关键词: 粗糙集, 信息熵, 条件信息熵, 模糊熵, 属性约简

Abstract: Fuzzy entropy and fuzziness are both important measurement methods of rough set uncertain measure. According to the formula of fuzzy entropy and new fuzziness of rough set uncertain measure, this paper proposes the concepts of revisionary conditional information entropy and relative fuzzy entropy in the decision information system, and proves the monotonicity of entropy by using two methods respectively in the process of attribute reduction. Then, this paper uses the algorithm of adding attributes for attribute reduction, and tests the recognition rate in RIDAS (rough set based intelligent data analysis system) platform. Finally, this paper compares and analyzes the experimental results between the two proposed information entropy and conditional information entropy, and provides a reference for the attribute reduction based on information entropy.

Key words: rough set, information entropy, condition information entropy, fuzzy entropy, attribute reduction