Regularized Multiple Criteria Linear Programming via Linear Programming
Year: 2012
Type: conference-paper
Abstract: Regularized multiple-criteria linear programming (RMCLP) model is a new powerful method for classification and has been used in various real-life data mining problems. In this paper, instead of solving quadratic programming (QP) in algorithm RMCLP, we proposed a novel RMCLP via linear programming (LP) for pattern classification(called LP-RMCLP). Numerical experiments on benchmark datasets show that the proposed method is comparable to traditional RMCLP in accuracy, however considerably faster than it.
Source: Procedia Computer Science
Authors: Zhiquan Qi, Yingjie Tian, Yong Shi
Institution: Chinese Academy of Sciences
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W2059620483