Kernel Based Simple Regularized Multiple Criteria Linear Programs for Binary Classification
Xi Zhao, Lingfeng Niu, Yong Shi · 2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT) · 2013
Binary classification is the simplest case for classification problem. In this paper, we proposed a new kernel based regularized multiple criteria linear programs for binary classification. Modeling capability of original regularized model were improved by introducing nonlinear kernel, which made the model could identify nonlinear patterns in data. Experiments result showed our model is comparable with classical binary classifiers and suitable for real world application.