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Hierarchical Clustering Algorithms with Influence Detection

Ohio State University

Glenn W. Milligan

Ohio State University

The computer program described in this study is based on the methodology developed by the authors to identify those individual data points that can affect the results of a cluster analysis. The computer program designed to compute the measure of internal influence is integrated with nine hierarchical clustering methods. Included among the methods is the first release of the Belbin, Faith, and Milligan 5-flexible clustering algorithm.

Educational and Psychological Measurement, Vol. 55, No. 2, 237-244 (1995)
DOI: 10.1177/0013164495055002007


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				R. Cheng and G. W. Milligan K-Means Clustering Methods with Influence Detection Educational and Psychological Measurement, October 1, 1996; 56(5): 833 - 838. [Abstract]