Further Research

As compared with neural network based method, L-J approach with combined kernel functions was observed to have a better performance. In addition, L-J method has the advantage on the basis of a single training run and is easier to compute for feature selection as compared with other SVM based methods. However, the computation speed is relatively slow when the kernel functions are complicated.

Hence, this subject is worth investigating in the future.

In addition to computation speed problems, the rules generalization is another important issue. Obviously, SVM based methods do not provide the ability of rule generalization although they have the strong foundation in statistical learning theory.

Most of the engineering or medical problems with regard to the rule generalization are still more exigent than feature selection for operators or non-experts. Hence, how to provide a function of rule generalization extend the SVM based method deemed an important issue in the interdisciplinary applications.

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