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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Projected Gustafson-Kessel Clustering Algorithm and Its Convergence
verfasst von : Charu Puri, Naveen Kumar
Erschienen in: Transactions on Rough Sets XIV
Verlag: Springer Berlin Heidelberg
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Fuzzy techniques have been used for handling vague boundaries of arbitrarily oriented clusters. However, traditional clustering algorithms tend to break down in high dimensional spaces due to inherent sparsity of data. We propose a modification in the objective function of Gustafson-Kessel clustering algorithm for projected clustering and prove the convergence of the resulting algorithm. We present the results of applying the proposed projected Gustafson-Kessel clustering algorithm to synthetic and UCI data sets, and also suggest a way of extending it to a rough set based algorithm.