Parameters | Genetics | Interactive Linkage Group Clustering Method

Interactive Linkage Group Clustering Method
Use the drop-down menu to specify the method to use for joining clusters to form linkage groups via hierarchical clustering. Different algorithms might work better than others depending on your data.
Note: This parameter is available only when Interactive Hierarchical Clustering has been selected from the Choose a linkage grouping method field.
Clustering methods are described in the following table:
Choose this method to set the distance between clusters to the ANOVA sum of squares across all markers between clusters. At each generation, two clusters from the previous generation are merged to reduce the within-cluster sum of squares over all partitions. The sums of squares are easier to interpret when they are divided by the total sum of squares to give the proportions of variance (squared semipartial correlations).
This method tends to join clusters with a small number of observations and is biased toward producing clusters with approximately the same number of observations. It is also very sensitive to outliers.2

Milligan, G.W. (1980) An examination of the effect of six types of error perturbation on fifteen clustering algorithms. Psychometrika 45: 325-342.

To Specify a Clustering Method:
Specify Interactive Hierarchical Clustering in the Choose a linkage grouping method field.
See the JMP documentation on the hierarchical clustering platform for more information.