A Complete Algorithm for Attribute Reduction

Abstract

Rough sets theory is an effective mathematical tool dealing with vagueness and uncertainty. It has been applied in a variety of fields such as data mining, pattern recognition or process control. It is significant to find high performance algorithms for attribute reduction. Most of presented algorithms were incomplete and the work on complete algorithms was comparatively little. This paper presented a complete algorithm based on the principle of discernibility matrix and discussed the time complexity of the algorithm. The proof of the completeness of the algorithm was also given in the paper. Finally, the validity of the algorithm was demonstrated by two classical databases in the UCI repository.