Modeling and Multivariate Methods - SAS

478 Clustering Data Chapter 18
Self Organizing Maps
Bandwidth determines the effect of neighboring clusters for predicting centroids. A higher bandwidth
results in a more detailed fitting of the data.
As an example of a SOM, use the Iris.jmp sample data table to follow the steps below:
1. Select Analyze > Multivariate Methods > Cluster.
2. Assign all four columns as Y, Column variables.
3. Select K Means on the Options menu.
4. Uncheck Columns Scaled Individually.
5. Click OK.
6. Select Self Organizing Map from the Method menu on the Control Panel.
7. Since we know the data consists of three species, set Number of Clusters equal to 3.
8. Set N Rows equal to 1 and N Columns equal to 3.
9. Click Go. The report is shown in Figure 18.11.
Figure 18.11 Self Organizing Map Report
The report gives summary statistics for each cluster:
• count of number of observations
• means for each variable
• standard deviations for each variable.