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By John A. Hartigan
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These measurements are reduced to 10 factors by principal components and factor analysis. The clusters constructed corresponded to standard syndromes such as depression, schizophrenia, mania, drug abuse, and depressive delusions. References 23 HAUTALUOM A , J. (1971). Syndromes, antecedents, and outcomes of psychoses: a cluster analytic study. J. Consult. Clin. Psychol. 37, 332-344. "Current psychiatric mental illness description and classifications have a questionable status . .. The entities called illnesses have low interjudge reliabilities.
Uses numerical taxonomy conservatively in a revision of the genera. Medicine BARON, D. , and FRASER, P. M. (1968). " Brit. Med. Bull. 24, 236-240. A number of clustering algorithms were tested on 50 patients with liver disease, with 330 characters recorded for each patient. In conforming to previous diagnoses of the patients, the single-linkage algorithm was less accurate than the average-linkage technique. Weighting characters to give more weight to rarely appearing characters also improved conformity to previous diagnoses.
For example, a typical object is initially selected for each cluster, and each object is added to the cluster to whose typical object it is closest. Algorithms of this type appear in Chapters 3, 9, and 10. 6 Searching It sometimes happens that mathematical considerations rule out many possible clusterings for a particular criterion, and it becomes feasible to search over the remaining clusterings for the optimal one. Such an algorithm appears in Chapter 6. 8 INTERPRETATION AND EVALUATION OF CLUSTERS An algorithm has been applied to the data producing these many clusters.