Pattern recognition based on the minimum norm minimum squared-error classifier
Fengxi Song, Jingyu Yang, Shuhai Liu · 2005
The performance of a novel binary linear classifier named as minimum norm minimum squared-error (MNMSE), which is based on a refined minimum squared-error discriminant criterion is evaluated in this paper. Experimental results show that MNMSE is very effective and efficient for many pattern recognition problems. In most cases it can compete with support vector machines in recognition rate and be more efficient than the methods.