A COMPARISON OF SOME CLUSTER-SEEKING TECHNIQUES.
Technical rept., Jun-Aug 66,
STANFORD RESEARCH INST MENLO PARK CALIF
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Conventional multivariate statistics examine in considerable depth the significance of relationships existing in data as shown by the mean and the covariance matrix. Shortcomings of this approach are briefly discussed. Cluster-seeking techniques are discussed as alternatives to conventional multivariate methods. Thirty variants of cluster-seeking techniques, the total number presently known to the author, are divided into seven categories probabilistic, signal detection, clustering, clumping, eigenvalue, minimal mode seeking and miscellaneous. These larger classes are contrasted and, within each class, the techniques are summarized and compared. A composite technique that combines the best features of the various approaches is proposed. Author
- Statistics and Probability