Convertion of real-valued outputs to classes 0 or 1. More...

#include <shark/Models/Converter.h>

Inheritance diagram for shark::ThresholdConverter:

Public Member Functions
SHARK_EXPORT_SYMBOL	ThresholdConverter (double threshold=0.0)

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

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

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

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

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

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

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

Public Member Functions inherited from shark::AbstractModel< RealVector, 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	hasSecondParameterDerivative () const
	Returns true when the second parameter derivative is implemented. More...

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

bool	hasSecondInputDerivative () const
	Returns true when the second parameter derivative is implemented. More...

bool	isSequential () const

virtual void	read (InArchive &archive)
	From ISerializable, reads a model from an archive. More...

virtual void	write (OutArchive &archive) const
	writes a model to an archive More...

virtual void	eval (InputType const &pattern, OutputType &output) const
	Standard interface for evaluating the response of the model to a single pattern. 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 &coefficients, State const &state, RealVector &derivative) const
	calculates the weighted sum of derivatives w.r.t the parameters. More...

virtual void	weightedParameterDerivative (BatchInputType const &pattern, BatchOutputType const &coefficients, Batch< RealMatrix >::type const &errorHessian, State const &state, RealVector &derivative, RealMatrix &hessian) const
	calculates the weighted sum of derivatives w.r.t the parameters More...

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

virtual void	weightedInputDerivative (BatchInputType const &pattern, BatchOutputType const &coefficients, typename Batch< RealMatrix >::type const &errorHessian, State const &state, RealMatrix &derivative, Batch< RealMatrix >::type &hessian) const
	calculates the weighted sum of derivatives w.r.t the inputs More...

virtual void	weightedDerivatives (BatchInputType const &patterns, 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
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 ()

Protected Attributes
double	m_threshold

Protected Attributes inherited from shark::AbstractModel< RealVector, unsigned int >
Features	m_features

Additional Inherited Members
Public Types inherited from shark::AbstractModel< RealVector, unsigned int >
enum	Feature

typedef RealVector	InputType
	Defines the input type of the model. More...

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

Detailed Description

Convertion of real-valued outputs to classes 0 or 1.

: The ThresholdConverter is a parameter-free model converting its real-valued input to a binary class label 0 or 1 by means of a threshold operation. Values above the threshold result in class 1, values equal to or below the threshold are converted to class 0. Ths threshold takes a default value of zero, which is adjusted to the case of a (linear or tanh) output neuron of a neural network, and to a binary support vector machine.

Definition at line 80 of file Converter.h.

Constructor & Destructor Documentation

◆ ThresholdConverter()

SHARK_EXPORT_SYMBOL shark::ThresholdConverter::ThresholdConverter ( double threshold = 0.0 )

Member Function Documentation

◆ createState()

boost::shared_ptr<State> shark::ThresholdConverter::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< RealVector, unsigned int >.

Definition at line 93 of file Converter.h.

References eval(), and SHARK_EXPORT_SYMBOL.

◆ eval() [1/2]

SHARK_EXPORT_SYMBOL void shark::ThresholdConverter::eval	(	BatchInputType const &	patterns,
		BatchOutputType &	outputs
	)		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

Reimplemented from shark::AbstractModel< RealVector, unsigned int >.

Referenced by createState(), shark::ThresholdVectorConverter::createState(), eval(), shark::ThresholdVectorConverter::eval(), and shark::ArgMaxConverter< KernelExpansion< InputType > >::eval().

◆ eval() [2/2]

void shark::ThresholdConverter::eval	(	BatchInputType const &	patterns,
		BatchOutputType &	outputs,
		State &	state
	)		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
state	intermediate results stored by eval which can be reused for derivative computation.

Implements shark::AbstractModel< RealVector, unsigned int >.

Definition at line 97 of file Converter.h.

References eval().