Titlebook: Innovations in Fuzzy Clustering; Theory and Applicati Mika Sato-Ilic,Lakhmi C. Jain Book 2006 Springer-Verlag Berlin Heidelberg 2006 Cluste

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Fuzzy Clustering based Principal Component Analysis,al Component Analysis (PCA) [1], [26] is a widely used and well-known data analysis technique. However problems arise, when the data does not have a structure that PCA can capture and thus we cannot obtain any satisfactory results. For the most part, this is due to the uniformity of the data structu

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Evaluation of Fuzzy Clustering,ider not only the belonging status of an object to the assumed clusters, but also to consider how much each of the objects belong to the clusters. Fuzzy clustering is a method to obtain “natural groups“ in the given observations by using an assumption of a fuzzy subset on clusters. By this method, w

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978-3-642-07072-3Springer-Verlag Berlin Heidelberg 2006

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Innovations in Fuzzy Clustering978-3-540-34357-8Series ISSN 1434-9922 Series E-ISSN 1860-0808

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https://doi.org/10.1007/3-540-34357-1Clustering Techniques; Computer; Fuzzy; Fuzzy Clustering; Pattern Recognition; Regression; calculus; cognit

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Mika Sato-Ilic,Lakhmi C. JainLatest research on fuzzy clustering and applications

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