An efficient rough feature selection algorithm with a multi-granulation view

International Journal of Approximate Reasoning

Volumn 53, Issue 6, 2012, Pages 912-926

  Liang, Jiye ^a   Wang, Feng ^a,b   Dang, Chuangyin ^b   Qian, Yuhua ^a  

^a SHANXI UNIVERSITY   (China)

^b CITY UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Feature selection; Large scale data sets; Multi granulation view; Rough set theory

Indexed keywords

COMPUTATION THEORY; DATA MINING; FEATURE EXTRACTION; GRANULATION; LEARNING SYSTEMS; SOFT COMPUTING;

ATTRIBUTE REDUCTION; DECISION PERFORMANCE; FEATURE SELECTION ALGORITHM; FEATURE SUBSET; LARGE SCALE DATA SETS; MULTI-GRANULATIONS; SOFT COMPUTING TOOLS; TIME SPENT;

ROUGH SET THEORY;

EID: 84861819666     PISSN: 0888613X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijar.2012.02.004     Document Type: Article

References (52)

1. J.G. Bazan, Dynamic reducts and statistical inference, in: Proceedings of 5th International Conference Information Processing and Management of Uncertainty in Knowledge-Based Systems IPMU'96, Granada, Spain, 1996, pp. 1147-1151.
2. J.G. Bazan A comparison of dynamic and non-dynamic rough set methods for extracting laws from decision tables L. Polkowski, A. Skowron, Rough Sets in Knowledge Discovery 1998 Physica-Verlag Heidelberg 321 365
3. I. Düntsch, and G. Gediga Uncertainty measures of rough set prediction Artificial Intelligence 106 1998 109 137 (Pubitemid 128402352)
4. S. Dick, A. Schenker, W. Pedrycz, and A. Kandel Regranulation: A granular algorithm enabling communication between granular worlds Information Science 177 2 2007 408 435 (Pubitemid 44634443)
5. M. Dash, and H. Liu Feature selection for classification Intelligent Data Analysis 1 1997 131 156
6. M. Dash, and H. Liu Consistency-based search in feature selection Artificial Intelligence 151 2003 155 176
7. I. Guyon, and A. Elisseeff An introduction to variable feature selection Machine Learning Research 3 2003 1157 1182
8. J.W. Guan, and D.A. Bell Rough computational methods for information systems Artificial Intelligence 105 1998 77 103 (Pubitemid 128398274)
9. J.W. Grzymala-Busse An algorithm for computing a single covering J.W. Grzymala-Busse, Managing Uncertainty in Expert Systems 1991 Kluwer Academic Publishers. Netherlands 66
10. J.W. Grzymala-Busse LERS l a system for learning from examples based on rough sets R. Slowinski, Intelligent Decision Support: Handbook of Applications and A dvances of the Rough Set Theory 1992 Kluwer Academic Publishers Netherlands 3 18
11. X.H. Hu, and N. Cercone Learning in relational databases: a rough set approach International Journal of Computational Intelligence 11 2 1995 323 338
12. Q.H. Hu, Z.X. Xie, and D.R. Yu Hybrid attribute reduction based on a novel fuzzy-rough model and information granulation Pattern Recognition 40 2007 3509 3521
13. Q.H. Hu, D.R. Yu, and Z.X. Xie Information-preserving hybrid data reduction based on fuzzy-rough techniques Pattern Recognition Letters 27 5 2006 414 423
14. V.N. Huynh, and Y. Nakamori A roughness measure for fuzzy sets Information Sciences 173 2005 255 275 (Pubitemid 40691106)
15. R. Jensen, and Q. Shen Semantics-preserving dimensionality reduction: rough and fuzzy-rough-based approaches IEEE Transactions on Knowledge and Data Engineering 16 12 2004 1457 1471 (Pubitemid 40010921)
16. R. Jensen, and Q. Shen Computational Intelligence and Feature Selection: Rough and Fuzzy Approaches 2008 IEEE Press/Wiley & Sons Canada
17. J.P. Jia Principles of Statistics Fourth ed. 2009 China Renmin University Publishing Beijing
18. Y.J. Jin, Z.F. Du, and Y. Jiang Sampling technique 2008 China Renmin University Publishing Beijing
19. G. Kader, and M. Perry Variability for Categorical Variables Journal of Statistics Education 15 2 2007
20. R. Kohavi, and G.H. John Wrappers for feature subset selection Artificial Intelligence 97 1-2 1997 273 324 (Pubitemid 127401107)
21. K. Kira, and L.A. Rendell The feature selection problem: traditional methods and a new algorithm Proceedings. AAAI 92 1992 129 134 (Pubitemid 23633599)
22. M. Kryszkiewicz, and P. Lasek FUN: fast discovery of minimal sets of attributes functionally determining a decision attribute Transactions on Rough Sets 9 2008 76 95
23. C.K. Lee, and G.G. Lee Information gain and divergence-based feature selection for machine learning-based text categorization Information Processing and Management 42 2006 155 165 (Pubitemid 41119082)
24. J.Y. Liang, K.S. Chin, C.Y. Dang, and C.M. Yam Richid A new method for measuring uncertainty and fuzziness in rough set theory International Journal of General Systems 31 4 2002 331 342 (Pubitemid 41623247)
25. J.Y. Liang, and Z.B. Xu The algorithm on knowledge reduction in incomplete information systems International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 10 1 2002 95 103
26. M. Modrzejewski, Feature selection using rough set theory, in: Proceedings of European Conference on Machine Learning, 1993, pp. 213-226.
27. D.Q. Miao, C. Gao, N. Zhang, and Z.F. Zhang Diverse reduct subspaces based co-training for partially labeled data International Journal of Approximate Reasoning 52 2011 1103 1117
28. N.S. Nguyen Approximate boolean reasoning: foundations and applications in data mining Lecture Notes in Computer Science 3100 2006 334 506
29. J.X. Ni Sampling survey 2002 Guangxi Normal University Press
30. W. Pedrycz, and G. Vukovich Feature analysis through information granulation and fuzzy sets Pattern Recognition 35 2002 825 834 (Pubitemid 34128809)
31. Z. Pawlak Rough Sets: Theoretical Aspects of Reasoning about Data 1991 Kluwer Academic Publishers. Boston
32. Z. Pawlak Rough set theory and its applications in data analysis Cybernetics and Systems 29 1998 661 688 (Pubitemid 128591850)
33. Z. Pawlak, and A. Skowron Rough sets and boolean reasoning Information Sciences 177 1 2007 41 73 (Pubitemid 44556700)
34. M. Perry, and G. Kader Variation as Unalikeability Teaching Statistics 27 2 2005 58 60
35. J. Qian, D.Q. Miao, Z.H. Zhang, and W. Li Hybrid approaches to attribute reduction based on indiscernibility and discernibility relation International Journal of Approximate Reasoning 52 2011 212 230
36. Y.H. Qian, J.Y. Liang, and C.Y. Dang Knowledge structure, knowledge granulation and knowledge distance in a knowledge base International Journal of Approximate Reasoning 50 1 2009 174 188
37. Y.H. Qian, J.Y. Liang, W. Pedrycz, and C.Y. Dang Positive approximation: an accelerator for attribute reduction in rough set theory Artificial Intelligence 174 2010 597 618
38. Y.H. Qian, J.Y. Liang, D.Y. Li, H.Y. Zhang, and C.Y. Dang Measures for evaluating the decision performance of a decision table in rough set theory Information Sciences 178 2008 181 202
39. Y.H. Qian, and J.Y. Liang Combination entropy and combination granulation in rough set theory International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 16 2 2008 179 193
40. R. Quinlan Induction of decision trees Machine Learning 1 1 1986 81 106
41. R.W. Swiniarski, and A. Skowron Rough set methods in feature selection and recognition Pattern Recognition Letters 24 2003 833 849 (Pubitemid 35391801)
42. A. Skowron Extracting laws from decision tables: a rough set approach Computational Intelligence 11 1995 371 388
43. D. Slezak Approximate entropy reducts Fundamenta Informaticae 53 3 - 4 2002 365 390
44. D. Tian, X.J. Zeng, and J. Keane Core-generating approximate minimum entropy discretization for rough set feature selection in pattern classification International Journal of Approximate Reasoning 52 2011 863 880
45. G.Y. Wang, H. Yu, and D.C. Yang Decision table reduction based on conditional information entropy Chinese Journal of Computer 25 7 2002 759 766 (Pubitemid 35339183)
46. G.Y. Wang, J. Zhao, and J.J. An A comparative study of algebra viewpoint and information viewpoint in attribute reduction Fundamenta Informaticae 68 3 2005 289 301
47. W. Wei, J.Y. Liang, Y.H. Qian, F. Wang, and C.Y. Dang Comparative study of decision performance of decision tables induced by attribute reductions International Journal of General Systems 39 8 2010 813 838
48. S.X. Wu, M.Q. Li, W.T. Huang, and S.F. Liu An improved heuristic algorithm of attribute reduction in rough set Journal of System Sciences and Information 2 3 2004 557 562
49. 2U/C)) Chinese Journal of Computer 29 3 2006 391 398
50. Y.Y. Yao Probabilistic rough set approximations International Journal of Approximate Reasoning 49 2 2008 255 271
51. Y.Y. Yao, and Y. Zhao Discernibility matrix simplification for constructing attribute reducts Information Sciences 179 5 2009 867 882
52. Y.Y. Yao, and Y. Zhao Attribute reduction in decision-theoretic rough set models Information Sciences 178 17 2008 3356 3373