JMP 12 Online Documentation (English)
Discovering JMP
Using JMP
Basic Analysis
Essential Graphing
Profilers
Design of Experiments Guide
Fitting Linear Models
Specialized Models
Multivariate Methods
Quality and Process Methods
Reliability and Survival Methods
Consumer Research
Scripting Guide
JSL Syntax Reference
JMP iPad Help
JMP Interactive HTML
Capabilities Index
JMP 13.2 Online Documentation
Multivariate Methods
• Cluster Analysis
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Cluster Analysis
Identify and Explore Groups of Similar Objects
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,
k-
means, and normal mixtures.
Example of a Cluster Analysis
Contents
Clustering Overview
Example of Clustering
Launch the Cluster Platform
Hierarchical Clustering
Hierarchical Cluster Report
Hierarchical Cluster Options
K-Means Clustering
K-Means Control Panel
K-Means Report
Normal Mixtures
Robust Normal Mixtures
Platform Options
Self Organizing Maps
Additional Examples of Cluster Analysis
Example of Self-Organizing Maps
Statistical Details