SVM Modeling Methodology

The classification performance of SVM is greatly decided by the model s parameters. Different problems have specific optimal parameters that have to be determined. Consequently, the selection of the model s parameters is an important requirement in SVM, because the kernel parameters and the cost parameter decide the performance of SVM in classification. 

Similar to the SVM classification, the selection of model parameters is an important requirement for the regression too. In this case of support vector regression (SVR), we have to tune not only the cost parameter C 0 and the parameters specific to each kernel, as in the classification, but also the penalty parameter e or p, depending on the type 

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