An incremental approach to computing conditional complementary entropy for dynamic information systems with varying object set

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참고문헌 (26)

1. W. Bang, "New incremental learning algorithm in the framework of rough set theory", International Journal of Fuzzy Systems, 1, pp.25~36 (1999)
2. C. G. Bai, "Complex investment decisions using rough set and fuzzy c-means: an example of investment in green supply chains", Eur. J. Oper. Res, 248, pp.507~521 (2016)
3. T. Beaubouef, "Information-theoretic measures of uncertainty for rough sets and rough relational databases", Inform. Sci, 109, pp.535~563 (1998)
4. I. Duentsch, "Uncertainty measures of rough set prediction", Arti cial Intelligence, 106, pp.109~137 (1998)
5. J. H. Dai, "Attribute selction based on a new conditonal entropy for incomplete decision systems", Knowledge-Based Systems, 39, pp.207~213 (2013)
6. J. H. Dai, "Conditional entropy for incomplete decision systems and its application in data mining", International Journal of General Systems, 41(7), pp.713~728 (2012)
7. J. H. Dai, "Uncertainty measurement for incomplete interval- valued information systems based on -weak similarity", Knowledge-Based Systems, 136, pp.159~171 (2017)
8. J. H. Dai, "Catoptrical rough set model on two universes using granule-based definition and its variable precision extensions", Inform. Sci, 390, pp.70~81 (2017)
9. F. Hu, "Incremental arrtibute reduction based on elementary sets", LNAI3641, pp.185~193 (2005)
10. J. Y. Liang, "A new method for measuring uncertainty and fuzziness in rough set theory", International Journal of General Systems, 31(4), pp.331~342 (2002)
11. J. H. Dai, "Attribute Selection for Partially Labeled Categorical Data By Rough Set Approach", IEEE Transactions on Cybernetics, pp.1~12 (2016)
12. J. H. Dai, "Maximal Discernibility Pairs based Approach to Attribute Reduction in Fuzzy Rough Sets", IEEE Transactions on Fuzzy Systems, 26(4), pp.2174~2187 (2018)
13. G. M. Lang, "An incremental approach to attribute reduction of dynamic set-valued information systems", International Journal of Machine Learning and Cybernetics, 5, pp.775~788 (2014)
14. G. M. Lang, "Characteristic matrixes-based knowledge reduction in dynamic covering decision information systems", Knowledge-Based Systems, 85, pp.1~26 (2015)
15. Z. W. Li, "A multi-granulation decision- theoretic rough set method for distributed fc-decision information systems: an application in medical diagnosis", Appl. Soft Comput, 56, pp.233~244 (2017)
16. Z. Pawlak, "Rough sets", International Journal of Computer and Information Sciences, 11(5), pp.341~356 (1982)
17. Z. Pawlak, "Rough Sets: Theoretical Aspects of Reasoning About Data" (1991), Kluwer Academic Publishers
18. Z. Pawlak, "Rudiments of rough sets", Information Sciences, 177, pp.3~27 (2007)
19. Z. Pawlak, "Rough sets: Some extensions", Information Sciences, 177, pp.28~40 (2007)
20. Z. Pawlak, "Rough sets and boolean reasoning", Information Sciences, 177, pp.41~73 (2007)
21. Y. H. Qian, "Combination entropy and combination granulation in rough set theory, International Journal of Uncertainty", Fuzziness and Knowledge-Based Systems, 16(2), pp.179~193 (2008)
22. Approximate reducts in decision tables, Research report, "D. Slezak", Institute of Computer Science, Warsaw University of Technology, ~ (1995)
23. D. Slezak, "Approximate entropy reducts", Fundamenta Informaticae, 53, pp.365~390 (2002)
24. S. H. Teng, "Ecient attribute reduction from the viewpoint of discernibility", Information Sciences, 326, pp.297~314 (2016)
25. C. Z. Wang, "A fitting model for feature selection with fuzzy rough sets", EEE Transactions on Fuzzy Systems, 25(4), pp.741~753
26. F. Wang, "Attribute reduction for dynamic data sets", Applied Soft Computing, 13, pp.676~689 (2013)

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