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prapi::clustering::ClusteringAlgorithm< T, I, C > Class Template Reference

#include <ClusteringAlgorithm.h>

Inheritance diagram for prapi::clustering::ClusteringAlgorithm< T, I, C >:

prapi::clustering::BSAS< T, I, C > prapi::clustering::MBSAS< T, I, C > List of all members.

Detailed Description

template<class T, class I = string, class C = int>
class prapi::clustering::ClusteringAlgorithm< T, I, C >

ClusteringAlgorithm is a common interface for different types of clustering schemes.

It also provides some useful methods for updating cluster representatives, refining the clustering result etc.


Public Methods

virtual List< Cluster< T,
I, C > > 
getClustering (const List< Sample< T, I, C > > &samples, const ProximityMeasure< T > &measure)=0
virtual void updateRepresentative (Cluster< T, I, C > &cluster)
 Update the representative for a cluster.

void merge (List< Cluster< T, I, C > > &clusters, ProximityMeasure< T > *measure, double threshold)
 Perform a merging procedure after the clusters have been formed.


Member Function Documentation

template<class T, class I, class C>
void prapi::clustering::ClusteringAlgorithm< T, I, C >::merge List< Cluster< T, I, C > > &    clusters,
ProximityMeasure< T > *    measure,
double    threshold
 

Perform a merging procedure after the clusters have been formed.

Parameters:
clusters  the produces clusters
threshold  a threshold for merging clusters that are "close" to each other

template<class T, class I, class C>
void prapi::clustering::ClusteringAlgorithm< T, I, C >::updateRepresentative Cluster< T, I, C > &    cluster [virtual]
 

Update the representative for a cluster.

The default implementation calculates the mean of each feature vector component.


The documentation for this class was generated from the following file:
Documentation generated on 11.09.2003 with Doxygen.
The documentation is copyrighted material.
Copyright © Topi Mäenpää 2003. All rights reserved.