AN ALGORITHM BASED ON ROUGH SET THEORY FOR DATA FILTERING

The rough set approach is an important tool to deal with uncertain or vague knowledge in AI applications. In this paper, the rough set theory is studied, and an algorithm based on the rough set theory for data filtering is proposed. Theoretical analysis and experimental result show this algorithm can effectively reduce granulation of attribute measurement and obtain a higher strength of prediction in terms of the statistical significance of rules.