lti::classifier::parameters Class Reference

the parameters for the class classifier More...

#include <ltiClassifier.h>

Inheritance diagram for lti::classifier::parameters:

[legend]

Collaboration diagram for lti::classifier::parameters:

[legend]

List of all members.

Public Types
enum	eDistanceMeasure { L1, L2 }
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 parameters *	clone () const
virtual bool	write (ioHandler &handler, const bool complete=true) const
virtual bool	read (ioHandler &handler, const bool complete=true)
Public Attributes
outputTemplate::eMultipleMode	multipleMode

---

Detailed Description

the parameters for the class classifier

---

Member Enumeration Documentation

enum lti::classifier::parameters::eDistanceMeasure

indicates the distance measure used for the classifier

Enumerator:

L1	L1-norm (sum of the absolut values)
L2	L2-norm (square root of the sum of the squares)

---

Constructor & Destructor Documentation

lti::classifier::parameters::parameters

(

)

default constructor

Reimplemented in lti::adaptiveKMeans::parameters, lti::bagging::parameters, lti::clustering::parameters, lti::crispDecisionTree::parameters, lti::DBScan< T >::parameters, lti::decisionTree::parameters, lti::hmmClassifier::parameters, lti::hmmOnlineClassifier::parameters, lti::kNNClassifier::parameters, lti::lvq::parameters, lti::manualCrispDecisionTree::parameters, lti::MLP::parameters, lti::MSTClustering< U >::parameters, lti::rbf::parameters, lti::shClassifier::parameters, lti::SOFM::parameters, lti::SOFM2D::parameters, lti::svm::parameters, and lti::unsupervisedClassifier::parameters.

lti::classifier::parameters::parameters

(

const parameters &

other

)

copy constructor

Parameters:

other

the parameters object to be copied

Reimplemented in lti::adaptiveKMeans::parameters, and lti::bagging::parameters.

virtual lti::classifier::parameters::~parameters

(

)

[virtual]

destructor

Reimplemented in lti::adaptiveKMeans::parameters, lti::bagging::parameters, lti::clustering::parameters, lti::crispDecisionTree::parameters, lti::DBScan< T >::parameters, lti::decisionTree::parameters, lti::hmmClassifier::parameters, lti::hmmOnlineClassifier::parameters, lti::kNNClassifier::parameters, lti::lvq::parameters, lti::manualCrispDecisionTree::parameters, lti::MLP::parameters, lti::MSTClustering< U >::parameters, lti::rbf::parameters, lti::shClassifier::parameters, lti::SOFM::parameters, lti::SOFM2D::parameters, lti::svm::parameters, and lti::unsupervisedClassifier::parameters.

---

Member Function Documentation

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

(

)

const [virtual]

returns a pointer to a clone of the parameters

Reimplemented in lti::adaptiveKMeans::parameters, lti::bagging::parameters, lti::clustering::parameters, lti::crispDecisionTree::parameters, lti::DBScan< T >::parameters, lti::decisionTree::parameters, lti::hmmClassifier::parameters, lti::hmmOnlineClassifier::parameters, lti::kNNClassifier::parameters, lti::lvq::parameters, lti::manualCrispDecisionTree::parameters, lti::MLP::parameters, lti::MSTClustering< U >::parameters, lti::rbf::parameters, lti::shClassifier::parameters, lti::SOFM::parameters, lti::SOFM2D::parameters, and lti::svm::parameters.

parameters& lti::classifier::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::ioObject.

Reimplemented in lti::adaptiveKMeans::parameters, and lti::bagging::parameters.

Referenced by operator=().

const char* lti::classifier::parameters::getTypeName

(

)

const [virtual]

returns name of this type

Reimplemented from lti::ioObject.

Reimplemented in lti::adaptiveKMeans::parameters, lti::bagging::parameters, lti::clustering::parameters, lti::crispDecisionTree::parameters, lti::DBScan< T >::parameters, lti::decisionTree::parameters, lti::hmmClassifier::parameters, lti::hmmOnlineClassifier::parameters, lti::kNNClassifier::parameters, lti::lvq::parameters, lti::manualCrispDecisionTree::parameters, lti::MLP::parameters, lti::MSTClustering< U >::parameters, lti::rbf::parameters, lti::shClassifier::parameters, lti::SOFM::parameters, lti::SOFM2D::parameters, lti::svm::parameters, and lti::unsupervisedClassifier::parameters.

parameters& lti::classifier::parameters::operator=

(

const parameters &

other

)

[inline]

Alias for copy.

Reimplemented from lti::ioObject.

Reimplemented in lti::adaptiveKMeans::parameters, and lti::bagging::parameters.

References copy().

virtual bool lti::classifier::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::ioObject.

Reimplemented in lti::adaptiveKMeans::parameters, lti::bagging::parameters, lti::clustering::parameters, lti::crispDecisionTree::parameters, lti::DBScan< T >::parameters, lti::decisionTree::parameters, lti::hmmClassifier::parameters, lti::hmmOnlineClassifier::parameters, lti::kNNClassifier::parameters, lti::manualCrispDecisionTree::parameters, lti::MLP::parameters, lti::MSTClustering< U >::parameters, lti::rbf::parameters, lti::shClassifier::parameters, lti::SOFM::parameters, lti::SOFM2D::parameters, and lti::svm::parameters.

virtual bool lti::classifier::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::ioObject.

Reimplemented in lti::adaptiveKMeans::parameters, lti::bagging::parameters, lti::clustering::parameters, lti::crispDecisionTree::parameters, lti::DBScan< T >::parameters, lti::decisionTree::parameters, lti::hmmClassifier::parameters, lti::hmmOnlineClassifier::parameters, lti::kNNClassifier::parameters, lti::manualCrispDecisionTree::parameters, lti::MLP::parameters, lti::MSTClustering< U >::parameters, lti::rbf::parameters, lti::shClassifier::parameters, lti::SOFM::parameters, lti::SOFM2D::parameters, and lti::svm::parameters.

---

Member Data Documentation

outputTemplate::eMultipleMode lti::classifier::parameters::multipleMode

Sets the mode the outputTemplate of the classifier works in, if it uses multipleIds.

This option is usually fixed for all classifiers. unsupervised classifiers methods usually wont use multiple ids, whereas supervised classifiers will. The default is ObjProb.

Setting this parameters only makes sense before using classify, since all information is recorded during training anyway.

---

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

• ltiClassifier.h