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- W2376754507 abstract "Feature selection is an essential step to perform cancer classification with DNA microarrays.Rough set theory has already been successfully applied to gene selection.To avoid losing information by discretization of continuous gene expression data in rough set theory,the theory of fuzzy rough sets is applied to gene selection.A fuzzy rough attribute reduction algorithm based on mutual information was proposed and applied to gene selection.The cost of computation of the algorithm is too high to be carried out if the number of the selected genes is large.This paper raised an approximate replacement of computation of the mutual information,from both maximum relevance and maximum significance.The novel method improves the efficiency and decreases the complexity.Extensive experiments were conducted on three public gene expression datasets.The experimental results confirm the efficiency and effectiveness of the algorithm." @default.
- W2376754507 created "2016-06-24" @default.
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- W2376754507 date "2013-01-01" @default.
- W2376754507 modified "2023-09-23" @default.
- W2376754507 title "Fast Approach to Mutual Information Based Gene Selection with Fuzzy Rough Sets" @default.
- W2376754507 hasPublicationYear "2013" @default.
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