An efficient global optimization approach for rough set based dimensionality reduction

International Journal of Innovative Computing, Information and Control

Volumn 3, Issue 3, 2007, Pages 725-736

  Tan, Songbo ^a   Cheng, Xueqi ^a   Xu, Hongbo ^a  

^a INSTITUTE OF COMPUTING TECHNOLOGY   (China)

Author keywords

Dimensionality reduction; Information processing; Knowledge discovery; Rough set

Indexed keywords

EID: 63649141299     PISSN: 13494198     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (23)

1. Pawlak, Z., Rough sets, International Journal of Computer and Information Science, vol.11, no.5, pp.341-356, 1982.
2. Pawlak, Z., Rough Sets: Theoretical Aspects of Reasoning About Data, Kluwer Academic Publishers, Dordrecht, 1991.
3. Pal, S. K. and A. Skowron, Rough Fuzzy Hybridization - A New Trend in Decision-making, Springer, 1999.
4. Wang J. and J. Wang, Reduction algorithms based on discernibility matrix: The ordered attributes method, Journal of Computer Science & Technology, vol.16, no.6, pp.489-504, 2001.
5. Hu, K., Y. Lu and C. Shi, Feature Ranking in Rough Sets, http://citeseer.nj.nec.com/587273.html.
6. Hu, K., L. Diao, Y. Lu and C. Shi, Sampling for Approximate Reduct in Very Large Datasets, http://citeseer.nj.nec.com/587308.html.
7. Hu, X., Knowledge Discovery in Databases: An Attribute-oriented Rough Set Approach, Ph.D. Thesis, Regina University, 1995.
8. Hu, X. H. and N. Cercone, Learning in relational databases: A rough set approach, International Journal of Computational Intelligence, vol.11, no.2, pp.232-338, 1995.
9. Jelonek, J., K. Krawiec and R. Slowinski, Rough set reduction of attributes and their domains for neural networks, International Computational Intelligence, vol.11, no.2, pp.339-347, 1995.
10. Guan, J. W. and D. A. Bell, Rough computational methods for information systems, Artificial Intelligences, vol. 105, nos.1-2, pp.77-103, 1998.
11. The ROSETTA homepage [http://www.idi.ntnu.no/~aleks/rosetta/], Norwegian University of Science and Technology, Department of Computer and Information Science.
12. Lui, S., Research on Rough Set Theory in Knowledge Discovery, Ph.D. Thesis, Institute of Computer Technology, China Academy of Science, China, 2003.
13. Vinterbo, S. and A. Øhrn, Minimal approximate hitting sets and rule templates, International Journal of Approximate Reasoning, vol.25, no.2, pp.123-143, 2000.
14. Vinterbo, S. and A. Øhrn, Minimal approximate hitting sets and rule templates, in Predictive Models in Medicine: Some Methods for Construction and Adaptation, Department of Computer and Information Science, NTNU Report 1999:130. http://www.idi.ntnu.no/~staalv/dev/thesis.ps.gz.
15. Johnson, D. S., Approximation algorithms for combinatorial problems, Journal of Computer and System Sciences, vol.9, pp.256-278, 1974.
16. Nguyen, S. H. and H. S. Nguyen, Some Efficient Algorithms for Rough Set Methods, 1996.
17. Bazan, J. G., A comparison of dynamic and non-dynamic rough set methods for extracting laws from decision tables, in Rough Sets in Knowledge Discovery 1: Methodology and Applications, L. Polkowski and A. Skowron (eds), Chapter 17, pp.321-365, 1994.
18. Bazan, J. G., A. Skowron and P. Synak, Dynamic reducts as a tool for extracting laws from decision tables, Proc. of the International Symposium on Methodologies for Intelligent Systems, Lecture Notes in Artificial Intelligence, Springer-Verlag, vol.869, pp.346-355, 1994.
19. Bazan, J. G., Dynamic Reducts and Statistical Inference. 1996.
20. Polkowski, L. and A. Skowron (eds), Rough Sets in Knowledge Discovery 1: Methodology and Applications, vol. 18 of Studies in Fuzziness and Soft Computing, Physica-Verlag, Heidelberg, Germany, 1998.
21. Merz, C. J. and P. Murphy, UCI Repository of Machine Learning Database, http://www.ics.uci.edu/~mlearn/MLRepository.html.
22. Gu, J., Global optimization for satisfiability (SAT) problem, IEEE Transactions on Knowledge and Data Engineering, vol.6, no.3, pp.361-381, 1994.
23. Tan, S., H. Xu and J. Gu, Efficient algorithms for attributes reduction problem, International Journal of Innovative Computing, Information & Control, vol.l, no.4, pp.767-777, 2005.