Results 251 to 260 of about 10,917,671 (339)
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Semi-supervised attribute reduction via attribute indiscernibility
International Journal of Machine Learning and Cybernetics, 2022Jianhua Dai +3 more
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Fusing attribute reduction accelerators
Information Sciences, 2021Yan Chen +4 more
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Applied Soft Computing, 2021
Fuzzy rough set theory is a powerful tool to deal with uncertainty information, which has been successfully applied to the fields of attribute reduction, rule extraction, classification tree induction, etc.
Zhong Yuan +5 more
semanticscholar +1 more source
Fuzzy rough set theory is a powerful tool to deal with uncertainty information, which has been successfully applied to the fields of attribute reduction, rule extraction, classification tree induction, etc.
Zhong Yuan +5 more
semanticscholar +1 more source
Fast and Robust Attribute Reduction Based on the Separability in Fuzzy Decision Systems
IEEE Transactions on Cybernetics, 2021Attribute reduction is one of the most important preprocessing steps in machine learning and data mining. As a key step of attribute reduction, attribute evaluation directly affects classification performance, search time, and stopping criterion.
Meng Hu +3 more
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GBNRS: A Novel Rough Set Algorithm for Fast Adaptive Attribute Reduction in Classification
IEEE Transactions on Knowledge and Data Engineering, 2020Feature reduction is an important aspect of Big Data analytics on today’s ever-larger datasets. Rough sets are a classical method widely applied in attribute reduction.
Shuyin Xia +5 more
semanticscholar +1 more source
Journal of Computer Science and Technology, 2004
Based on the principle of discernibility matrix, a kind of reduction algorithm with attribute order has been developed and its solution has been proved to be complete for reduct and unique for a given attribute order. Being called the reduct problem, this algorithm can be regarded as a mapping R = Reduct(S) from the attribute order space Θ to the ...
Suqing Han, Jue Wang 0004
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Based on the principle of discernibility matrix, a kind of reduction algorithm with attribute order has been developed and its solution has been proved to be complete for reduct and unique for a given attribute order. Being called the reduct problem, this algorithm can be regarded as a mapping R = Reduct(S) from the attribute order space Θ to the ...
Suqing Han, Jue Wang 0004
openaire +2 more sources
Greedy Algorithm for Attribute Reduction
Fundamenta Informaticae, 2008In the paper the accuracy of greedy algorithmfor construction of partial tests (superreducts) and partial decision rules is considered. Results of experiments with greedy algorithm are described.
Beata Zielosko, Marcin Piliszczuk
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Attribute reduction and attribute characteristics of formal contexts
2013 International Conference on Machine Learning and Cybernetics, 2013In this paper, by the definitions of meet-irreducible element we discuss attribute characteristics and attribute reduction of formal contexts. We first propose an effective method to determine whether an element is meet-irreducible. Then present an approach to judge the indispensable attributes and the dispensable attribute, by which the attribute ...
Eric C. C. Tsang, Ming-Wen Shao
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Attributes correlation coefficients and their application to attributes reduction
Journal of Intelligent & Fuzzy Systems, 2019In this paper, information entropy about logarithmic form is used to measure uncertainty of knowledge, and the correlation connection between information entropy, conditional information entropy, joint information entropy and mutual information entropy are analyzed. Correlation coefficient ρ
Xia Wu 0003 +2 more
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A new algorithm for attribute reduction
2011 Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), 2011According to attribute reduction based on Rough Set theory, this paper put forward a new algorithm for attribute reduction based on degree of dependency. This algorithm, with less complication and high efficiency, can calculate all attribute reductions and cores. The experimental results show that this algorithm is high-level feasibility and effective.
Xiaoyu Chen, Yanli Zhao
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