Boosting SVM Classifiers with Logistic Regression
Yuan‐chin Ivan Chang · 2003
The support vector machine classifier is a linear maximum margin classifier. It performs very well in many classification applications. Although, it could be extended to nonlinear cases by exploiting the idea of kernel, it might still su#er from the heterogeneity in the training examples. Since there are very few theories in the literature to guide us on how to choose kernel functions, the selection of kernel is usually based on a try-and-error manner.