Clustering Methods Based on Likelihood Ratio Criteria

Abstract
The standard classification model with several normal populations is extended to the cluster analysis situation where little or no previous information about the population parameters is available. Some common clustering procedures are shown to be extensions of likelihood ratio methods of classification. The analysis suggests that the procedures may have a tendency to partition the sample into groups of about the same size. This suggestion is examined in an example.