Cluster Analysis
Ribbon bar. Select the Data Mining tab. In the Clustering/Grouping group, click Cluster to display the Cluster Analysis dialog.
Classic menus. From the Data Mining menu, select Cluster Analysis (Generalized EM, k-Means & Tree) to display the Cluster Analysis dialog.
When k-means is selected as the algorithm, there are three tabs: Quick, k-Means, and Validation. When EM is selected as the algorithm, there are three tabs: Quick, EM, and Validation. When Tree Clustering is selected as the algorithm, there are two tabs: Quick and Tree clustering.
Variables
Click the
Variables button to display a standard variable selection dialog. Select one or more categorical variables and/or one or more continuous variables for the analysis. If the
Algorithm chosen for the analysis on the
Quick tab is
EM, on the
EM
tab you can further determine the distribution that applies to each continuous variable.OK
Click this button to begin the cluster analyses and to display the results dialog where you can review all results.
Cancel
Click this button to close the
Cluster Analysis dialog without performing an analysis.
Options
See Options Menu for descriptions of the commands on this menu.
Open Data
Click this button to display the Select Data Source dialog, which contains options to choose the spreadsheet on which to perform the analysis. The
Select Data Source dialog contains a list of the spreadsheets that are currently active.
Select Cases
Click this button to display the Analysis/Graph Case Selection Conditions dialog, which contains options to create conditions for which cases will be included (or excluded) in the current analysis. More information is available in the case selection conditions overview and syntax summary.
W
Click the W (weight) button to display the Analysis/Graph Case Weights dialog, which contains options to adjust the contribution of individual cases to the outcome of the current analysis by "weighting" those cases in proportion to the values of a selected variable. Note that case weights are treated as simple case multipliers in the computations.
MD casewise deletion
Missing data can be deleted Casewise or included in the analyses. If this check box is not selected, the k-Means algorithm will compute cluster assignments based on the observed data only, and the EM algorithm will compute cluster weights (probabilities) based on the observed data only. If all data are missing for a case, that case will be excluded from the analyses regardless of the setting of this option.