A general formulation for support vector machines
W. Chu, S. Sathiya Keerthi, C.J. Ong · 2002
In this paper, we derive a general formulation of support vector machines for classification and regression respectively. L/sub e/, loss function is proposed as a patch of L/sub 1/ and L/sub 2/ soft margin loss functions for classifier, while soft insensitive loss function is introduced as the generalization of popular loss functions for regression. The introduction of the two loss functions results in a general formulation for support vector machines.