Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Tjhi, William-Chandra | Chen, Lihui
Affiliations: Division of Information Engineering, School of EEE, Nanyang Technological University, Republic of Singapore, 639798. E-mail: [email protected], [email protected]
Abstract: Clustering is often seen as a more practical but very challenging answer to the task of categorizing objects. Minimum Sum-squared Residue for Fuzzy Co-Clustering (MSR-FCC) is proposed to address two issues faced by many existing clustering algorithms, namely the high-dimensionality and the inherent fuzziness found in most real-world data. MSR-FCC is able to simultaneously cluster data and features using fuzzy techniques. It suggests a new partitioning fuzzy co-clustering algorithm based on the mean squared residue approach. Besides handling overlap clusters, MSR-FCC offers the flexibility that allows the number of data clusters to be different from the number of feature clusters, which reflects the distribution characteristic inherited in real-world data. In this paper, mathematical formulation of MSR-FCC is derived and explained. Experiments were conducted on standard datasets to demonstrate that the proposed algorithm is able to cluster high-dimensional data with overlaps feasibly and at the same time, it provides a new and promising mechanism for improving the interpretability of the co-clusters through the fuzzy membership function.
Keywords: Fuzzy co-clustering, clustering, fuzzy set
DOI: 10.3233/IDA-2006-10304
Journal: Intelligent Data Analysis, vol. 10, no. 3, pp. 237-249, 2006
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
[email protected]
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office [email protected]
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
如果您在出版方面需要帮助或有任何建, 件至: [email protected]