1. An SV reduction method for multi-class SVMs comprising: a first step of selecting, from a plurality of initially present support vectors, support vector pairs z i , z j j=1, 2,. .. , N S ); a second step of preparing a single-variable objective function with a single global maximum and determining a maximum value k of the objective function; a third step of applying the maximum value k to the support vector pairs z j to determine a temporary vector Ztemp[i] with small classification errors; and a fourth step of representing the support vector pair z j by the temporary vector Ztemp[i].