区间序信息系统的无监督特征选择

Unsupervised Feature Selection for Interval Ordered Information Systems

目前已有很多针对单值信息系统的无监督特征选择方法,但针对区间值信息系统的无监督特征选择方法却很少.针对区间序信息系统,文中提出模糊优势关系,并基于此关系扩展模糊排序信息熵和模糊排序互信息,用于评价特征的重要性.再结合一种综合考虑信息量和冗余度的无监督最大信息最小冗余(Um IMR)准则,构造无监督特征选择方法.最后通过实验证明文中方法的有效性.

There are a number of unsupervised feature selection methods proposed for single-valued information systems, but little research focuses on unsupervised feature selection of interval-valued information systems. In this paper, a fuzzy dominance relation is proposed for interval ordered information systems. Then, fuzzy rank information entropy and fuzzy rank mutual information are extended to evaluate the importance of features. Consequently, an unsupervised feature selection method is designed based on an unsupervised maximum information and minimum redundancy （ UmImR ） criterion. In the UmImR criterion, the amount of information and redundancy are taken into account. Experimental results demonstrate the effectiveness of the proposed method.