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An Efficient Algorithm for Pawlak Reduction Based on Simplified Discernibility Matrix
Advances in Soft Computing, 2009Bing-Ru Yang
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A New Discernibility Matrix and Function
2006In the paper, we define a new discernibility matrix and function between two decision tables. They are extension of Hu's improved discernibility matrix and function such that the reducts and the cores of decision tables could be calculated by parts of them. The method of new discernibility matrix and function may be applied to the cases of large amount
Dayong Deng, Houkuan Huang
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Exhaustive Search with Belief Discernibility Matrix and Function
2013This paper proposes a new feature selection method based on rough sets to take away the unnecessary attributes for the classification process from partially uncertain decision system. The uncertainty exists only in the decision attributes (classes) and is represented by the belief function theory.
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A Feature Selection Algorithm Based on Discernibility Matrix
2007A heuristic algorithm of reduct computation for feature selection is proposed in the paper, which is a discernibility matrix based method and aims at reducing the number of irrelevant and redundant features in data mining. The method used both significance information of attributes and information of discernibility matrix to define the necessity of ...
Fuyan Liu, Shaoyi Lu
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Multilabel Feature Selection Based on Relative Discernibility Pair Matrix
IEEE Transactions on Fuzzy Systems, 2022In multi-label learning, the curse of dimensionality is one of major challenges. Existing single-label feature selection methods cannot be directly applied to multi-label data, and multi-label feature selections have thus been widely studied. As an effective granular computing tool, rough set theory has been applied to multi-label feature selections ...
Erliang Yao +3 more
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The method of attribute reduction based on discernibility matrix
2010 International Conference on Computer Application and System Modeling (ICCASM 2010), 2010With respect to decision table, especially the inconsistent ones. On the basis of equivalent partitions, This paper quantifies the elements in the same class deduced by condition attribute belonging to different decision attribute classes, generates the discernibility matrix and measures the indexes of attribute significance reasonable, and then uses ...
null Lv Yue-jin +2 more
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Belief Discernibility Matrix and Function for Incremental or Large Data
2013This paper proposes an incremental attribute selection method based on rough sets from partially uncertain and incremental or large decision system. The uncertainty exists only in the decision attributes classes and is represented by the belief function theory.
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Discernibility Matrix Enriching and Boolean-And Algorithm for Attributes Reduction
2014discernibility matrix and binary discernibility matrix method is easy to understand and design, which has aroused great concern by many scholar. Research shows that the two methods produce a large number of repeated and useless elements (if A is the subset of B, B is the useless element of A) on the fly. These repeated and useless elements occupy a lot
ZhangYan Xu +3 more
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Attribute Reduction in Concept Lattice Based on Discernibility Matrix
2005As an effective tool for knowledge discovery, concept lattice has been successfully applied to various fields. One of the key problems of knowledge discovery is knowledge reduction. This paper studies attribute reduction in concept lattice. Using the idea similar to Skowron and Rauszer's discernibility matrix, the discernibility matrix and function of ...
Wen-Xiu Zhang, Ling Wei, Jian-Jun Qi
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Heuristic for Attribute Selection Using Belief Discernibility Matrix
2012This paper proposes a new heuristic attribute selection method based on rough sets to remove the superfluous attributes from partially uncertain data. We handle uncertainty only in decision attributes (classes) under the belief function framework.
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