Chapter 20. Multiclass Support Vector Machine
Sergio Herrero-Lopez
In this chapter we present the GPU implementation of the support vector machine (SVM). The SVM is a set of supervised learning methods used for classification and regression. Given a set of training examples, the SVM algorithm builds a model that predicts the class of new unseen examples. This algorithm is considered essential in both machine-learning and data-mining curriculums and is frequently used by practitioners. Besides, its utilization spans to a wide variety of applied research fields such as computer vision, neuroscience, text categorization, and finance. This study shows that the GPU implementation of the dual form of the SVM using the sequential minimal optimization ...
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