Local reducts and jumping emerging patterns in relational databases

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4259 LNAI, Issue , 2006, Pages 358-367

  Terlecki, Pawel ^a   Walczak, Krzysztof ^a  

^a WARSAW UNIVERSITY OF TECHNOLOGY   (Poland)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); COMPUTER AIDED SOFTWARE ENGINEERING; DATA STRUCTURES; ROUGH SET THEORY;

JUMPING EMERGING PATTERN; LOCAL REDUCTS; REAL RELATIONAL DATASETS;

RELATIONAL DATABASE SYSTEMS;

EID: 33845239003     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11908029_38     Document Type: Conference Paper

References (11)

1. H. Fan, Efficient Mining of Interesting Emerging Patterns and Their Effective Use in Classification. University of Melbourne: PhD thesis, 2004.
2. G. Dong and J. Li, "Mining border descriptions of emerging patterns from dataset pairs," Knowl. Inf. Syst., vol. 8, no. 2, pp. 178-202, 2005.
3. J. Wroblewski, The Adaptive Methods for Object Classification. Warsaw University, Institute of Informatics: PhD thesis, 2002.
4. P. Terlecki and K. Walczak, "On the relation between rough set reducts and jumping emerging patterns," Information Sciences, 2006 (to be published).
5. A. Skowron and C. Rauszer, "The discernibility matrices and functions in information systems," in Intelligent Decision Support (R. Slowinski, ed.), (Dordrecht, The Netherlands), pp. 331-362, Kluwer Academic Publishers, 1992.
6. J. Bazan, H. S. Nguyen, S. H. Nguyen, P. Synak, and J. Wroblewski, "Rough set algorithms in classification problem," Rough set methods and applications: new developments in knowl. disc, in inf. syst., pp. 49-88, 2000.
7. J. Li, G. Dong, K. Ramamohanarao, and L. Wong, "Deeps: A new instance-based lazy discovery and classification system," Mach. Learn., vol. 54, no. 2, pp. 99-124, 2004.
8. N. Shan and W. Ziarko, "An incremental learning algorithm for constructing decision rules," in Rough Sets, Fuzzy Sets and Knowledge Discovery (W. Ziarko, ed.), pp. 326-334, Springer Verlag, Berlin, 1994.
9. P. Terlecki and K. Walczak, "Attribute set dependence in apriori-like reduct computation," in Rough Sets and Knowl. Techn., 2006 (to be published).
10. M. Jürgens and H.-J. Lenz, "Tree based indexes vs. bitmap indexes - a performance study.," Int. Journal of Cooperative Inf. Syst., vol. 10, no. 3, pp. 355-376, 2001.
11. C. B. D.J. Newman, S. Hettich and C. Merz, "UCI repository of machine learning databases," 1998.