A Fast and Efficient Algorithm for Border Extraction
Zhiyong Lin, Zhifeng Hao, Xiaowei Yang · 2007
For some classification methods, such as support vector machine, the border examples are useful in the classifier design. In this paper, a fast algorithm for border extraction is proposed. The algorithm is firstly derived from the linearly separated case intuitively. Then, through kernel trick, the algorithm is extended to the nonlinearly separated case. Several simulations are carried out to evaluate the algorithm's performance, and the results show its effectiveness. Also, the effects of the parameters on the algorithm are discussed, and some suggestions on how to select the parameters are presented.