β-Interval attribute reduction in variable precision rough set model

Soft Computing

Volumn 15, Issue 8, 2011, Pages 1643-1656

  Zhou, Jie ^a   Miao, Duoqian ^a  

^a TONGJI UNIVERSITY   (China)

Author keywords

Interval core; Interval reduct; Interval characteristic sets; Shadowed sets; Variable precision rough set model (VPRSM)

Indexed keywords

ATTRIBUTE CORE; ATTRIBUTE REDUCTION; CHARACTERISTIC SET; DISCERNIBILITY MATRIX; EVALUATION FUNCTION; INTERVAL ATTRIBUTE; NOVEL METHODS; PAWLAK'S ROUGH SET MODEL; PRECISION PARAMETER; REDUCT DEFINITIONS; SHADOWED SETS; THEORY AND PRACTICE; VARIABLE-PRECISION ROUGH SET MODEL;

HEURISTIC ALGORITHMS; OPTIMIZATION;

ROUGH SET THEORY;

EID: 79960104935     PISSN: 14327643     EISSN: 14337479     Source Type: Journal    
DOI: 10.1007/s00500-011-0693-4     Document Type: Article

References (42)

1. An A, Shan N, Chan C (1996) Discovering rules for water demand prediction: an enhanced rough set approach. Eng Appl Artif Intell 9: 645-653.
2. Anantaram C, Nagaraja G, Nori KV (1998) Verification of accuracy of rules in a rule based system. Data Knowl Eng 27: 115-138.
3. Beynon M (2000) An investigating of β-reduct selection within the variable precision rough sets model. In: The second international conference on rough sets and current trend in computing (RSCTC 2000). LNAI 2005: 114-122.
4. Beynon M (2001) Reducts within the variable precision rough sets model: a further investigation. Eur J Oper Res 134: 595-597.
5. Beynon M (2003) The introduction and utilization of (l-u)-graphs in the extended variable precision rough sets model. Int J Intell Syst 18: 1035-1055.
6. Beynon M, Peel MJ (2001) Variable precision rough set theory and data discretization: an application to corporate failure prediction. Int J Manag Sci 29: 561-576.
7. Dimitras AI et al (1999) Business failure using rough sets. Eur J Oper Res 114: 263-280.
8. Dubois D, Prade H (1999) Rough fuzzy sets and fuzzy rough sets. Int J Gen Syst 17: 191-209.
9. Greco S, Matarazzo B, Slowinski R (2008) Parameterized rough set model using rough membership and Bayesian confirmation measures. Int J Approx Reason 49: 285-300.
10. Herbert JP, Yao JT (2009) Criteria for choosing a rough set model. Comput Math Appl 57: 908-918.
11. Jelonek J, Krawiec K, Slowinski R (1995) Rough set reduction of attributes and their domains for neural networks. Int J Comput Intell 11: 339-347.
12. Katzberg JK, Ziarko W (1993) Variable precision rough sets with asymmetric bounds. In: Ziarko W, Rijsbergen CJ (eds) Rough sets, fuzzy sets and knowledge discovery. Springer, New York, pp 167-177.
13. Mushrif MM, Ray AK (2008) Color image segmentation: rough-set theoretic approach. Pattern Recogn Lett 29: 483-493.
14. Pawlak Z (1982) Rough sets. Int J Comput Inf Sci 11: 314-356.
15. Pawlak Z, Skowron A (2007) Rudiments of rough sets. Inf Sci 177: 3-27.
16. Pawlak Z, Wong SKM, Ziarko W (1988) Rough sets: probabilistic versus deterministic approach. Int J Man Mach Stud 29: 81-95.
17. Pedrycz W (1998) Shadowed sets: representing and processing fuzzy sets. IEEE T Syst Man Cybern B 28: 103-109.
18. Pedrycz W (1999) Shadowed sets: bridging fuzzy and rough sets. In: Pal SK, Skowron A (eds) Rough fuzzy hybridization a new trend in decision-making. Springer, Singapore, pp 179-199.
19. Pedrycz W (2005) Interpretation of clusters in the framework of shadowed sets. Pattern Recogn Lett 26: 2439-2449.
20. Pedrycz W (2009) From fuzzy sets to shadowed sets: interpretation and computing. Int J Intell Syst 24: 48-61.
21. Pedrycz W, Bukovich G (2002) Granular computing with shadowed sets. Int J Intell Syst 17: 173-197.
22. Shen Q, Chouchoulas A (2002) A rough-fuzzy approach for generating classification rules. Pattern Recogn Lett 35: 2425-2438.
23. Skowron A, Rauszer C (1991) The discernibility matrices and functions in information systems. In: Slowinski R (eds) Intelligent decision support: handbook of applications and advances of the rough sets theory. Kluwer, Dordrecht, pp 331-362.
24. Slezak D (2003) Attribute reduction in the Bayesian version of variable precision rough set model. Electron Notes Theor Comput Sci 82: 1-11.
25. Slezak D, Ziarko W(2002) Bayesian rough set model. In: Proceedings of the international workshop on foundation of data mining (FDM'2002). Maebashi, Japan, pp 131-135.
26. Slezak D, Ziarko W (2005) The investigation of the Bayesian rough set model. Int J Approx Reason 40: 81-91.
27. Su C-T, Hsu J-H (2006) Precision parameter in the variable precision rough sets model: an application. Int J Manag Sci 34: 149-157.
28. Thangavel K, Pethalakshmi A (2009) Dimensionality reduction based on rough set theory: a review. Appl Soft Comput 9: 1-12.
29. Wang J, Miao DQ (1998) Analysis on attribute reduction strategies of rough set. J Comput Sci Technol 13: 189-193.
30. Wang JY, Zhou J (2009) Research of reduct features in the variable precision rough set model. Neurocomputing 72: 2643-2648.
31. Wang RZ, Miao DQ, Hu GR et al (2006) Discernibility matrix based algorithm for reduction of attributes. In: Butz CJ (eds) Web intelligence and intelligent agent technology. IEEE Computer Society, Hong Kong, pp 477-480.
32. Wojciech K et al (2008) Stochastic dominance-based rough set model for ordinal classification. Inf Sci 178: 4019-4037.
33. Yao YY (2003) Probabilistic approaches to rough sets. Expert Syst 20: 287-297.
34. Yao Y Y (2007) Decision-theoretic rough set modes. In: Proceedings of RSKT'07. LNAI 4481: 1-12.
35. Yao YY (2008) Probabilistic rough set approximations. Int J Approx Reason 49: 255-271.
36. Yao YY, Wong SKM (1992) A decision theoretic framework for approximating concepts. Int J Man Mach Stud 37: 793-809.
37. Yao YY, Zhao Y (2008) Attribute reduction in decision-theoretic rough set model. Inf Sci 178: 3356-3373.
38. Yao YY, Wong SKM, Lingras P (1990) A decision-theoretic rough set model. In: Ras ZW et al (eds) Methodologies for intelligent systems. North-Holland, New York, pp 17-24.
39. Yao Y Y, Zhao Y, Wang J (2006) On reduct construction algorithms. In: Proceedings of RSKT'06. LNAI 4062: 297-304.
40. Zhu W, Wang FY (2003) Reduction and axiomization of covering generalized rough sets. Inf Sci 152: 217-230.
41. Ziarko W (1993) Variable precision rough set model. J Comput Syst Sci 46: 44-54.
42. Ziarko W (1999) Decision making with probabilistic decision tables. In: Proceedings of RSFDGrC'99. LNAI 1711: 463-471.