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prapi::VQClassifier< I, C > Class Template Reference

#include <VectorQuantizer.h>

Inheritance diagram for prapi::VQClassifier< I, C >:

List of all members.

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Detailed Description

template<class I = std::string, class C = int>
class prapi::VQClassifier< I, C >

VQClassifier is a vector quantizer that uses a code book and works as a classifier at the same time.

Public Methods
	VQClassifier (ProximityMeasure< double > *measure, int classCount=1)
	Create a new VectorQuantizer.
	VQClassifier (ProximityMeasure< double > &measure, int classCount=1)
	Create a new VectorQuantizer.
virtual int	getBinIndex (const util::List< double > &vector) const throw (ClassificationException&)
	Get the scalar correspondent (codebook bin index) for a multi-dimensional vector.
int	getBinIndex (const Sample< double, I, C > &sample) const throw (ClassificationException&)
	Get the scalar correspondent (codebook bin index) for a multi-dimensional vector.
int	getMaxIndex () const
	Returns the length of the code book minus one.
virtual int	getClassification (Sample< double, I, C > &sample) throw (ClassificationException&)
	Get the classification given to the closest code book vector.
util::List< Sample< double, I, C > >	getCodeBook () const
	Get a copy of the current code book.
util::List< Sample< double, I, C > > &	codeBook ()
	Get a reference to the current code book.
const util::List< Sample< double, I, C > > &	codeBook () const
	Get a const reference to the current code book.
void	setCodeBook (util::List< Sample< double, I, C > > codeBook)
	Set the code book.
void	setBinIndexMode (bool binIndexMode)
	Change classification mode.
bool	getBinIndexMode () const
	Get the current classification mode.
Protected Attributes
bool	_bBinIndexMode
util::List< Sample< double, I, C > >	_lstCodeBook

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Constructor & Destructor Documentation

template<class I, class C> prapi::VQClassifier< I, C >::VQClassifier (  ProximityMeasure< double > *    measure, int    classCount = 1 )

Create a new VectorQuantizer. There are no training samples as the internal code book is used as such. Parameters: measure  the proximity measure to be used in measuring distances between vectors (autorelease). classCount  the number of classes in the data

template<class I, class C> prapi::VQClassifier< I, C >::VQClassifier (  ProximityMeasure< double > &    measure, int    classCount = 1 )

Create a new VectorQuantizer. There are no training samples as the internal code book is used as such. Parameters: measure  the proximity measure to be used in measuring distances between vectors. classCount  the number of classes in the data

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Member Function Documentation

template<class I = std::string, class C = int> int prapi::VQClassifier< I, C >::getBinIndex (  const Sample< double, I, C > &    sample )  const throw (ClassificationException&) [inline]

Get the scalar correspondent (codebook bin index) for a multi-dimensional vector. Parameters: sample  the sample whose feature vector is to be quantized Returns: the index of the closest vector in the code book

template<class I, class C> int prapi::VQClassifier< I, C >::getBinIndex (  const util::List< double > &    vector )  const throw (ClassificationException&) [virtual]

Get the scalar correspondent (codebook bin index) for a multi-dimensional vector. Parameters: vec  a multi-dimensional vector to be quantized Returns: the index of the closest vector in the code book Implements prapi::VectorQuantizer.

template<class I = std::string, class C = int> void prapi::VQClassifier< I, C >::setBinIndexMode (  bool    binIndexMode )  [inline]

Change classification mode. VQClassifier can work in two different modes. The default (intuitive) way is to assign a classification according to the trueClass field of the best matching code vector. In "bin index" mode, classification is assigned according to the index of the best matching code vector. In this mode, each code vector represents a "class". The first code vector has the index 0 and so on.

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

• VectorQuantizer.h

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Documentation generated on 11.09.2003 with Doxygen.
The documentation is copyrighted material.
Copyright © Topi Mäenpää 2003. All rights reserved.