Support Vector Machine and Generalization
Takio Kurita · Journal of Advanced Computational Intelligence and Intelligent Informatics · 2004
The support vector machine (SVM) has been extended to build up nonlinear classifiers using the kernel trick. As a learning model, it has the best recognition performance among the many methods currently known because it is devised to obtain high performance for unlearned data. This paper reviews how to enhance generalization in learning classifiers centering on the SVM.