K-Means Clustering Methods with Influence Detection

Abstract
A software program is described that performs K-means clustering with several enhancements. The software system includes the influence detection methodology developed by Cheng and Milligan. As such, the applied user can identify those data points that affect the results of a given cluster analysis. The user interface is interactive and allows for multiple analyses in the same session. Finally, the software can handle data set sizes much larger than those provided for by traditional hierarchical clustering methods.

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