Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

On the structure of definable sets in covering approximation spaces

  • Original Article
  • Published:
International Journal of Machine Learning and Cybernetics Aims and scope Submit manuscript

Abstract

Covering rough sets, a generalization of the classical rough sets, are main research topics of rough set theory. Various covering rough set models have been proposed. In this paper, ten important types of covering rough set models are first reviewed. The algebraic structures of definable sets, inner definable sets and outer definable sets in these covering rough sets are then investigated. Based on the concept of definable sets, we further explore relations among the ten covering rough sets. Finally, the conditions for neighborhood \(\{N(x):x\in U\}\) to form a partition of the universe U are discussed, and an open problem proposed by Yun et al. is answered.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. Angiulli F, Pizzuti C (2005) Outlier mining in large high-dimensional data sets. IEEE Trans Knowl Data Eng 17(2):203–215

    Article  MathSciNet  Google Scholar 

  2. Bonikowski Z, Bryniarski E, Wybraniec U (1998) Extensions and intentions in the rough set theory. Inf Sci 107:149–167

    Article  MATH  Google Scholar 

  3. Cattaneo G (1998) Abstract approximation spaces for rough theories. In: Polkowski L, Skowron A (eds) Rough sets in knowledge discovery. Methodology and applications, Physica-Verlag, Heidelberg, pp 59–98

  4. Chen D, Wang C, Hu Q (2007) A new approach to attribute reduction of consistent and inconsistent covering decision systems with covering rough sets. Inf Sci 177:3500–3518

    Article  MATH  Google Scholar 

  5. Dubois D, Prade H (1990) Rough fuzzy sets and fuzzy rough sets. Int J Gen Syst 17:191–209

    Article  MATH  Google Scholar 

  6. Ge X, Li J, Ge Y (2010) Some separations in covering approximation. Int J Comput Math Sci 4:156–160

    MathSciNet  Google Scholar 

  7. Ge X, Li Z (2011) Definable subsets in covering approximation spaces. Int J Comput Math Sci 5(1):31–34

    MathSciNet  Google Scholar 

  8. Hall M, Holmes G (2003) Benchmarking attribute selection techniques for discrete class data mining. IEEE Trans Knowl Data Eng 15(6):1437–1447

    Article  Google Scholar 

  9. He Q, Wu C, Chen D, Zhao S (2011) Fuzzy rough set based attribute reduction for information systems with fuzzy decisions. Knowl Based Syst 24:689–696

    Article  Google Scholar 

  10. Hu Q, Pan W, An S, Ma P, Wei J (2011) An efficient gene selection technique for cancer recognition based on neighborhood mutual information. Int J Mach Learn Cybern 1:63–74

    Article  Google Scholar 

  11. Kondo M (2006) On the structure of generalized rough sets. Inf Sci 176:589–600

    Article  MathSciNet  MATH  Google Scholar 

  12. Leung Y, Wu WZ, Zhang WX (2006) Knowledge acquisition in incomplete information systems: a rough set approach. Eur J Oper Res 168:164–180

    Article  MathSciNet  MATH  Google Scholar 

  13. Li TJ, Leung Y, Zhang WX (2008) Generalized fuzzy rough approximation operators based on fuzzy coverings. Int J Approx Reason 48(3):836–856

    Article  MathSciNet  MATH  Google Scholar 

  14. Li T, Ruan D, Geert W, Song J, Xu Y (2007) A rough sets based characteristic relation approach for dynamic attribute generalization in data mining. Knowl Based Syst 20:485–494

    Article  Google Scholar 

  15. Lingras P, Butz C (2007) Rough set based 1-v-1 and 1-v-r approaches to support vector machine multi-classification. Inf Sci 177:3782–3798

    Article  Google Scholar 

  16. Liu G, Zhu W (2008) The algebraic structures of generalized rough set theory. Inf Sci 178:4105–4113

    Article  MATH  Google Scholar 

  17. Liu G (2008) Axiomatic systems for rough sets and fuzzy rough sets. Int J Approx Reason 48:857–867

    Article  MATH  Google Scholar 

  18. Liu G, Sai Y (2009) A comparison of two types of rough sets induced by coverings. Int J Approx Reason 50:521–528

    Article  MathSciNet  MATH  Google Scholar 

  19. Liu G (2010) Rough set theory based on two universal sets and its applications. Knowl Based Syst 23:110–115

    Article  Google Scholar 

  20. Nanda S, Majumda S (1992) Fuzzy rough sets. Fuzzy Sets Syst 45:157–160

    Article  MATH  Google Scholar 

  21. Pawlak Z (1982) Rough sets. Int J Comput Inf Sci 5:341–356

    Article  MathSciNet  Google Scholar 

  22. Pawlak Z (1991) Rough sets: theoretical aspects of reasoning about data. Kluwer, Dordrecht

    MATH  Google Scholar 

  23. Pei D (2005) A generalized model of fuzzy rough sets. Int J Gen Syst 34(5):603–613

    Article  MathSciNet  MATH  Google Scholar 

  24. Pei D (2007) On definable concepts of rough set models. Inf Sci 177:4230–4239

    Article  MATH  Google Scholar 

  25. Polkowski L, Skowron A (1998) Rough sets in knowledge discovery, vol 1. Physica-Verlag, Heidelberg

  26. Polkowski L, Skowron A (1998) Rough sets in knowledge discovery, vol 2. Physica-Verlag, Heidelberg

  27. Pomykala J (1987) Approximation operations in approximation spaces. Bull Pol Acad Sci 35:653–662

    MathSciNet  MATH  Google Scholar 

  28. Qin K, Gao Y, Pei Z (2007) On covering rough sets. Lect Notes AI 4481:34–41

    Google Scholar 

  29. Radzikowska A, Kerre E (2002) A comparative study of fuzzy rough sets. Fuzzy Sets Syst 126:137–155

    Article  MathSciNet  MATH  Google Scholar 

  30. Sidorov G, Koeppen M, Cruz-Cortés N (2011) Recent advances in machine learning techniques and applications. Int J Mach Learn Cybern 2(3):123–124

    Article  Google Scholar 

  31. Skowron A, Stepaniuk J (1996) Tolerance approximation spaces. Fundam Inform 27:245–253

    MathSciNet  MATH  Google Scholar 

  32. Skowron A, Vanderpooten D (2000) A generalized definition of rough approximations based on similarity. IEEE Trans Knowl Data Eng 12:331–336

    Article  Google Scholar 

  33. Tsang ECC, Chen D, Yeung DS (2008) Approximations and reducts with covering generalized rough sets. Comput Math Appl 56:279–289

    Article  MathSciNet  MATH  Google Scholar 

  34. Vagin V, Fomina M (2011) Problem of knowledge discovery in noisy databases. Int J Mach Learn Cybern 2(3):135–145

    Article  Google Scholar 

  35. Wang X, Hong J (1999) Learning optimization in simplifying fuzzy rules. Fuzzy Sets Syst 106(3):349–356

    Article  MathSciNet  MATH  Google Scholar 

  36. Wang X, Tsang ECC, Zhao S, Chen D, Yeung DS (2007) Learning fuzzy rules from fuzzy samples based on rough set techniques. Inf Sci 177:4493–4514

    Article  MathSciNet  MATH  Google Scholar 

  37. Wang XZ, Zhai JH, Lu SX (2008) Induction of multiple fuzzy decision trees based on rough set technique. Inf Sci 178:3188–3202

    Article  MathSciNet  MATH  Google Scholar 

  38. Wang XZ, Lu SX, Zhai JH (2008) Fast fuzzy multi-category SVM based on support vector domain description. Int J Pattern Recognit Artif Intell 22(1):109–120

    Article  Google Scholar 

  39. Wang XZ, He YL, Dong LC, Zhao HY (2011) Particle swarm optimization for determining fuzzy measures from data. Inf Sci 181(19):4230–4252

    Article  MATH  Google Scholar 

  40. Wu WZ, Zhang WX, Li HZ (2003) Knowledge acquisition in incomplete fuzzy information systems via rough set approach. Expert Syst 20(5):280–286

    Article  Google Scholar 

  41. Wu WZ, Mi JS, Zhang WX (2003) Generalized fuzzy rough sets. Inf Sci 151:263–282

    Article  MathSciNet  MATH  Google Scholar 

  42. Wu WZ (2008) Attribute reduction based on evidence theory in incomplete decision systems. Inf Sci 178:1355–1371

    Article  MATH  Google Scholar 

  43. Wu WZ, Zhang M, Li HZ, Mi JS (2005) Knowledge reduction in random information systems via Dempster–Shafer theory of evidence. Inf Sci 174:143–164

    Article  MathSciNet  MATH  Google Scholar 

  44. Xu F, Yao Y, Miao D (2008) Rough Set Approximations in formal concept analysis and knowledge spaces. In: Proceedings of the 17th international conference on foundations of intelligent systems. LNAI, vol 4994, Toronto, Canada, pp 319–328

  45. Xu WH, Zhang WX (2007) Measuring roughness of generalized rough sets induced by a covering. Fuzzy Sets Syst 158:2443–2455

    Article  MATH  Google Scholar 

  46. Yang L, Xu L (2009) Algebraic aspects of generalized approximation spaces. Int J Approx Reason 51:151–161

    Article  MATH  Google Scholar 

  47. Yang X, Song X, Chen Z, Yang J (2011) On multigranulation rough set in incomplete information system. Int J Mach Learn Cybern. doi:10.1007/s13042-011-0054-8

  48. Yao YY (1996) Two views of the theory of rough sets in finite universe. Int J Approx Reason 15(4):291–317

    Article  MATH  Google Scholar 

  49. Yao YY (1998) Constructive and algebraic methods of the theory of rough sets. Inf Sci 109:21–47

    Article  MATH  Google Scholar 

  50. Yao YY (1998) On generalized Pawlak approximation operators. In: Rough sets and current trends in computing. LNAI, vol 1424, pp 298–307

  51. Yi W, Lu M, Liu Z (2011) Multi-valued attribute and multi-labeled data decision tree algorithm. Int J Mach Learn Cybern 2:67–74

    Article  Google Scholar 

  52. Yun Z, Ge X, Bai X (2011) Axiomatization and conditions for neighborhoods in a covering to form a partition. Inf Sci 181:1735–1740

    Article  MathSciNet  MATH  Google Scholar 

  53. Zhai J (2011) Fuzzy decision tree based on fuzzy-rough technique. Soft Comput 15(6):1087–1096

    Article  Google Scholar 

  54. Zhu W, Wang FY (2003) Reduction and axiomization of covering generalized rough sets. Inf Sci 152:217–230

    Article  MATH  Google Scholar 

  55. Zhu W (2006) Properties of the fourth type of covering-based rough sets. In: HIS’06, AUT Technology Park, Auckland, New Zealand, 13–15 December, pp 43–46

  56. Zhu W (2007) Topological approaches to covering rough sets. Inf Sci 177(6):1499–1508

    Article  MATH  Google Scholar 

  57. Zhu W, Wang FY (2007) On three types of covering rough sets. IEEE Trans Knowl Data Eng 19(8):1131–1144

    Article  Google Scholar 

  58. Zhu W (2007) Generalized rough sets based on relations. Inf Sci 177:4997–5011

    Article  MATH  Google Scholar 

  59. Zhu W (2009) Relationship between generalized rough sets based on binary relation and covering. Inf Sci 179:210–225

    Article  MATH  Google Scholar 

  60. Zhu W (2009) Relationship among basic concepts in covering-based rough sets. Inf Sci 179:2478–2486

    Article  MATH  Google Scholar 

  61. Zhu W, Wang S (2011) Matroidal approaches to generalized rough sets based on relations. Int J Mach Learn Cybern 2(4):273–279

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by grants from the National Natural Science Foundation of China (Nos. 10971186, 71140004 and 11061004), the Natural Science Foundation of Fujian Province (Nos. JK2011031, 2011J01374), the Department of Education of Fujian Province (No. JA11171) and the Science Foundation of Zhangzhou Normal University in China (No. SJ1015).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jinkun Chen.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chen, J., Li, J. & Lin, Y. On the structure of definable sets in covering approximation spaces. Int. J. Mach. Learn. & Cyber. 4, 195–206 (2013). https://doi.org/10.1007/s13042-012-0086-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13042-012-0086-8

Keywords