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Enrichment Procedures for Soft Clusters: A Statistical Test and its Applications

R.D. Phillips1, M.S. Hossain1, L.T. Watson1,2, R.H. Wynne3, Naren Ramakrishnan1
Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0106, USA.
Department of Mathematics, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0123, USA.
Department of Forest Resources and Environmental Conservation, Virginia Polytechnic Instituteand State University, Blacksburg, VA 24061-0324, USA.

Computer Modeling in Engineering & Sciences 2014, 97(2), 175-197. https://doi.org/10.3970/cmes.2014.097.175

Abstract

Clusters, typically mined by modeling locality of attribute spaces, are often evaluated for their ability to demonstrate ‘enrichment’ of categorical features. A cluster enrichment procedure evaluates the membership of a cluster for significant representation in predefined categories of interest. While classical enrichment procedures assume a hard clustering definition, this paper introduces a new statistical test that computes enrichments for soft clusters. Application of the new test to several scientific datasets is given.

Keywords

Cluster enrichment, fuzzy clustering, statistical significance test.

Cite This Article

Phillips, R., Hossain, M., Watson, L., Wynne, R., Ramakrishnan, N. (2014). Enrichment Procedures for Soft Clusters: A Statistical Test and its Applications. CMES-Computer Modeling in Engineering & Sciences, 97(2), 175–197.



This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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