期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2015
卷号：8
期号：8
页码：299-308
DOI：10.14257/ijsip.2015.8.8.31
出版社：SERSC
摘要：Based on fuzzy one-class support vector machine (SVM) and least squares (LS) one- class 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
关键词：Class imbalanced learning; One-class SVM; Least squares; Fuzzy ; information
