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- W2352473676 abstract "Although Twin Support Vector Machine(TSVM)has faster speed than traditional support vector machine for classification problem, it does not take the importance of the training samples on the learning of the decision hyperplane into account with respect to the classification task. In this paper, Fuzzy Twin Support Vector Machine(FTSVM)is proposed by applying a fuzzy membership to each training sample to reduce the effects of the samples on the hyperplane. Experiments on several UCI benchmark datasets show that the fuzzy twin support vector machine is effective and feasible relative to twin support vector machine, fuzzy support vector machine and support vector machine." @default.
- W2352473676 created "2016-06-24" @default.
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- W2352473676 date "2013-01-01" @default.
- W2352473676 modified "2023-09-25" @default.
- W2352473676 title "Twin Support Vector Machine algorithm with fuzzy weighting" @default.
- W2352473676 hasPublicationYear "2013" @default.
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