The Comparative Study of SVM Tools for Data Classification (original) (raw)

Support vector machine (SVM) is one of the recent methods for statistical learning, it addresses classification and regression problems . It can be considered as an alternative to neural networks. The advantage of SVM, with respect to neural network, is that it provides a theoretical framework for taking into account not only the experimental data to design an optimal classifier, but also a structural behavior for allowing better generalization capability. This paper introduces SVM theory, applications and its algorithmic implementations. Although there are proven algorithms for constructing SVM programs, it is usually faster and also more reliable to make use or adapt a public domain SVM implementation packages. In this paper, we explain three of the popularly used C/C++ based SVM packages and demonstrate their usage. We report some results of their usage in classification on a number of different datasets, taking into consideration the tuning of SVM kernel hyperparameters for perf...