关键词: 粗糙集, 属性约简, 带权决策表, 正域约简, 近似分类精度约简

Abstract:

Attribute reduction is an important part in rough set theory. For the usual decision table, when considering each row in the table as a decision rule, the number of occurrences of the same decision rule is taken as the weight, and thus the weighted decision table is obtained. The corresponding matrix of positive region reduction is proposed and the proof is given, and the algorithm 1 is obtained. Comparing the positive region reduction algorithm between the decision table and the weighted decision table, it is found that the algorithm 1 is superior to the former to some extent after converting the decision table into a weighted decision table. Then the corresponding matrix of approximate classification accuracy reduction is proposed and proved. Two algorithms are tested on the selected UCI datasets. The feasibility and effectiveness of the proposed algorithm are illustrated by experiments.

Key words: rough set, attribute reduction, weighted decision table, positive region reduction, approximate classification accuracy reduction