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Relative reducts in consistent and inconsistent decision tables of the Pawlak rough set model. (English) Zbl 1183.68608

Summary: A relative reduct can be considered as a minimum set of attributes that preserves a certain classification property. This paper investigates three different classification properties, and suggests three distinct definitions accordingly. In the Pawlak rough set model, while the three definitions yield the same set of relative reducts in consistent decision tables, they may result in different sets in inconsistent tables.
Relative reduct construction can be carried out based on a discernibility matrix. The study explicitly stresses a fact, that the definition of a discernibility matrix should be tied to a certain property. Regarding the three classification properties, we can define three distinct definitions accordingly.
Based on the common structure of the specific definitions of relative reducts and discernibility matrices, general definitions of relative reducts and discernibility matrices are suggested.

MSC:

68T30 Knowledge representation
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[1] Beaubouef, T.; Petry, F. E.; Arora, G., Information-theoretic measures of uncertainty for rough sets and rough relational databases, Information Sciences, 109, 185-195 (1998)
[2] Düntsch, I.; Gediga, G., Uncertainty measures of rough set prediction, Artificial Intelligence, 106, 77-107 (1998)
[3] Hu, Q. H.; Xie, Z. X.; Yu, D. R., Hybrid attribute reduction based on a novel fuzzy-rough model and information granulation, Pattern Recognition Letters, 40, 3509-3521 (2007) · Zbl 1129.68073
[4] Hu, Q. H.; Yu, D. R.; Xie, Z. X., Information-preserving hybrid data reduction based on fuzzy-rough techniques, Pattern Recognition Letters, 27, 414-423 (2006)
[5] Hu, X. H.; Cercone, N., Learning in relational databases: a rough set approach, Computational Intelligence, 11, 323-338 (1995)
[6] Klir, J.; Wierman, M. J., Uncertainty Based Information: Elements of Generalized Information Theory (1999), Physica-Verlag: Physica-Verlag New York · Zbl 0935.68023
[7] Kryszkiewicz, M., Comparative study of alternative types of knowledge reduction in inconsistent systems, International Journal of Intelligent Systems, 16, 105-120 (2001) · Zbl 0969.68146
[8] Liang, J. Y.; Shi, Z. Z., The information entropy, rough entropy and knowledge granulation in rough set theory, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 12, 37-46 (2004) · Zbl 1074.68072
[9] Mi, J. S.; Wu, W. Z.; Zhang, W. X., Approaches to knowledge reduction based on variable precision rough set model, Information Sciences, 159, 255-272 (2004) · Zbl 1076.68089
[11] Nguyen, S. H.; Nguyen, H. S., Some efficient algorithms for rough set methods, Proceedings of the International Conference on Information Processing and Management of Uncertainty on Knowledge Based Systems, 1451-1456 (1996)
[12] Pawlak, Z., Rough sets, International Journal of Computer and Information Sciences, 11, 341-356 (1982) · Zbl 0501.68053
[13] Pawlak, Z., Rough Sets: Theoretical Aspects of Reasoning About Data (1991), Kluwer Academic Publishers: Kluwer Academic Publishers Boston · Zbl 0758.68054
[14] Skowron, A., Boolean reasoning for decision rules generation, Proceedings of the International Symposium on Methodologies for Intelligent Systems, 295-305 (1993)
[15] Skowron, A.; Rauszer, C., The discernibility matrices and functions in information systems, (Slowiński, R., Intelligent Decision Support, Handbook of Applications and Advances of the Rough Sets Theory (1992), Kluwer: Kluwer Dordrecht)
[16] Slezak, D., Approximate reducts in decision tables, Proceedings of Information Processing and Management of Uncertainty, 1159-1164 (1996)
[17] Slezak, D., Normalized decision functions and measures for inconsistent decision tables analysis, Fundamenta Informaticae, 44, 291-319 (2000) · Zbl 0970.68171
[18] Susmaga, R., Reducts and constructs in attribute reduction, Fundamenta Informaticae, 61, 2, 159-181 (2004) · Zbl 1083.68123
[19] Wang, G. Y., Calculation methods for core attributes of decision table, Chinese Journal of Computers, 26, 611-615 (2003), in Chinese
[20] Wang, G. Y.; Zhao, J.; Wu, J., A comparitive study of algebra viewpoint and information viewpoint in attribute reduction, Foundamenta Informaticae, 68, 1-13 (2005)
[21] Wang, J.; Miao, D. Q., Analysis on attribute reduction strategies of rough set, Chinese Journal of Computer Science and Technology, 13, 189-192 (1998) · Zbl 0902.68049
[22] Wang, J.; Wang, J., Reduction algorithms based on discernibility matrix: the ordered attributes method, Journal of Computer Science and Technology, 16, 489-504 (2001) · Zbl 1014.68160
[23] Wierman, M. J., Measuring uncertainty in rough set theory, International Journal of General Systems, 28, 283-297 (1999) · Zbl 0938.93034
[24] Wu, W. Z.; Zhang, M.; Li, H. Z.; Mi, J. S., Knowledge reduction in random information systems via Dempster-Shafer theory of evidence, Information Sciences, 174, 143-164 (2005) · Zbl 1088.68169
[25] Yang, M.; Sun, Z. H., Improvement of discernibility matrix and the computation of a core, Journal of Fudan University (Natural Science), 43, 865-868 (2004), in Chinese
[26] Yao, Y. Y., Decision-theoretic rough set models, Proceedings of the Second International Conference on Rough Sets and Knowledge Technology, LNAI 4481, 1-12 (2007)
[27] Yao, Y. Y.; Zhao, Y., Attribute reduction in decision-theoretic rough set models, Information Sciences, 178, 3356-3373 (2008) · Zbl 1156.68589
[28] Yao, Y. Y.; Zhao, Y., Discernibility matrix simplification for constructing attribute reducts, Information Sciences, 179, 7, 867-882 (2009) · Zbl 1162.68704
[29] Ye, D. Y.; Chen, Z. J., An improved discernibility matrix for computing all reducts of an inconsistent decision table, The Proceedings of the Fifth IEEE International Conference on Cognitive Informatics, 305-308 (2006)
[30] Zhang, W. X.; Mi, J. S.; Wu, W. Z., Knowledge reduction in inconsistent information systems, Chinese Journal of Computers, 1, 12-18 (2003)
[31] Zhao, K.; Wang, J., A reduction algorithm meeting users’ requirements, Journal of Computer Science and Technology, 17, 578-593 (2002) · Zbl 1057.68026
[32] Zhao, Y.; Luo, F.; Wong, S. K.M.; Yao, Y. Y., A general definition of an attribute reduct, Proceedings of the Second Rough Sets and Knowledge Technology, 101-108 (2007)
[33] Zhao, Y.; Yao, Y. Y.; Luo, F., Data analysis based on discernibility and indiscernibility, Information Sciences, 177, 4959-4976 (2007) · Zbl 1129.68071
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