Conversion of real-valued or vector valued outputs to class labels. More...

#include <shark/Models/Classifier.h>

Inheritance diagram for shark::Classifier< Model >:

Public Types
typedef Model::InputType	InputType

typedef unsigned int	OutputType

typedef Batch< InputType >::type	BatchInputType

typedef Batch< unsigned int >::type	BatchOutputType

Public Types inherited from shark::AbstractModel< Model::InputType, unsigned int >
enum	Feature

typedef Model::InputType	InputType
	Defines the input type of the model. More...

typedef unsigned int	OutputType
	Defines the output type of the model. More...

typedef AbstractModel< Model::InputType, unsigned int, RealVector >	ModelBaseType
	Defines the BaseType used by the model (this type). Useful for creating derived models. More...

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

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

typedef TypedFlags< Feature >	Features

typedef TypedFeatureNotAvailableException< Feature >	FeatureNotAvailableException

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

Public Member Functions
	Classifier ()

	Classifier (Model const &decisionFunction)

std::string	name () const
	returns the name of the object More...

RealVector	parameterVector () const
	Return the parameter vector. More...

void	setParameterVector (RealVector const &newParameters)
	Set the parameter vector. More...

std::size_t	numberOfParameters () const
	Return the number of parameters. More...

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

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

RealVector const &	bias () const

RealVector &	bias ()

Model const &	decisionFunction () const
	Return the decision function. More...

Model &	decisionFunction ()
	Return the decision function. More...

void	eval (BatchInputType const &input, BatchOutputType &output) const

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

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

void	read (InArchive &archive)
	From ISerializable. More...

void	write (OutArchive &archive) const
	From ISerializable. More...

Public Member Functions inherited from shark::AbstractModel< Model::InputType, unsigned int >
	AbstractModel ()

virtual	~AbstractModel ()

const Features &	features () const

virtual void	updateFeatures ()

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

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

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

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

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. More...

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

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

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

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

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 More...

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

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

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

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

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

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

	BOOST_SERIALIZATION_SPLIT_MEMBER ()

Additional Inherited Members
Protected Attributes inherited from shark::AbstractModel< Model::InputType, unsigned int >
Features	m_features

Detailed Description

template<class Model>
class shark::Classifier< Model >

Conversion of real-valued or vector valued outputs to class labels.

: The Classifier is a model converting the real-valued vector output of an underlying decision function to a class label 0, ..., d-1 by means of an arg-max operation. The class returns the argument of the maximal input component as its output. This convertson is adjusted to interpret the output of a linear model, a neural network or a support vector machine for multi-category classification.

In the special case that d is 1, it is assumed that the model can be represented as a 2 d vector with both components having the same value but opposite sign. In consequence, a positive output of the model is interpreted as class 1, a negative as class 0.

The underlying decision function is an arbitrary model. It should be default constructable and it can be accessed using decisionFunction(). The parameters of the Classifier are the ones of the decision function.

Optionally the model allows to set bias values which are added on the predicted values of the decision function. Thus adding positive weights on a class makes it more likely to be predicted. In the binary case with a single output, a positive weight makes class one more likely and a negative weight class 0.

Definition at line 64 of file Classifier.h.

Member Typedef Documentation

◆ BatchInputType

template<class Model>

typedef Batch<InputType>::type shark::Classifier< Model >::BatchInputType

Definition at line 71 of file Classifier.h.

◆ BatchOutputType

template<class Model>

typedef Batch<unsigned int>::type shark::Classifier< Model >::BatchOutputType

Definition at line 72 of file Classifier.h.

◆ InputType

template<class Model>

typedef Model::InputType shark::Classifier< Model >::InputType

Definition at line 69 of file Classifier.h.

◆ OutputType

template<class Model>

typedef unsigned int shark::Classifier< Model >::OutputType

Definition at line 70 of file Classifier.h.

Constructor & Destructor Documentation

◆ Classifier() [1/2]

template<class Model>

shark::Classifier< Model >::Classifier ( )

inline

Definition at line 74 of file Classifier.h.

◆ Classifier() [2/2]

template<class Model>

shark::Classifier< Model >::Classifier ( Model const & decisionFunction )

inline

Definition at line 75 of file Classifier.h.

Member Function Documentation

◆ bias() [1/2]

template<class Model>

RealVector const& shark::Classifier< Model >::bias ( ) const

inline

Definition at line 104 of file Classifier.h.

Referenced by shark::Classifier< KernelExpansion< InputType > >::eval().

◆ bias() [2/2]

template<class Model>

RealVector& shark::Classifier< Model >::bias ( )

inline

Definition at line 107 of file Classifier.h.

◆ decisionFunction() [1/2]

template<class Model>

Model const& shark::Classifier< Model >::decisionFunction ( ) const

inline

Return the decision function.

Definition at line 112 of file Classifier.h.

Referenced by shark::KernelSGDTrainer< InputType, CacheType >::train(), and shark::KernelBudgetedSGDTrainer< InputType, CacheType >::train().

◆ decisionFunction() [2/2]

template<class Model>

Model& shark::Classifier< Model >::decisionFunction ( )

inline

Return the decision function.

Definition at line 117 of file Classifier.h.

◆ eval() [1/3]

template<class Model>

void shark::Classifier< Model >::eval	(	BatchInputType const &	input,
		BatchOutputType &	output
	)		const

inline

Definition at line 121 of file Classifier.h.

Referenced by shark::Classifier< KernelExpansion< InputType > >::eval().

◆ eval() [2/3]

template<class Model>

void shark::Classifier< Model >::eval	(	BatchInputType const &	input,
		BatchOutputType &	output,
		State &	state
	)		const

inline

Definition at line 142 of file Classifier.h.

◆ eval() [3/3]

template<class Model>

void shark::Classifier< Model >::eval	(	InputType const &	pattern,
		OutputType &	output
	)		const

inlinevirtual

Standard interface for evaluating the response of the model to a single pattern.

Parameters

pattern	the input of the model
output	the prediction or response of the model to the pattern

Reimplemented from shark::AbstractModel< Model::InputType, unsigned int >.

Definition at line 146 of file Classifier.h.

◆ inputShape()

template<class Model>

Shape shark::Classifier< Model >::inputShape ( ) const

inlinevirtual

Returns the expected shape of the input.

Implements shark::AbstractModel< Model::InputType, unsigned int >.

Definition at line 94 of file Classifier.h.

◆ name()

template<class Model>

std::string shark::Classifier< Model >::name ( ) const

inlinevirtual

returns the name of the object

Reimplemented from shark::INameable.

Definition at line 78 of file Classifier.h.

◆ numberOfParameters()

template<class Model>

std::size_t shark::Classifier< Model >::numberOfParameters ( ) const

inlinevirtual

Return the number of parameters.

Reimplemented from shark::IParameterizable< RealVector >.

Definition at line 89 of file Classifier.h.

◆ outputShape()

template<class Model>

Shape shark::Classifier< Model >::outputShape ( ) const

inlinevirtual

Returns the shape of the output.

For the classifier, Shape is 0 as the output is a scalar

Implements shark::AbstractModel< Model::InputType, unsigned int >.

Definition at line 100 of file Classifier.h.

◆ parameterVector()

template<class Model>

RealVector shark::Classifier< Model >::parameterVector ( ) const

inlinevirtual

Return the parameter vector.

Reimplemented from shark::IParameterizable< RealVector >.

Definition at line 81 of file Classifier.h.

◆ read()

template<class Model>

void shark::Classifier< Model >::read ( InArchive & archive )

inlinevirtual

From ISerializable.

Reimplemented from shark::AbstractModel< Model::InputType, unsigned int >.

Definition at line 165 of file Classifier.h.

◆ setParameterVector()

template<class Model>

void shark::Classifier< Model >::setParameterVector ( RealVector const & newParameters )

inlinevirtual

Set the parameter vector.

Reimplemented from shark::IParameterizable< RealVector >.

Definition at line 85 of file Classifier.h.

◆ write()

template<class Model>

void shark::Classifier< Model >::write ( OutArchive & archive ) const

inlinevirtual

From ISerializable.

Reimplemented from shark::AbstractModel< Model::InputType, unsigned int >.

Definition at line 170 of file Classifier.h.

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

include/shark/Models/Classifier.h

Public Types

Public Member Functions

Additional Inherited Members

Detailed Description

template<class Model> class shark::Classifier< Model >

Member Typedef Documentation

◆ BatchInputType

◆ BatchOutputType

◆ InputType

◆ OutputType

Constructor & Destructor Documentation

◆ Classifier() [1/2]

◆ Classifier() [2/2]

Member Function Documentation

◆ bias() [1/2]

◆ bias() [2/2]

◆ decisionFunction() [1/2]

◆ decisionFunction() [2/2]

◆ eval() [1/3]

◆ eval() [2/3]

◆ eval() [3/3]

◆ inputShape()

◆ name()

◆ numberOfParameters()

◆ outputShape()

◆ parameterVector()

◆ read()

◆ setParameterVector()

◆ write()

template<class Model>
class shark::Classifier< Model >