How to Fine-tune Support Vector Machines for Classification

This book covers in the first part the theoretical aspects of support vector machines and their functionality, and then based on the discussed concepts it explains how to find-tune a support vector machine to yield highly accurate prediction results which are adaptable to any classification tasks. The introductory part is extremely beneficial to someone new to learning support vector machines, while the more advanced notions are useful for everyone who wants to understand the mathematics behind support vector machines and how to find-tune them in order to generate the best predictive performance of a certain classification model.