Agglomerative clustering based on Euclidean distances among interval scale variables.

Agglomerative clustering, like K-Means, requires you to specify the number of clusters.

Two different methods are provided : updating cluster centers iteratively (iterate and classify) or classifying only.

Options controls the displayed output and lets you change the default missing value handling.

Save request to copy the cluster membership variable as well as the distance of each observation from the cluster center.

Please refer to the SPSS documentation for details (Quick Cluster command).

• Hierarchical clustering [CLUSTER]
• Two step cluster
• Decision trees