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An Examination Of Indexes For Determining The Number Of Clusters In Binary Data Sets, E. Dimitriadou, Sara Dolnicar, A. Weingessel

Faculty of Commerce - Papers (Archive)

The problem of choosing the correct number of clusters is as old as cluster analysis itself. A number of authors have suggested various indexes to facilitate this crucial decision. One of the most extensive comparative studies of indexes was conducted by Milligan & Cooper (1985). The present piece of work pursues the same goal under different conditions. In contrast to Milligan and Cooper's work, the emphasis here is on high-dimensional empirical binary data. Binary artificial data sets are constructed to reflect features typically encountered in real-world situations in the field of marketing research. The simulation includes 162 binary data sets …