Using the Cluster Platform
Clustering is the technique of grouping rows together that share similar values across a number of variables. It is a wonderful exploratory technique to help you understand the clumping structure of your data. JMP provides three different clustering methods:
• Hierarchical clustering is appropriate 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. You can choose the number of clusters that you like after the tree is built.
• K-means clustering is appropriate for larger tables, up to hundreds of thousands of rows. It makes a fairly good guess at cluster ...