Abstract：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.
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