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Cereal.jmp (Help > Sample Data) Clustering Use clustering to automatically group rows having similar characteristics.

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Example: Cereal.jmp (Help > Sample Data) Clustering Use clustering to automatically group rows having similar characteristics. Hierarchical Clustering 1. From an open JMP® data table, select Analyze > Multivariate Methods > Cluster. 2. Select one or more variables from Select Columns and click Y, Columns. 3. If available, select a Label variable. 4. Select the desired method (bottom left corner) and click OK. JMP will generate: • A dendrogram, showing the clusters formed at each step. • A scree plot, showing the distance bridged each step. • The clustering history, giving cluster statistics for each step. Tips: • To color clusters, to mark or save clusters, or to request other options, click the top red triangle. • To dynamically change the number of clusters, click and drag one of the black diamonds left or right. K-Means Clustering 1. From an open table, select Analyze > Multivariate Methods > Cluster. 2. Select one or more continuous variables from Select Columns and click Y, Columns (continuous variables have blue triangles). 3. Under Options, change Hierarchical to KMeans, and click OK. 4. In the resulting Control Panel, enter the number of clusters and click Go. JMP will generate: • A summary of the cluster sizes. • Tables of cluster means and standard deviations for each variable. Tips: • To obtain biplots, parallel plots or request other options, click the red triangle for the K Means heading. • To perform analyses for a range of cluster sizes: In the Control Panel, enter the lower limit in number of clusters and the upper limit in range of clusters, then click Go. • To step through the formation of the clusters: In the Control Panel, check Single Step then click Go. • To locate potential multivariate outliers, select Declutter in the Control Panel. Note: For more information on Declutter and additional discussion of these and other clustering methods, search for “cluster” in the JMP Help or see the book Multivariate Methods (under Help > Books). jmp.com/learn rev 02/2014

 
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