Results 251 to 260 of about 2,610,867 (326)
Some of the next articles are maybe not open access.
A method for data classification based on discernibility matrix and discernibility function
Wuhan University Journal of Natural Sciences, 2006A method for data classification will influence the efficiency of classification. Attributes reduction based on discernibility matrix and discernibility function in rough sets can use in data classification, so we put forward a method for data classification.
Sun Shi-bao, Qin Ke-yun
openaire +1 more source
Information Sciences, 2019
We eliminate unnecessary computations of attribute discernibility sets in discernibility matrix-based methods (DM-methods) of attribute reduction in concept lattices. We obtain a polynomial time algorithm we call a Skim DM-method.
Jan Konečný, Petr Krajča
semanticscholar +1 more source
We eliminate unnecessary computations of attribute discernibility sets in discernibility matrix-based methods (DM-methods) of attribute reduction in concept lattices. We obtain a polynomial time algorithm we call a Skim DM-method.
Jan Konečný, Petr Krajča
semanticscholar +1 more source
Neurocomputing, 2019
The datasets in real-world applications often vary dynamically over time. Moreover, datasets often expand by introducing a group of data in many cases rather than a single object one by one.
Fumin Ma +3 more
semanticscholar +1 more source
The datasets in real-world applications often vary dynamically over time. Moreover, datasets often expand by introducing a group of data in many cases rather than a single object one by one.
Fumin Ma +3 more
semanticscholar +1 more source
Finding reducts without building the discernibility matrix
5th International Conference on Intelligent Systems Design and Applications (ISDA'05), 2005We present algorithms for fast generation of short reducts which avoid building the discernibility matrix explicitly. We show how information obtained from this matrix can be obtained based only on the distributions of attribute values. Since the size of discernibility matrix is quadratic in the number of data records, not building the matrix ...
M. Korzen, S. Jaroszewicz
openaire +1 more source
Journal of Intelligent & Fuzzy Systems, 2019
Attribute reduction is one of the crucial issues in Formal Concept Analysis. Discernibility matrix plays an important role in attribute reduction, and has been achieved many successful applications in different concept lattice models.
Leijun Li +3 more
semanticscholar +1 more source
Attribute reduction is one of the crucial issues in Formal Concept Analysis. Discernibility matrix plays an important role in attribute reduction, and has been achieved many successful applications in different concept lattice models.
Leijun Li +3 more
semanticscholar +1 more source
Fuzzy Rough Discernibility Matrix Based Feature Subset Selection With MapReduce
IEEE Region 10 Conference, 2019Fuzzy-rough set theory (FRST) is a hybridization of fuzzy sets with rough sets with applications to attribute reduction in hybrid decision systems. The existing reduct computation approaches in fuzzy-rough sets are not scalable to large scale decision ...
N. Pavani +3 more
semanticscholar +1 more source
Minimal Element Selection in the Discernibility Matrix for Attribute Reduction
Chinese journal of electronics, 2019Discernibility matrix is a beautiful theoretical result to get reducts in the rough set, but the existing algorithms based on discernibility matrix share the same problem of heavy computing load and large store space, since there are numerous redundancy ...
Yu Jiang
semanticscholar +1 more source
Information Sciences, 2018
In recent years, discernibility matrix based methods of attribute reduction in concept lattices (DM-methods) enjoyed an increase in attention and were applied in many extensions of formal concept analysis. In our previous paper, we pointed out that there
Jan Konečný, Petr Krajča
semanticscholar +1 more source
In recent years, discernibility matrix based methods of attribute reduction in concept lattices (DM-methods) enjoyed an increase in attention and were applied in many extensions of formal concept analysis. In our previous paper, we pointed out that there
Jan Konečný, Petr Krajča
semanticscholar +1 more source
Discernibility Matrix Based Algorithm for Reduction of Attributes
2006 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Workshops, 2006In rough set theory, it has been proved that finding the minimal reduct of information systems or decision tables is a NP-complete problem. Therefore, it is hard to obtain the set of the most concise rules by existing algorithms for reduction of knowledge.
Ruizhi Wang, Duoqian Miao, Guirong Hu
openaire +1 more source
Attribute reduction based on improved discernibility matrix
2010 2nd IEEE International Conference on Information Management and Engineering, 2010The attribute reduction based on information entropy is different to that based on positive region in inconsistent information system. The problem of discernibility matrix in algebra view is analyzed, and an new discernibility matrix based on information entropy is proposed in this paper.
Zhou Peng, Li Zhishu, Huang Zhiguo
openaire +1 more source