Support Vector Machine with Different Penalty Coefficients
Xunhua Zhang · Jiangnan daxue xuebao. Ziran kexue ban · 2007
A support vector machine model that distinguishes different samples category's penalty coefficients is proposed.The Lagrange equation is built and its dual form of modal is deduced by KKT condition.This model could let users mark the importance of different samples,and give relevant penalty coefficients according to different importance.This situation can decrease the possibility of being misclassified in important samples.The result of experimentation shows that this model can classify customizing task well.