Cost-Sensitive Support Vector Machine for Semi-Supervised Learning
Zhiquan Qi, Yingjie Tian, Yong Shi, Xiaodan Yu · Procedia Computer Science · 2013
Cost-sensitive learning has been a hot research topic in machine learning. Many cost-sensitive methods have been successfully applied in many real-world applications such as disease diagnosis, fraud detection and business decision making. In this paper, we proposed a new Cost-Sensitive Laplacian Support Vector Machine(called Cos-LapSVM), which can deal with the cost- sensitive problem in Semi-Supervised Learning. The effectiveness of the proposed method is demonstrated via experiments on UCI datasets