A new wavelet scaling kernel-support vector (WSK-SV) algorithm based on scaling function of wavelet and support vector (SV) algorithm was presented in this paper

which firstly took Daubechies and Shannon wavelet-scaling kernel function for a kind of admissible support vector kernel

respectively.WSK-SV algorithm possesses such properties as compactly supported wavelet bases

orthogonal bases

multiresolution analysis (MRA)

and satisfies Mercer condition for scaling kernel function.This algorithm not only has the advantages of general support vector machine (SVM)

but also has a good convergence and excellent capacity of generalization

which can improve the learning efficiency and predicting ability.Numerical experiments demonstrate that this proposed WSK-SV algorithm is feasible and effective.