Rule generation based on rough set theory

Guoyin Wang; Yu Wu; Paul S. Fisher

doi:10.1117/12.381732

6 April 2000 Rule generation based on rough set theory

Guoyin Wang, Yu Wu, Paul S. Fisher

Proceedings Volume 4057, Data Mining and Knowledge Discovery: Theory, Tools, and Technology II; (2000) https://doi.org/10.1117/12.381732
Event: AeroSense 2000, 2000, Orlando, FL, United States

Abstract

In this paper, we propose an approach that can generate logical rules from an information system. It is based on Pawlak's rough set theory. There are two steps in our rule generation approach. First, attribute reduction is done on an information table according to Skowron's discernibility matrix and logic function simplification, some important and valuable attributes are extracted. Then, value reduction is performed and corresponding logic rules are generated. All reducts including the minimal reduct of an information system can be obtained through these two reductions. Our approach can generate both the maximal generalized decision rules as well as potential interesting and useful rules according to requirements.

Citation Download Citation

Guoyin Wang, Yu Wu, and Paul S. Fisher "Rule generation based on rough set theory", Proc. SPIE 4057, Data Mining and Knowledge Discovery: Theory, Tools, and Technology II, (6 April 2000); https://doi.org/10.1117/12.381732

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