Iterative Clustering Report
In the K Means Cluster platform, the Iterative Clustering report shows a Control Panel for fitting models. You can iteratively fit different numbers of clusters or you can specify a range using the Range of Clusters option. In addition, you can customize how initial cluster centers are determined using the Initial Clusters option under Advanced Controls. As you fit models, additional reports are added to the window. See K Means Report.
Figure 14.7 Iterative Clustering Control Panel
The Control Panel has the following options:
Method
The following clustering methods are available:
KMeans Clustering
Described in this chapter.
Self Organizing Map
Described in Self Organizing Map Control Panel.
Number of Clusters
Designates the number of clusters to form.
Range of Clusters (Optional)
Provides an upper bound for the number of clusters to form. If a number is entered here, the platform creates separate analyses for every integer between Number of Clusters and the value entered as Range of Clusters (Optional).
Go
Unless Single Step is selected, fits the clusters automatically.
Single Step
Enables you to step through the clustering process one iteration at a time. When you select Single Step and click Go, a K Means Cluster report appears with no cluster assignments but containing a Go and a Step button.
– Click the Step button to step through the iterations one at a time.
– Click the Go button to fit the clusters automatically.
Use within-cluster std deviations
Scales distances using the estimated standard deviation of each variable for observations within each cluster. If you do not select this option, distances are scaled by an overall estimate of the standard deviation of each variable.
Shift distances using sampling rates
Adjusts distances based on the sizes of clusters. If you have unequally sized clusters, an observation should have a higher probability of being assigned to larger clusters because there is a higher prior probability that the observation comes from a larger cluster.
Advanced Controls
The following advanced controls are available:
Maximum Iterations
The maximum number of iterations of the convergence stage of the EM algorithm.
Initial Clusters
Enables you to specify how initial cluster centers are selected. This drop-down menu influences how the clustering algorithm seeds its starting values. Regardless of the option selected, the report displays a Cluster Summary, Cluster Means, and Cluster Standard Deviations table for each clustering solution. The following options are available:
Default
Initial cluster centers are selected automatically based on the order of the data and the specified number of clusters.
Randomize
Initial cluster centers are selected using the same algorithm as the Default option, but with a randomized order of the data table rows. This introduces variation in the initial seeds and can lead to different clustering results on each run, unless the random seed is fixed.
Select Column
Initial cluster centers are selected based on the means of each level in the chosen column. The number of clusters is automatically set to match the number of levels in the column. If the specified number of clusters is smaller than the number of levels, it is updated to match. If it is larger, the additional cluster centers are initialized with random values drawn from a normal distribution centered at the overall mean and scaled by the overall standard deviation.
Caution: If the selected column is continuous with more than 12 unique values, the values are automatically grouped into 12 bins. To use all distinct values, change the modeling type of the column to Nominal or Ordinal.
Tip: To change the column selected for initial cluster assignment, select either Default or Randomize from the Initial Clusters drop-down menu. Then choose Select Column again to specify a different column.
Iterative Clustering Options
This section covers the options in the Iterative Clustering red triangle menu.
See “Local Data Filters in JMP Reports”, “Redo Menus in JMP Reports”, “Group Platform”, and “Save Script Menus in JMP Reports” in Using JMP for more information about the following options:
Local Data Filter
Shows or hides the local data filter that enables you to filter the data used in a specific report.
Redo
Contains options that enable you to repeat or relaunch the analysis. In platforms that support the feature, the Automatic Recalc option immediately reflects the changes that you make to the data table in the corresponding report window.
Platform Preferences
Contains options that enable you to view the current platform preferences or update the platform preferences to match the settings in the current JMP report.
Save Script
Contains options that enable you to save a script that reproduces the report to several destinations.
Note: Additional options for this platform are available through scripting. Open the Scripting Index under the Help menu. In the Scripting Index, you can also find examples for scripting the options that are described in this section.