#include <shark/Models/NearestNeighborClassifier.h>

Inheritance diagram for shark::NearestNeighborClassifier< InputType >:

Public Types
enum	DistanceWeights { UNIFORM, ONE_OVER_DISTANCE }
	Type of distance-based weights. More...

typedef AbstractNearestNeighbors< InputType, unsigned int >	NearestNeighbors

typedef base_type::BatchInputType	BatchInputType

typedef base_type::BatchOutputType	BatchOutputType

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

typedef InputType	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

Public Member Functions
	NearestNeighborClassifier (NearestNeighbors const *algorithm, std::size_t neighbors=3)
	Constructor. More...

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

std::size_t	neighbors () const
	return the number of neighbors More...

void	setNeighbors (std::size_t neighbors)
	set the number of neighbors More...

DistanceWeights	getDistanceWeightType () const
	query the way distances enter as weights More...

void	setDistanceWeightType (DistanceWeights dw)
	set the way distances enter as weights More...

virtual RealVector	parameterVector () const
	get internal parameters of the model More...

virtual void	setParameterVector (RealVector const &newParameters)
	set internal parameters of the model More...

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

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

void	eval (BatchInputType const &patterns, BatchOutputType &output, State &state) const
	soft k-nearest-neighbor prediction More...

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

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

Public Member Functions inherited from shark::AbstractModel< 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	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	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 (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
NearestNeighbors const *	m_algorithm

std::size_t	m_classes
	number of classes More...

std::size_t	m_neighbors
	number of neighbors to be taken into account More...

DistanceWeights	m_distanceWeights
	type of distance-based weights computation More...

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

Detailed Description

template<class InputType>
class shark::NearestNeighborClassifier< InputType >

Nearest Neighbor Classifier.

: The NearestNeighborClassifier predicts a class label according to a local majority decision among its k nearest neighbors. It is not specified how ties are broken.

This model requires the use of one of sharks nearest neighhbor Algorithms.

See also: AbstractNearestNeighbors

Definition at line 56 of file NearestNeighborClassifier.h.

Member Typedef Documentation

◆ BatchInputType

template<class InputType>

typedef base_type::BatchInputType shark::NearestNeighborClassifier< InputType >::BatchInputType

Definition at line 61 of file NearestNeighborClassifier.h.

◆ BatchOutputType

template<class InputType>

typedef base_type::BatchOutputType shark::NearestNeighborClassifier< InputType >::BatchOutputType

Definition at line 62 of file NearestNeighborClassifier.h.

◆ NearestNeighbors

template<class InputType>

typedef AbstractNearestNeighbors<InputType,unsigned int> shark::NearestNeighborClassifier< InputType >::NearestNeighbors

Definition at line 59 of file NearestNeighborClassifier.h.

Member Enumeration Documentation

◆ DistanceWeights

template<class InputType>

enum shark::NearestNeighborClassifier::DistanceWeights

Type of distance-based weights.

Enumerator
UNIFORM	uniform (= no) distance-based weights
ONE_OVER_DISTANCE	weight each neighbor's label with 1/distance

Definition at line 65 of file NearestNeighborClassifier.h.

Constructor & Destructor Documentation

◆ NearestNeighborClassifier()

template<class InputType>

shark::NearestNeighborClassifier< InputType >::NearestNeighborClassifier	(	NearestNeighbors const *	algorithm,
		std::size_t	neighbors = `3`
	)

inline

Constructor.

Parameters

algorithm	the used algorithm for nearst neighbor search
neighbors	number of neighbors

Definition at line 75 of file NearestNeighborClassifier.h.

Member Function Documentation

◆ createState()

template<class InputType>

boost::shared_ptr<State> shark::NearestNeighborClassifier< InputType >::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< InputType, unsigned int >.

Definition at line 123 of file NearestNeighborClassifier.h.

References shark::AbstractModel< InputType, unsigned int >::eval().