Multiclass Generalized Eigenvalue Proximal Support Vector Machines

Support Vector Machines represent state of the art in supervised learning. Recently, the Regularized Generalized Eigenvalue Classifier (ReGEC) extension has been proposed to solve binary classification problems. In the present work we describe MultiReGEC, a novel technique that generalizes ReGEC to multiclass classification problems. This method is based on statistical and geometrical considerations, providing strong fundamentals to the proposed extension. After a detailed description of the MultiReGEC algorithm, we show, through extensive numerical experiments, that the accuracy of the proposed algorithm well compares with other de facto standard techniques.