• All Known Subinterfaces:
GeometricLinkage
All Known Implementing Classes:
CentroidLinkage, CompleteLinkage, FlexibleBetaLinkage, GroupAverageLinkage, MedianLinkage, MinimumVarianceLinkage, SingleLinkage, WardLinkage, WeightedAverageLinkage

@Reference(authors="G. N. Lance, W. T. Williams",
title="A general theory of classificatory sorting strategies 1. Hierarchical systems",
booktitle="The Computer Journal 9.4",
url="https://doi.org/10.1093/comjnl/9.4.373",
bibkey="doi:10.1093/comjnl/9.4.373")
public interface Linkage
Abstract interface for implementing a new linkage method into hierarchical clustering.

Reference:

G. N. Lance, W. T. Williams
A general theory of classificatory sorting strategies
1. Hierarchical systems
The Computer Journal 9.4

Since:
0.6.0
Author:
Erich Schubert
• ### Method Summary

All Methods
Modifier and Type Method Description
double combine​(int sizex, double dx, int sizey, double dy, int sizej, double dxy)
Compute combined linkage for two clusters.
default double initial​(double d, boolean issquare)
Initialization of the distance matrix.
default double restore​(double d, boolean issquare)
Restore a distance to the original scale.
• ### Method Detail

• #### initial

default double initial​(double d,
boolean issquare)
Initialization of the distance matrix.
Parameters:
d - Distance
issquare - Flag to indicate the input values are already squared
Returns:
Initial value
• #### restore

default double restore​(double d,
boolean issquare)
Restore a distance to the original scale.
Parameters:
d - Distance
issquare - Flag to indicate the input values were already squared
Returns:
Initial value
• #### combine

double combine​(int sizex,
double dx,
int sizey,
double dy,
int sizej,
double dxy)
Compute combined linkage for two clusters.
Parameters:
sizex - Size of first cluster x before merging
dx - Distance of cluster x to j before merging
sizey - Size of second cluster y before merging
dy - Distance of cluster y to j before merging
sizej - Size of candidate cluster j
dxy - Distance between clusters x and y before merging
Returns:
Combined distance