Least Squares Fuzzy One-class Support Vector Machine for Imbalanced Data
نویسندگان
چکیده
Based on fuzzy one-class support vector machine (SVM) and least squares (LS) oneclass SVM, we propose an LS fuzzy one-class SVM to deal with the class imbalanced problem. The LS fuzzy one-class SVM applies a fuzzy membership to each sample and attempts to solve the modified primal problem. Hence, we just need to solve a system of linear equations as opposed solving the quadratic programming problem (QPP) in fuzzy one-class SVM, which leads to an extremely simple and fast algorithm. Numerical experiments on several benchmark data sets demonstrate the feasibility and effectiveness of the proposed algorithm.
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