Incremental versus non-incremental: Data and algorithms based on ordering relations

International Journal of Computational Intelligence Systems

Volumn 4, Issue 1, 2011, Pages 112-122

  Jia, Xiuyi ^a   Shang, Lin ^a   Chen, Jiajun ^a   Dai, Xinyu ^a  

^a NANJING UNIVERSITY   (China)

Author keywords

Data concentration; Data saturation; Dominance based rough set approach; Incremental rule induction

Indexed keywords

ROUGH SET THEORY;

DATA CONCENTRATION; DOMINANCE-BASED ROUGH SET APPROACH; INCREMENTAL ALGORITHM; INCREMENTAL RULE INDUCTIONS; LARGE DATASETS; PERFORMANCE ANALYSIS; RULE INDUCTION ALGORITHMS; TIME COMPLEXITY ANALYSIS;

MATRIX ALGEBRA;

EID: 78851472000     PISSN: 18756891     EISSN: 18756883     Source Type: Journal    
DOI: 10.1080/18756891.2011.9727768     Document Type: Article

References (10)

1. Chen, Z. L., and Chen, G. Q., 2008. Building an associate classifier based on fuzzy association rules. International Journal of Computational Intelligence Systems, 1–3:262–272.
2. Greco, S., Matarazzo, B., Slowinski, R., and Stefanowinski, J., An algorithm for induction of decision rules consistent with the dominance principle. Proc. Intl. Conf. On Rough Sets and Current Trends in Computing. pp. 304–313.
3. Greco, S., Slowinski, R., Stefanowski, J., and Zurawski, M., 2004. Incremental versus non-incremental rule induction for multicriteria classification. Transaction on Rough Sets, II:33–53.
4. Jia, X. Y., Shang, L., and Chen, J. J., 2007. Rule induction algrithom based on dominance-based on rough set approach(in Chinese). Journal of Jiangnan University(Natural Science Edition), 6 (6):686–689.
5. Liu, Y., Xu, C. F., Lin, T. Y., and Pan, Y. H., Incremental supervised rule mining from inconsistent redundancy data. Proc. Intl. Conf. On Data MiningWORKSHOP Foundations of Secmantic Oriented Data and Web Mining. pp. 46–48.
6. Pawlak, Z., 1991. Rough Sets, Theoretical Aspects of Reasoning about Data, Dordrecht, Boston, London:Kluwer Academic Publishers.
7. Yao, Y. Y., and Lin, T. Y., 1996. Generalization of rough sets using modal logic. Intelligent Automation and Soft Computing, 2 (2):103–120.
8. Yao, Y. Y., and Sai, Y., 2001. Mining ordering rules using rough set theory. Bulletin of International Rough Set Society, 5:99–106.
9. Yao, Y. Y., 2003. Mining high order decision rules. Rough Set Theory and Granular Computing,:125–135.
10. Yao, Y. Y., Zhou, B., and Chen, Y. H., Interpreting low and high order rules:a granular computing approach. Proc. Intl Conf. On Rough Sets and Emerging Intelligent System Paradigms. Vol. 4585, pp. 371–380. LNAI.