef base_type::BatchOutputType shark::ZeroOneLoss< LabelType, OutputType >::BatchOutputType

Definition at line 56 of file ZeroOneLoss.h.

Constructor & Destructor Documentation

◆ ZeroOneLoss()

template<class LabelType = unsigned int, class OutputType = LabelType>

shark::ZeroOneLoss< LabelType, OutputType >::ZeroOneLoss ( )

inline

constructor

Definition at line 59 of file ZeroOneLoss.h.

Member Function Documentation

◆ eval() [1/4]

template<class LabelType = unsigned int, class OutputType = LabelType>

double shark::ZeroOneLoss< LabelType, OutputType >::eval	(	BatchLabelType const &	labels,
		BatchOutputType const &	predictions
	)		const

inlinevirtual

Return zero if labels == predictions and one otherwise.

Implements shark::AbstractLoss< LabelT, OutputT >.

Definition at line 70 of file ZeroOneLoss.h.

References SIZE_CHECK.

Referenced by main(), main(), and run_one_trial().

◆ eval() [2/4]

template<class LabelType = unsigned int, class OutputType = LabelType>

virtual double shark::AbstractLoss< LabelT, OutputT >::eval	(	BatchLabelType const &	target,
		BatchOutputType const &	prediction
	)		const

virtual

evaluate the loss for a batch of targets and a prediction

Parameters

target	target values
prediction	predictions, typically made by a model

Implements shark::AbstractLoss< LabelT, OutputT >.

◆ eval() [3/4]

template<class LabelType = unsigned int, class OutputType = LabelType>

virtual double shark::AbstractLoss< LabelT, OutputT >::eval	(	ConstLabelReference	target,
		ConstOutputReference	prediction
	)		const

inlinevirtual

evaluate the loss for a target and a prediction

Parameters

target	target value
prediction	prediction, typically made by a model

Reimplemented from shark::AbstractLoss< LabelT, OutputT >.

Definition at line 92 of file AbstractLoss.h.

◆ eval() [4/4]

template<class LabelType = unsigned int, class OutputType = LabelType>

double shark::AbstractLoss< LabelT, OutputT >::eval	(	Data< LabelType > const &	targets,
		Data< OutputType > const &	predictions
	)		const

inlinevirtual

from AbstractCost

Parameters

targets	target values
predictions	predictions, typically made by a model

Reimplemented from shark::AbstractLoss< LabelT, OutputT >.

Definition at line 149 of file AbstractLoss.h.

◆ name()

template<class LabelType = unsigned int, class OutputType = LabelType>

std::string shark::ZeroOneLoss< LabelType, OutputType >::name ( ) const

inlinevirtual

From INameable: return the class name.

Reimplemented from shark::INameable.

Definition at line 64 of file ZeroOneLoss.h.

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

include/shark/ObjectiveFunctions/Loss/ZeroOneLoss.h

Public Types

Public Member Functions

Additional Inherited Members

Detailed Description

Member Typedef Documentation

◆ BatchLabelType

◆ BatchOutputType

Constructor & Destructor Documentation

◆ ZeroOneLoss()

Member Function Documentation

◆ eval() [1/4]

◆ eval() [2/4]

◆ eval() [3/4]

◆ eval() [4/4]

◆ name()