Rough multi-category decision theoretic framework

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

Volumn 5009 LNAI, Issue , 2008, Pages 676-683

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

^a SAINT MARY S UNIVERSITY   (Canada)

^b TONGJI UNIVERSITY   (China)

Author keywords

K means cluster algorithm; Rough approximation; Rough sets; Web usage mining

Indexed keywords

CLASSIFICATION (OF INFORMATION); CLUSTERING ALGORITHMS; MATHEMATICAL MODELS; PROBLEM SOLVING; ROUGH SET THEORY; SUPERVISED LEARNING; UNSUPERVISED LEARNING;

K-MEANS CLUSTER ALGORITHM; ROUGH APPROXIMATION; ROUGH SETS; WEB USAGE MINING;

DECISION THEORY;

EID: 44649128091     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-79721-0_90     Document Type: Conference Paper

References (11)

1. Lingras, P., Butz, C.J.: Rough set based 1-v-1 and 1-v-r approaches to support vector machine multi-classification. Information Sciences 177, 3298-3782 (2007)
2. Lingras, P., West, C.: Interval set clustering of web users with rough k-means. Journal of Intelligent Information System 23, 5-16 (2004)
3. Pawlak, Z., Wong, S.K.M., Ziarko, W.: Rough sets: probabilistic versus deterministic approach. International Journal of Man-Machine Studies 29, 81-95 (1988)
4. Pawlak, Z., Skowron, A.: Rough membership functions. In: Yager, R.R., Fedrizzi, M., Kacprzyk, J. (eds.) Advances in the Dempster-Shafer Theory of Evidence, pp. 251-271. John Wiley and Sons, New York (1994)
5. Pawlak, Z., Skowron, A.: Rough sets: some extensions. Information Sciences 177, 28-40 (2007)
6. Slezak, D.: Rough sets and Bayes factor. In: Peters, J.F., Skowron, A. (eds.) Transactions on Rough Sets III. LNCS, vol. 3400, pp. 202-229. Springer, Heidelberg (2005)
7. Wong, S.K.M., Ziarko, W.: Comparison of the probabilistic approximate classification and the fuzzy set model. Fuzzy Sets and Systems 21, 357-362 (1987)
8. Yao, Y.Y., Wong, S.K.M.: A decision theoretic framework for approximating concepts. International Journal of Man-machine Studies 37, 793-809 (1992)
9. Yao, Y.Y., Wong, S.K.M., Lingras, P.: A decision-theoretic rough set model. In: Ras, Z.W., Zemankova, M., Emrich, M.L. (eds.) Methodologies for Intelligent Systems, vol. 5, pp. 17-24. North-Holland, New York (1990)
10. Yao, Y.Y.: Decision-theoretic rough set models. In: Yao, J., Lingras, P., Wu, W.-Z., Szczuka, M., Cercone, N.J., Ślȩzak, D. (eds.) RSKT 2007. LNCS (LNAI), vol. 4481, pp. 1-12. Springer, Heidelberg (2007)
11. Ziarko, W.: Variable precision rough set model. Journal of Computer and System Sciences 46, 39-59 (1993)