Selecting SVM kernels and input variable subsets in credit scoring models

Abstract

We explore simultaneous variable subset selection and kernel selection within SVM classification models. First we apply results from SVM classification models with different kernel functions to a fixed subset of credit client variables provided by a German bank. Free variable subset selection for the bank data is discussed next. A simple stochastic search procedure for variable subset selection is also presented.