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In its basic form, an SVM classifies a pattern vector X into classes based on the support vectors xi and their corresponding classes yi as: M y = sign ∑αiyiK(xi, x) + b i=1 (9) where M is the number of support vectors; K( · , ·) is a symmetric positive-definite kernel ...