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Volumn 49, Issue 5, 1998, Pages 415-422

Data mining using extensions of the rough set model

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EID: 85088546438     PISSN: 00028231     EISSN: None     Source Type: Journal    
DOI: 10.1002/(sici)1097-4571(19980415)49:5<415::aid-asi4>3.0.co;2-z     Document Type: Article
Times cited : (4)

References (16)
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    • Deogun, J. S., Raghavan, V. V., & Sever, H. (1994). Rough set based classification methods and extended decision tables. Soft Computing: Proceedings of the Third International Workshop on Rough Sets and Soft Computing (RSSC'94), San Jose, CA, November 10-12, T. Y. Lin and A. M. Wildberger (Eds.), San Diego, CA: The Society for Computer Simulation (pp. 302-305).
    • (1994) Soft Computing: Proceedings of the Third International Workshop on Rough Sets and Soft Computing (RSSC'94) , pp. 302-305
    • Deogun, J.S.1    Raghavan, V.V.2    Sever, H.3
  • 4
    • 0002946532 scopus 로고
    • Rough approximate operators
    • W. P. Ziarko (Ed.), London: Springer-Verlag
    • Lin, T. Y., & Liu, Q. (1994). Rough approximate operators. In W. P. Ziarko (Ed.), Rough sets, fuzzy sets and knowledge discovery (pp. 256-260). London: Springer-Verlag.
    • (1994) Rough Sets, Fuzzy Sets and Knowledge Discovery , pp. 256-260
    • Lin, T.Y.1    Liu, Q.2
  • 5
    • 84947729722 scopus 로고
    • Combination of evidence in rough set theory
    • Sudbury, Canada, May 27-29, O. Abou-Rabia, C. K. Chang and W. W. Koczkodaj (Eds.), Los Alamitos, CA: IEEE Computer Society Press
    • Lingras, P. J. (1993). Combination of evidence in rough set theory. Proceedings of the Fifth International Conference on Computing and Information (ICCI'93), Sudbury, Canada, May 27-29, O. Abou-Rabia, C. K. Chang and W. W. Koczkodaj (Eds.), Los Alamitos, CA: IEEE Computer Society Press (pp. 289-293).
    • (1993) Proceedings of the Fifth International Conference on Computing and Information (ICCI'93) , pp. 289-293
    • Lingras, P.J.1
  • 6
    • 11344290352 scopus 로고
    • Plausibilistic rule extraction from incomplete databases using non-transitive rough set model
    • Nashville, TN, March 2, T. Y. Lin (Ed.), San Jose, CA: San Jose State University
    • Lingras, P. J. (1995). Plausibilistic rule extraction from incomplete databases using non-transitive rough set model. Proceedings of the twenty-third Computer Science Conference (CSC'95) Workshop on Rough Sets and Database Mining, Nashville, TN, March 2, T. Y. Lin (Ed.), San Jose, CA: San Jose State University (12 pages).
    • (1995) Proceedings of the Twenty-third Computer Science Conference (CSC'95) Workshop on Rough Sets and Database Mining , pp. 12
    • Lingras, P.J.1
  • 8
    • 0039448844 scopus 로고
    • Rough set semantics for non-classical logics
    • Ziarko, W. P. (Ed.), London: Springer-Verlag
    • Orlowska, E. (1993). Rough set semantics for non-classical logics. In Ziarko, W. P. (Ed.), Rough Sets, Fuzzy Sets and Knowledge Discovery (pp. 143-148). London: Springer-Verlag.
    • (1993) Rough Sets, Fuzzy Sets and Knowledge Discovery , pp. 143-148
    • Orlowska, E.1
  • 10
    • 0002138277 scopus 로고
    • Rough sets: A new approach to vagueness
    • L. A. Zadeh & J. Kacprzyk (Eds.), New York: Wiley
    • Pawlak, Z. (1992). Rough sets: A new approach to vagueness. In L. A. Zadeh & J. Kacprzyk (Eds.), Fuzzy logic for the management of uncertainty (pp. 105-118). New York: Wiley.
    • (1992) Fuzzy Logic for the Management of Uncertainty , pp. 105-118
    • Pawlak, Z.1
  • 12
    • 0002580328 scopus 로고
    • From the rough set theory to the evidence theory
    • R. Yager, M. Fedrizzi, & J. Kospryk (Eds.), New York: Wiley
    • Skowron, A., & Grzymala-Busse, J. (1994). From the rough set theory to the evidence theory. In R. Yager, M. Fedrizzi, & J. Kospryk (Eds.), Advances in the Dempster-Shafer theory of evidence (pp. 193-236). New York: Wiley.
    • (1994) Advances in the Dempster-Shafer Theory of Evidence , pp. 193-236
    • Skowron, A.1    Grzymala-Busse, J.2
  • 14
    • 0011157035 scopus 로고
    • Comparison of the probabilistic approximate classification and the fuzzy set model
    • Wong, S. K. M., & Ziarko, W. (1987). Comparison of the probabilistic approximate classification and the fuzzy set model. Fuzzy Sets and Systems, 21, 357-362.
    • (1987) Fuzzy Sets and Systems , vol.21 , pp. 357-362
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  • 15
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    • Representation and classification of rough set models
    • San Jose, CA, November 10-12, T. Y. Lin and A. M. Wildberger (Eds.), San Diego, CA: the Society for Computer Simulation
    • Yao, Y. Y., Li, X., Lin, T. Y., & Liu, Q. (1994). Representation and classification of rough set models. Soft Computing: Proceedings of the Third International Workshop on Rough Sets and Soft Computing (RSSC'94), San Jose, CA, November 10-12, T. Y. Lin and A. M. Wildberger (Eds.), San Diego, CA: the Society for Computer Simulation (pp. 44-47).
    • (1994) Soft Computing: Proceedings of the Third International Workshop on Rough Sets and Soft Computing (RSSC'94) , pp. 44-47
    • Yao, Y.Y.1    Li, X.2    Lin, T.Y.3    Liu, Q.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.