An Adaptive Weighted Support Vector Machine

In weighted support vector machines for regression, each training sample has different approximation error requirement and different penalty due to the effect of weighting factors on them. In order to solve the shortcoming of the weighting factors selection problems in weighted support vector machines, AWSVM, an adaptive selecting approach is proposed which can choose appropriate weighting factors adaptively by the new regression algorithm. Experimental results show that the proposed method has a better performance.