Kernel-based multiple criteria linear programming classifier
Zhan Zhang, Dongling Zhang, Yingjie Tian · Procedia Computer Science · 2010
This paper proposed a novel classification model which introduced the kernel function into the original Multiple Criteria Linear Programming (MCLP) model. MCLP model is used as a classification method which can only solve linear separable problems in data mining. However, the proposed kernel-based MCLP model can deal with non-linear cases. Meanwhile, unlike some other complicated models, this model is effective and easy to understand. A couple of experimental tests were conducted to evaluate the performance of the proposed kernel-based MCLP model compared with the existing methods: original MCLP and SVM. The results show that kernel-based MCLP model is a competitive method in dealing with nonlinear separable classification problems.