smile.clustering.linkage
Class WardLinkage
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- smile.clustering.linkage.Linkage
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- smile.clustering.linkage.WardLinkage
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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.
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Constructor Summary
Constructors Constructor and Description WardLinkage(double[][] proximity)Constructor.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method and Description voidmerge(int i, int j)Merge two clusters into one and update the proximity matrix.java.lang.StringtoString()
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Constructor Detail
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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.
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