Precision of rough set clustering

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5306 LNAI, Issue , 2008, Pages 369-378

  Lingras, Pawan ^a   Chen, Min ^a,b   Miao, Duoqian ^b  

^a SAINT MARY S UNIVERSITY   (Canada)

^b TONGJI UNIVERSITY   (China)

Author keywords

K means clustering algorithm; Precision; Rough sets

Indexed keywords

FUZZY CLUSTERING; ROUGH SET THEORY;

CHOICE OF PARAMETERS; CONVENTIONAL CLUSTERING; MULTIPLE CLUSTERS; PRECISION; REAL-WORLD; SET REPRESENTATION;

K-MEANS CLUSTERING;

EID: 57049184601     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-88425-5_38     Document Type: Conference Paper

References (17)

1. Banerjee, M., Mitra, S., Pal, S.K.: Rough fuzzy MLP: knowledge encoding and classification. IEEE Transactions on Neural Networks 9(6), 1203-1216 (1998)
2. Ho, T.B., Nguyen, N.B.: Nonhierarchical Document Clustering by a Tolerance Rough Set Model. International Journal of Intelligent Systems 17(2), 199-212 (2002)
3. Hartigan, J.A., Wong, M.A.: Algorithm AS136: A K-Means Clustering Algorithm. Applied Statistics 28, 100-108 (1979)
4. Hirano, S., Tsumoto, S.: Rough Clustering and Its Application to Medicine. Information Sciences 124, 125-137 (2000)
5. Lingras, P.: Unsupervised Rough Set Classification using GAs. Journal Of Intelligent Information Systems 16(3), 215-228 (2001)
6. Lingras, P., West, C.: Interval Set Clustering of Web Users with Rough K-means. Journal of Intelligent Information Systems 23(1), 5-16 (2004)
7. Lingras, P., Hogo, M., Snorek, M.: Interval Set Clustering of Web Users using Modified Kohonen Self-Organizing Maps based on the Properties of Rough Sets. Web Intelligence and Agent Systems: An International Journal 2(3), 217-230 (2004)
8. Mitra, S.: An evolutionary rough partitive clustering. Pattern Recognition Letters 25, 1439-1449 (2004)
9. Mitra, S., Bank, H., Pedrycz, W.: Rough-Fuzzy Collaborative Clustering. IEEE Trans. on Systems, Man and Cybernetics 36(4), 795-805 (2006)
10. Nguyen, H.S.: Rough Document Clustering and the Internet. Handbook on Granular Computing (2007)
11. Pedrycz, W., Waletzky, J.: Fuzzy Clustering with Partial Supervision. IEEE Trans. on Systems, Man and Cybernetics 27(5), 787-795 (1997)
12. Polkowski, L., Skowron, A.: Rough Mereology: A New Paradigm for Approximate Reasoning. International Journal of Approximate Reasoning 15(4), 333-365 (1996)
13. Peters, J.F., Skowron, A., Suraj, Z., Rzasa, W., Borkowski, M.: Clustering: A rough set approach to constructing information granules. In: Proceedings of 6th International Conference on Soft Computing and Distributed Processing, Rzeszow, Poland, June 24-25, 2002, pp. 57-61 (2002)
14. Pawlak, Z.: Rough Sets: Theoretical Aspects of Reasoning about Data. Kluwer Academic Publishers, Dordrecht (1992)
15. Peters, G.: Some Refinements of Rough k-Means. Pattern Recognition 39(8), 1481-1491 (2006)
16. Yao, Y.Y.: Constructive and algebraic methods of the theory of rough sets. Information Sciences 109, 21-47 (1998)
17. Yao, Y.Y., Zhao, Y.: Attribute reduction in decision-theoretic rough set models. Information Sciences (to appear, 2008)