Studies on rough sets in multiple tables

Authors:
R. S. Milton;V. Uma Maheswari;Arul Siromoney
Affiliations:
Department of Computer Science, Madras Christian College, Chennai, India;Department of Computer Science and Engineering, College of Engineering Guindy, Anna University, Chennai, India;Department of Computer Science and Engineering, College of Engineering Guindy, Anna University, Chennai, India
Venue:
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part I
Year:
2005

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Abstract

Rough Set Theory is a mathematical tool to deal with vagueness and uncertainty. Rough Set Theory uses a single information table. Relational Learning is the learning from multiple relations or tables. This paper studies the use of Rough Set Theory and Variable Precision Rough Sets in a multi-table information system (MTIS). The notion of approximation regions in the MTIS is defined in terms of those of the individual tables. This is used in classifying an example in the MTIS, based on the elementary sets in the individual tables to which the example belongs. Results of classification experiments in predictive toxicology based on this approach are presented.