#include <shark/Models/OneVersusOneClassifier.h>

Inheritance diagram for shark::OneVersusOneClassifier< InputType, VectorType >:

Public Types
typedef base_type::BatchInputType	BatchInputType

typedef base_type::BatchOutputType	BatchOutputType

Public Types inherited from shark::AbstractModel< InputTypeT, OutputTypeT, ParameterVectorType >
enum	Feature { HAS_FIRST_PARAMETER_DERIVATIVE = 1 , HAS_FIRST_INPUT_DERIVATIVE = 4 }

typedef InputTypeT	InputType
	Defines the input type of the model.

typedef OutputTypeT	OutputType
	Defines the output type of the model.

typedef AbstractModel< InputTypeT, OutputTypeT, ParameterVectorType >	ModelBaseType
	Defines the BaseType used by the model (this type). Useful for creating derived models.

typedef Batch< InputType >::type	BatchInputType
	defines the batch type of the input type.

typedef Batch< OutputType >::type	BatchOutputType
	defines the batch type of the output type

typedef TypedFlags< Feature >	Features

typedef TypedFeatureNotAvailableException< Feature >	FeatureNotAvailableException

Public Types inherited from shark::IParameterizable< VectorType >
typedef VectorType	ParameterVectorType

Public Member Functions
	OneVersusOneClassifier ()
	Constructor.

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

virtual VectorType	parameterVector () const
	get internal parameters of the model

virtual void	setParameterVector (VectorType const &newParameters)
	set internal parameters of the model

virtual std::size_t	numberOfParameters () const
	return the size of the parameter vector

unsigned int	numberOfClasses () const
	return number of classes

Shape	inputShape () const
	Returns the expected shape of the input.

Shape	outputShape () const
	Returns the shape of the output.

binary_classifier_type const &	binary (unsigned int class_one, unsigned int class_zero) const
	Obtain binary classifier.

void	addClass (std::vector< binary_classifier_type * > const &binmodels)
	Add binary classifiers for one more class to the model.

boost::shared_ptr< State >	createState () const
	Creates an internal state of the model.

void	eval (BatchInputType const &patterns, BatchOutputType &output, State &state) const

void	read (InArchive &archive)
	from ISerializable, reads a model from an archive

void	write (OutArchive &archive) const
	from ISerializable, writes a model to an archive

virtual void	eval (BatchInputType const &patterns, BatchOutputType &outputs) const
	Standard interface for evaluating the response of the model to a batch of patterns.

virtual void	eval (BatchInputType const &patterns, BatchOutputType &outputs, State &state) const=0
	Standard interface for evaluating the response of the model to a batch of patterns.

virtual void	eval (InputType const &pattern, OutputType &output) const
	Standard interface for evaluating the response of the model to a single pattern.

Public Member Functions inherited from shark::AbstractModel< InputTypeT, OutputTypeT, ParameterVectorType >
	AbstractModel ()

virtual	~AbstractModel ()

const Features &	features () const

virtual void	updateFeatures ()

bool	hasFirstParameterDerivative () const
	Returns true when the first parameter derivative is implemented.

bool	hasFirstInputDerivative () const
	Returns true when the first input derivative is implemented.

Data< OutputType >	operator() (Data< InputType > const &patterns) const
	Model evaluation as an operator for a whole dataset. This is a convenience function.

OutputType	operator() (InputType const &pattern) const
	Model evaluation as an operator for a single pattern. This is a convenience function.

BatchOutputType	operator() (BatchInputType const &patterns) const
	Model evaluation as an operator for a single pattern. This is a convenience function.

virtual void	weightedParameterDerivative (BatchInputType const &pattern, BatchOutputType const &outputs, BatchOutputType const &coefficients, State const &state, ParameterVectorType &derivative) const
	calculates the weighted sum of derivatives w.r.t the parameters.

virtual void	weightedInputDerivative (BatchInputType const &pattern, BatchOutputType const &outputs, BatchOutputType const &coefficients, State const &state, BatchInputType &derivative) const
	calculates the weighted sum of derivatives w.r.t the inputs

virtual void	weightedDerivatives (BatchInputType const &patterns, BatchOutputType const &outputs, BatchOutputType const &coefficients, State const &state, ParameterVectorType &parameterDerivative, BatchInputType &inputDerivative) const
	calculates weighted input and parameter derivative at the same time

Public Member Functions inherited from shark::IParameterizable< VectorType >
virtual	~IParameterizable ()

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

Public Member Functions inherited from shark::ISerializable
virtual	~ISerializable ()
	Virtual d'tor.

void	load (InArchive &archive, unsigned int version)
	Versioned loading of components, calls read(...).

void	save (OutArchive &archive, unsigned int version) const
	Versioned storing of components, calls write(...).

	BOOST_SERIALIZATION_SPLIT_MEMBER ()

Protected Attributes
unsigned int	m_classes
	number of classes to be distinguished

std::vector< binary_classifier_type * >	m_binary
	list of binary classifiers

Protected Attributes inherited from shark::AbstractModel< InputTypeT, OutputTypeT, ParameterVectorType >
Features	m_features

Detailed Description

template<class InputType, class VectorType = RealVector>
class shark::OneVersusOneClassifier< InputType, VectorType >

One-versus-one Classifier.

: The one-versus-one classifier combines a number of binary classifiers to form a multi-class ensemble classifier. In the one-versus-one model, there exists one binary classifier for each pair of classes. The predictions of all binary machines are combined with a simple voting scheme.

: The classifier can be extended to handle more classes on the fly, without a need for re-training the existing binary models.

Definition at line 63 of file OneVersusOneClassifier.h.

Member Typedef Documentation

◆ BatchInputType

template<class InputType , class VectorType = RealVector>

typedef base_type::BatchInputType shark::OneVersusOneClassifier< InputType, VectorType >::BatchInputType

Definition at line 69 of file OneVersusOneClassifier.h.

◆ BatchOutputType

template<class InputType , class VectorType = RealVector>

typedef base_type::BatchOutputType shark::OneVersusOneClassifier< InputType, VectorType >::BatchOutputType

Definition at line 70 of file OneVersusOneClassifier.h.

Constructor & Destructor Documentation

◆ OneVersusOneClassifier()

template<class InputType , class VectorType = RealVector>

shark::OneVersusOneClassifier< InputType, VectorType >::OneVersusOneClassifier ( )

inline

Constructor.

Definition at line 73 of file OneVersusOneClassifier.h.

Member Function Documentation

◆ addClass()

template<class InputType , class VectorType = RealVector>

void shark::OneVersusOneClassifier< InputType, VectorType >::addClass ( std::vector< binary_classifier_type * > const & binmodels )

inline

Add binary classifiers for one more class to the model.

The parameter binmodels holds a vector of n binary classifiers, where n is the current number of classes. The i-th model is this list is supposed to output a value of 1 for class n and a value of 0 for class i when faced with the binary classification problem of separating class i from class n. Afterwards the model can predict the n+1 classes {0, ..., n}.

Definition at line 148 of file OneVersusOneClassifier.h.

References shark::OneVersusOneClassifier< InputType, VectorType >::m_binary, shark::OneVersusOneClassifier< InputType, VectorType >::m_classes, and SHARK_RUNTIME_CHECK.

Referenced by main().

◆ binary()

template<class InputType , class VectorType = RealVector>

binary_classifier_type const & shark::OneVersusOneClassifier< InputType, VectorType >::binary	(	unsigned int	class_one,
		unsigned int	class_zero
	)		const

inline

Obtain binary classifier.

: The method returns the binary classifier used to distinguish class_one from class_zero. The convention class_one > class_zero is used (the inverse classifier can be constructed from this one by flipping the labels). The binary classifier outputs a value of 1 for class_one and a value of zero for class_zero.

Definition at line 133 of file OneVersusOneClassifier.h.

References shark::OneVersusOneClassifier< InputType, VectorType >::m_binary, shark::OneVersusOneClassifier< InputType, VectorType >::m_classes, and SHARK_ASSERT.

◆ createState()

template<class InputType , class VectorType = RealVector>

boost::shared_ptr< State > shark::OneVersusOneClassifier< InputType, VectorType >::createState ( ) const

inlinevirtual

Creates an internal state of the model.

The state is needed when the derivatives are to be calculated. Eval can store a state which is then reused to speed up the calculations of the derivatives. This also allows eval to be evaluated in parallel!

Reimplemented from shark::AbstractModel< InputTypeT, OutputTypeT, ParameterVectorType >.

Definition at line 155 of file OneVersusOneClassifier.h.

◆ eval() [1/4]

template<class InputType , class VectorType = RealVector>

void shark::OneVersusOneClassifier< InputType, VectorType >::eval	(	BatchInputType const &	patterns,
		BatchOutputType &	output,
		State &	state
	)		const

inlinevirtual

One-versus-one prediction: evaluate all binary classifiers, collect their votes, and return the class with most votes.

Implements shark::AbstractModel< InputTypeT, OutputTypeT, ParameterVectorType >.

Definition at line 162 of file OneVersusOneClassifier.h.

References shark::batchSize(), shark::OneVersusOneClassifier< InputType, VectorType >::m_binary, and shark::OneVersusOneClassifier< InputType, VectorType >::m_classes.

◆ eval() [2/4]

template<class InputType , class VectorType = RealVector>

virtual void shark::AbstractModel< InputTypeT, OutputTypeT, ParameterVectorType >::eval	(	BatchInputType const &	patterns,
		BatchOutputType &	outputs
	)		const

inlinevirtual

Standard interface for evaluating the response of the model to a batch of patterns.

Parameters

patterns	the inputs of the model
outputs	the predictions or response of the model to every pattern

Reimplemented from shark::AbstractModel< InputTypeT, OutputTypeT, ParameterVectorType >.

Definition at line 163 of file AbstractModel.h.

◆ eval() [3/4]

template<class InputType , class VectorType = RealVector>

virtual void shark::AbstractModel< InputTypeT, OutputTypeT, ParameterVectorType >::eval	(	BatchInputType const &	patterns,
		BatchOutputType &	outputs,
		State &	state
	)		const

virtual

Standard interface for evaluating the response of the model to a batch of patterns.

Parameters

patterns	the inputs of the model
outputs	the predictions or response of the model to every pattern
state	intermediate results stored by eval which can be reused for derivative computation.

Implements shark::AbstractModel< InputTypeT, OutputTypeT, ParameterVectorType >.