de.aitools.dm.clustering.algorithms.hac
Interface HACClusterMethod

All Known Implementing Classes:

Centroid, CompleteLink, Median, SingleLink, UnweightedAverageLink, WardsMethod, WeightedAverageLink

public interface HACClusterMethod

Represents one possible equation to use on updating the similarities.

Version:

$Id: HACClusterMethod.java,v 1.1 2011/06/22 14:22:51 dogu3912 Exp $

Author:

johannes.kiesel(/\t)uni-weimar.de

Method Summary

double

simRQ(double simAB, double simAQ, double simBQ, int sizeA, int sizeB, int sizeQ) Equation (from Tan et al.

Method Detail

simRQ

double simRQ(double simAB,
             double simAQ,
             double simBQ,
             int sizeA,
             int sizeB,
             int sizeQ)

Equation (from Tan et al. (2006) p. 524, see HAC for full reference):
sim(R,Q) = α_a * sim(A,Q) + α_b * sim(B,Q) + β * sim(A,B) + γ * |sim(A,Q) - sim(B,Q)|
Where α_a, α_b, β and γ depend on the method to use.
See the class description of the concrete implementation for information about these parameters.
Cluster A and cluster B are merged to form cluster R. This method calculates the proximity of R to a cluster Q.

Parameters:

simAB - Proximity between A and B

simAQ - Proximity between A and Q

simBQ - Proximity between B and Q

mA - Number of elements in cluster A

mB - Number of elements in cluster B

mQ - Number of elements in cluster Q

Returns:

simRQ, the proximity between R and Q