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Recently proposed weighted linear loss twin support vector machine (WLTSVM) is an efficient algorithm for binary classification. However, the performance of multiple WLTSVM classifier needs improvement since it uses the strategy ‘one-versus-rest’ with high computational complexity. This paper presents a weighted linear loss multiple birth support vector machine based on information granulation (WLMSVM)...
Multiple birth support vector machine is a novel machine learning algorithm for multi-class classification, which is considered as an extension of twin support vector machine. Compared with training speeds of other multi-class classifiers based on twin support vector machine, the training speed of multiple birth support vector machine is faster, especially when the number of class is large. However,...
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