OCLUS: An Analytic Method for Generating Clusters with Known Overlap |
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Authors: | Douglas Steinley Robert Henson |
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Institution: | (1) University of Missouri, Columbia, USA;(2) University of North Carolina, Greensboro, USA |
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Abstract: | The primary method for validating cluster analysis techniques is throughMonte
Carlo simulations that rely on generating data with known cluster structure (e.g., Milligan
1996). This paper defines two kinds of data generation mechanisms with cluster overlap,
marginal and joint; current cluster generation methods are framed within these definitions.
An algorithm generating overlapping clusters based on shared densities from several different
multivariate distributions is proposed and shown to lead to an easily understandable
notion of cluster overlap. Besides outlining the advantages of generating clusters within
this framework, a discussion is given of how the proposed data generation technique can
be used to augment research into current classification techniques such as finite mixture
modeling, classification algorithm robustness, and latent profile analysis. |
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Keywords: | |
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