Abstract
In this paper, it is demonstrated that the generalized ADCLUS model (Psychological Review 86:87–123, 1979; Psychometrika 47:449–475, 1982) may serve as a theoretical data model for two-mode clustering. The data model has the potential to offer a generale rationale for the generation of artificial data sets in Monte Carlo experiments in that a number of model parameters are included which may generate clusters of different shape, overlap, between-group heterogeneity, etc. The usefulness of the data model as a framework to comparatively estimate the performance of some two-mode methods is demonstrated in a Monte Carlo study.
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Wiedenbeck, M., Krolak-Schwerdt, S. (2009). ADCLUS. In: Gaul, W., Bock, HH., Imaizumi, T., Okada, A. (eds) Cooperation in Classification and Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00668-5_4
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DOI: https://doi.org/10.1007/978-3-642-00668-5_4
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