Application of variable precision rough set approach to car driver assessment

Next Generation of Data-Mining Applications

Volumn , Issue , 2005, Pages 149-164

  Aryeetey, Kwei ^a   Ziarko, Wojciech ^a   Quaye, Kwei ^b  

^a UNIVERSITY OF REGINA   (Canada)

^b Saskatchewan Govemment Insurance   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 70350744467     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1109/9780471696650     Document Type: Chapter

References (16)

1. Aryeetey, K., Ziarko, W., Tai, P., and Ago, C, Identification of rules for brain metastases and survival time prediction for small cell lung cancer patients, in Proceedings of International Symposium “Intelligent Information Systems” Physica-Verlag, Zakopane, Poland, pp. 1-12, 2001.
2. Grzymala-Busse, J., and Ziarko. W., Data mining based on rough sets, in Data Mining: Opportunities and Challenges, IDEA Group Publishing, Hershey, PA, pp. 142-173, 2003.
3. Insurance Research Council: Motor vehicle records may not provide an accurate or complete account of driving histories, http://www.ircweb.org/news/NewsReleases/20020626.htm, 2002.
4. Katzberg, J., and Ziarko, W., Variable precision rough sets with asymmetric bounds, in Proceedings of the International Workshop on Rough Sets and Knowledge Discovery (RSKD '93), pp. 163-191, 1993.
5. Pawlak, Z., Rough Sets-Theoretical Aspects of Reasoning About Data, Kluwer Academic Publishers, Dordrecht, 1991.
6. Quaye, K., Using Prior Convictions and Accidents to Identify Unsafe Drivers-An examination of Saskatchewan’s Delinquent Driver Program, Saskatchewan Government Insurance, Regina, Saskatchewan, Canada, 1997.
7. Ślęzak, D., and Ziarko, W., Bayesian rough set model, in Proceedings of FDM '2002. December 9, Maebashi, Japan pp. 131-135, 2002.
8. South Carolina Department of Insurance: Factors Affecting Insurance Cost, http ://www.doi. state. sc .us/Eng/Public/FormPub/CoatFactors. asp. 2003.
9. Stewart, J. R., and Campbell, B., The Statistical Association Between Past and Future Accidents and Violations, University of North Carolina, Chapel Hill, NC, 1972.
10. Yao, Y. Y., and Wong, S. K. M., A decision theoretic framework for approximating concepts, International Journal of Man-Machine Studies 37, 793-809 (1992).
11. Ziarko, W., Variable precision rough sets model, Journal of Computer and Systems Sciences 46(1), 39-59 (1993).
12. Ziarko, W., Approximation region-based decision tables, in Rough Sets and Current Trends in Computing, Polkowski, L., and Skowron, A. (eds.), Lecture Notes in AI 1424, Springer-Verlag, Berlin, pp. 178-185, 1998.
13. Ziarko, W., Decision making with probabilistic decision tables, in Proceedings of the 7th International Workshop on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, RSFDGrC '99, Yamaguchi, Japan, Lecture Notes in AI 1711, Springer-Verlag, Berlin, pp. 463-471, 1999.
14. Ziarko, W., Probabilistic decision tables in the variable precision rough set model, Computational Intelligence: an International Journal 17(3), 593-603 (2001a) .
15. Ziarko, W., Set approximation quality measures in the variable precision rough set model, Proceedings of the International Conference on Hybrid Intelligent Systems, in Soft Computing Systems, Management and Applications, IOS Press, Amsterdam, 442-452, 2001b .
16. Ziarko, W., Acquisition of hierarchy-structured probabilistic decision tables and rules from data, in Proceedings of IEEE International Conference on Fuzzy Systems, Honolulu, pp. 779-784, 2002.