Package kieker.analysis.generic.clustering.mtree

Class TrimmedAlgorithm<T>

java.lang.Object

kieker.analysis.generic.clustering.mtree.TrimmedAlgorithm<T>

Type Parameters:

T - the type of the Clustered Elements

public class TrimmedAlgorithm<T>
extends Object

An implementation of the trimmed algorithm. The algorithm is proposed in the paper "A Sub-Quadratic Exact Medoid Algorithm". It seems to try to find the model which has the smallest distance to all other models.

Since:

2.0.0

Author:

Lars Jürgensen

Constructor Summary

Constructors

Constructor	Description
TrimmedAlgorithm(T[] models, IDistanceFunction<T> distanceFunction)

Method Summary

Modifier and Type	Method	Description
T	calculate()

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

TrimmedAlgorithm

public TrimmedAlgorithm(T[] models,
 IDistanceFunction<T> distanceFunction)

Method Details

calculate

public T calculate()