SPSS® 12.0 Command Syntax Reference

228 CLUSTER
Operations
• More than one clustering method can be specified on the METHOD subcommand.
The CLUSTER procedure involves four steps:
• First, CLUSTER obtains distance measures of similarities between or distances separating
initial clusters (individual cases or individual variables if the input is a matrix measuring
distances between variables).
• Second, it combines the two nearest clusters to form a new cluster.
• Third, it recomputes similarities or distances of existing clusters to the new cluster.
• It then returns to the second step until all items are combined in one cluster.
This process yields a hierarchy of cluster solutions, ranging from one overall cluster to as
many clusters as there are items being clustered. Clusters at a higher level can contain several
lower-level clusters. Within each level, the clusters are disjoint (each item belongs to only
one cluster).
• CLUSTER identifies clusters in solutions by sequential integers (1, 2, 3, and so on).
Limitations
Example
• CLUSTER stores cases and a lower-triangular matrix of proximities in memory. Storage
requirements increase rapidly with the number of cases. You should be able to cluster 100
cases using a small number of variables in an 80K workspace.
• CLUSTER does not honor weights.
CLUSTER V1 TO V4
/PLOT=DENDROGRAM
/PRINT=CLUSTER (2 4).
• This example clusters cases based on their values for all variables between and including
V1 and V4 in the working data file.
• The analysis uses the default measure of distance (squared Euclidean) and the default
clustering method (average linkage between groups).
• PLOT requests a dendrogram.
• PRINT displays a table of the cluster membership of each case for the two-, three-, and
four-cluster solutions.
Variable List
The variable list identifies the variables used to compute similarities or distances between
cases.