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prapi::NNClassifier< T, I, C > Class Template Reference

#include <Classifier.h>

Inheritance diagram for prapi::NNClassifier< T, I, C >:

List of all members.

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Detailed Description

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

An implementation of the nearest neighbor classifier.

Each unknown sample is classified according to the class of the sample that has the smallest proximity measure between it.

Public Methods
	NNClassifier (util::List< Sample< T, I, C > > *trainingSamples, ProximityMeasure< T > *measure, int classCount)
	Create a new NN classifier with the given training samples, proximity measure and class count.
	NNClassifier (util::List< Sample< T, I, C > > &trainingSamples, ProximityMeasure< T > *measure, int classCount)
	Create a new NN classifier with the given training samples, proximity measure and class count.
	NNClassifier (util::List< Sample< T, I, C > > &trainingSamples, ProximityMeasure< T > &measure, int classCount)
	Create a new NN classifier with the given training samples, proximity measure and class count.
C	getClassification (Sample< T, I, C > &sample) throw (ClassificationException&)
	Get the classification for a single sample.

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Constructor & Destructor Documentation

template<class T, class I = std::string, class C = int> prapi::NNClassifier< T, I, C >::NNClassifier (  util::List< Sample< T, I, C > > *    trainingSamples, ProximityMeasure< T > *    measure, int    classCount )  [inline]

Create a new NN classifier with the given training samples, proximity measure and class count. (Autorelease measure.)

template<class T, class I = std::string, class C = int> prapi::NNClassifier< T, I, C >::NNClassifier (  util::List< Sample< T, I, C > > &    trainingSamples, ProximityMeasure< T > *    measure, int    classCount )  [inline]

Create a new NN classifier with the given training samples, proximity measure and class count. (Autorelease measure.)

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Member Function Documentation

template<class T, class I, class C> C prapi::NNClassifier< T, I, C >::getClassification (  Sample< T, I, C > &    sample )  throw (ClassificationException&) [virtual]

Get the classification for a single sample. This method is used by holdOut and leaveOneOut to classify each sample. Subclasses must override this method. Parameters: sample  the sample to be classified Returns: the classification. Simple classfiers (like NN or kNN) use integers. More sophisticated ones may use any classification type. See also: Sample for more information. Implements prapi::Classifier< T, I, C >.

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

• Classifier.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.