Related Procedures

The TwoStep Cluster Analysis procedure is useful for finding natural groupings of cases or variables. It works well with categorical and continuous variables, and can analyze very large data files.

• If you have a small number of cases, and want to choose between several methods for cluster formation, variable transformation, and measuring the dissimilarity between clusters, try the Hierarchical Cluster Analysis procedure. The Hierarchical Cluster Analysis procedure also allows you to cluster variables instead of cases.
• The K-Means Cluster Analysis procedure is limited to scale variables, but can be used to analyze large data and allows you to save the distances from cluster centers for each object.