Variable Attribute Selection

نویسندگان

  • Jun Wang
  • Zhongzhi Shi
چکیده

This paper presents a new attribute selection measure-variable attribute selection, based on an extended version of discernibility matrix. The new measure has an advantage for users to acquire knowledge of diierent levels of granu-larity, for example, discriminant rules or characteristic rules. It can also be used for handling continuous-valued attributes. Empirical results demonstrate that applying the variable attribute selection method to continuous-valued attributes datasets can produce simpler rules than using discretization as a preprocess-ing in rough set induction.

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تاریخ انتشار 2007