Abstract
This paper introduces an approach of condition combination to generate rules in a decision table. First we describe the concepts of negative condition and condition combination upon which our work is based, then their important properties for designing our algorithms. The algorithms are analyzed to show their time complexity and concern with attribute ordering.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Pawlak, Z. 1982. Rough Sets, Information and Computer Science, 11(5),341–356
Ziarko, W. and Shan, N. 1995. Knowledge discovery as a search for classification, Workshop on Rough Sets and Database Mining, 23rd Annual Computer Science, CSC'95
Cercone, N., Hamilton, H. J., Hu, X. and Shan, N. 1997. Data mining using attribute-oriented generalization and information reduction, in Rough sets and data mining: analysis for imprecise data, T.Y.Lin and N.Cercone eds., Kluwer Academic Publishers.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1998 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Xue, H., Cai, Q. (1998). Rule generalization by condition combination. In: Wu, X., Kotagiri, R., Korb, K.B. (eds) Research and Development in Knowledge Discovery and Data Mining. PAKDD 1998. Lecture Notes in Computer Science, vol 1394. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-64383-4_51
Download citation
DOI: https://doi.org/10.1007/3-540-64383-4_51
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-64383-8
Online ISBN: 978-3-540-69768-8
eBook Packages: Springer Book Archive