JMP 12 Multivariate Methods

Clustering Overview

Clustering is a multivariate technique of grouping rows together that share similar values. It can use any number of variables. The variables must be numeric variables for which numerical differences make sense. The common situation is that data are not scattered evenly through n-dimensional space, but rather they form clumps, locally dense areas, modes, or clusters. The identification of these clusters goes a long way toward characterizing the distribution of values.

JMP provides three approaches to clustering:

• hierarchical clustering for small tables, up to several thousand rows. It combines rows in a hierarchical sequence portrayed as a tree. In JMP, the tree, also called a dendrogram, is a dynamic, responding graph. ...