lti::adaptiveKMeans::parameters Class Reference

the parameters for the class adaptiveKMeans More...

#include <ltiAdaptiveKMeans.h>

Inheritance diagram for lti::adaptiveKMeans::parameters:

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Collaboration diagram for lti::adaptiveKMeans::parameters:

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List of all members.

Public Member Functions
	parameters ()
	parameters (const parameters &other)
virtual	~parameters ()
const char *	getTypeName () const
parameters &	copy (const parameters &other)
parameters &	operator= (const parameters &other)
virtual classifier::parameters *	clone () const
virtual bool	write (ioHandler &handler, const bool complete=true) const
virtual bool	read (ioHandler &handler, const bool complete=true)
Public Attributes
double	minNeighborhood
double	maxNeighborhood
double	learnRate
int	nbNeighborhoods
double	minNumberOfPoints
int	nbClusters
bool	detectNeighborhood
int	maxIterations
double	maxDistance

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Detailed Description

the parameters for the class adaptiveKMeans

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Constructor & Destructor Documentation

lti::adaptiveKMeans::parameters::parameters

(

)

default constructor

Reimplemented from lti::classifier::parameters.

lti::adaptiveKMeans::parameters::parameters

(

const parameters &

other

)

copy constructor

Parameters:

other

the parameters object to be copied

Reimplemented from lti::classifier::parameters.

virtual lti::adaptiveKMeans::parameters::~parameters

(

)

[virtual]

destructor

Reimplemented from lti::classifier::parameters.

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Member Function Documentation

virtual classifier::parameters* lti::adaptiveKMeans::parameters::clone

(

)

const [virtual]

returns a pointer to a clone of the parameters

Reimplemented from lti::classifier::parameters.

parameters& lti::adaptiveKMeans::parameters::copy

(

const parameters &

other

)

copy the contents of a parameters object

Parameters:

other

the parameters object to be copied

Returns:

a reference to this parameters object

Reimplemented from lti::classifier::parameters.

const char* lti::adaptiveKMeans::parameters::getTypeName

(

)

const [virtual]

returns name of this type

Reimplemented from lti::classifier::parameters.

parameters& lti::adaptiveKMeans::parameters::operator=

(

const parameters &

other

)

copy the contents of a parameters object

Parameters:

other

the parameters object to be copied

Returns:

a reference to this parameters object

Reimplemented from lti::classifier::parameters.

virtual bool lti::adaptiveKMeans::parameters::read	(	ioHandler &	handler,
		const bool	complete = true
	)			[virtual]

read the parameters from the given ioHandler

Parameters:

	handler	the ioHandler to be used
	complete	if true (the default) the enclosing begin/end will be also written, otherwise only the data block will be written.

Returns:

true if write was successful

Reimplemented from lti::classifier::parameters.

virtual bool lti::adaptiveKMeans::parameters::write	(	ioHandler &	handler,
		const bool	complete = true
	)			const [virtual]

write the parameters in the given ioHandler

Parameters:

	handler	the ioHandler to be used
	complete	if true (the default) the enclosing begin/end will be also written, otherwise only the data block will be written.

Returns:

true if write was successful

Reimplemented from lti::classifier::parameters.

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Member Data Documentation

bool lti::adaptiveKMeans::parameters::detectNeighborhood

if true the parameters minNeighborhood, maxNeighborhood, increment and maxDistance will be automaticly be detected

double lti::adaptiveKMeans::parameters::learnRate

the learn rate

double lti::adaptiveKMeans::parameters::maxDistance

if every component of the centroids moves less than this parameter the centroids are stable

int lti::adaptiveKMeans::parameters::maxIterations

maximum number of iterations before the next neighborhood considered

double lti::adaptiveKMeans::parameters::maxNeighborhood

maximum neighborhood

double lti::adaptiveKMeans::parameters::minNeighborhood

minimum neighborhood

double lti::adaptiveKMeans::parameters::minNumberOfPoints

minimum number of points in one cluster.

If a cluster has less than this the cluster will be deleted

int lti::adaptiveKMeans::parameters::nbClusters

number of clusters to start with

int lti::adaptiveKMeans::parameters::nbNeighborhoods

the increment of the neighborhood

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

• ltiAdaptiveKMeans.h