Oscar Javier Herrera

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Support Vector Machines (SVM) are learning methods useful for solving supervised learning problems such as classification (SVC) and regression (SVR). SVM's are based on the Statistical Learning Theory and the minimization of the Structural Risk [1], an enhancement over neural networks such as Multi-Layer Perceptrons. However, the major drawback is the high(More)
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