Fuzzy rough set based attribute reduction
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In this paper, we use the variable precision method on approximate operators of the FRS model to expand measures to effectively evaluate attributes on noisy datasets. The main contributions of this paper include: Proposing new approximation operations to extend VPFRS to VPOFRS; proposing some measures based on VPOFRS to evaluate the consistency degree of the decision table and the dependence degree of the attribute.
15p dianmotminh02 03-05-2024 2 1 Download
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The objective of the thesis: Proposes filter-wrapper algorithms for fuzzy rough set based attribute reduction in decision tables to reduce the cardinality of reduct and increase significantly the classification accuracy.
28p extraenglish 24-05-2021 12 3 Download
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The first is the hybrid filterwrapper algorithm proposal for finding the reduction set of the decision table using advanced fuzzy distance measurements and other measurements basing on fuzzy rough set to minimize2 the number of attributes of reduction set. Reduce and improve the accuracy of the classification model.
26p capheviahe27 23-02-2021 25 3 Download
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In this paper, we propose a fuzzy distance based attribute reduction method on the decision table with numerical attribute value domain. Experiments on data sets show that the proposed method is more efficient than the ones based on Shannon’s entropy on the executed time and the classification accuracy of reduct.
9p vitomato2711 11-03-2020 23 0 Download
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In addition to traditional exploiting information methods, researchers have developed attribute reduction methods to reduce the size of the data space and eliminate irrelevant attributes. Our attribute reduction is based on the dependence between attributes in traditional rough set theory and in fuzzy rough set. The author built the tool which is inclusion degree and tolerance-based contingency table to solve the problem of finding the approximation set on set-valued information systems.
7p mangamanga 29-02-2020 25 0 Download