smile.clustering.linkage

Class WardLinkage

java.lang.Object

smile.clustering.linkage.Linkage

smile.clustering.linkage.WardLinkage

public class WardLinkage
extends Linkage

Ward's linkage. Ward's linkage follows the analysis of variance approach The dissimilarity between two clusters is computed as the increase in the "error sum of squares" (ESS) after fusing two clusters into a single cluster. Ward's Method seeks to choose the successive clustering steps so as to minimize the increase in ESS at each step. Note that it is only valid for Euclidean distance based proximity matrix.

Author:

Haifeng Li

Constructor Summary

Constructors

Constructor and Description
WardLinkage(double[][] proximity) Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
void	merge(int i, int j) Merge two clusters into one and update the proximity matrix.
String	toString()

Methods inherited from class smile.clustering.linkage.Linkage

getProximity

Methods inherited from class java.lang.Object

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

Constructor Detail

WardLinkage

public WardLinkage(double[][] proximity)

Constructor.

Parameters:

proximity - the proximity matrix to store the distance measure of dissimilarity. To save space, we only need the lower half of matrix.

Method Detail

toString

public String toString()

Overrides:

toString in class Object

merge

public void merge(int i,
         int j)

Description copied from class: Linkage

Merge two clusters into one and update the proximity matrix.

Specified by:

merge in class Linkage

Parameters:

i - cluster id.

j - cluster id.