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- W2383557176 abstract "SVM normal feature selection algorithm only considers the contribution made to feature selection by the normal,ignoring the contribution made by the distribution of features totally.In this paper,based on the analysis of SVM normal algorithm,and the difference between the probability that attributes occurs in positive and negative samples,a weighed SVM normal algorithm,which considers both the distribution and the normal was presented.The experiment results show that,compared with SVM normal algorithm and information gain algorithm,when a small feature space is applied,the weighed SVM normal algorithm has better feature selection performance than SVM normal algorithm and information gain algorithm." @default.
- W2383557176 created "2016-06-24" @default.
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- W2383557176 date "2006-01-01" @default.
- W2383557176 modified "2023-09-25" @default.
- W2383557176 title "An improved feature selection algorithm for linear SVM classifiers" @default.
- W2383557176 hasPublicationYear "2006" @default.
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