Attribute Reduction Algorithm of Rough Sets Based on Discernibility Matrix
Zhen Ye · Jisuanji fangzhen · 2008
The efficiency of algorithm for attribute reduction in rough set theory based on discernibility matrix was impacted by the number of non-empty elements in discernibility matrix. The disadvantages of some discernibility matrices were analyzed. According to this, a new discernibility matrix was redefined, which regarded a decision-making class [xj]C as a decision-making rule, where [xj]C ∈U/C. Therefore, it decreased greatly the number of non-empty elements, which improved the efficiency of algorithm for attribute reduction based on discernibility matrix. And the formulas computing the number of non-empty elements in these discernibility matrices and some theorems were introduced. An algorithm based on heuristic information was proposed. At most time, this algorithm can find out a minimal attribute reduction. Lastly, the simulation experiments for UCI database were displayed.