A NEW ALGORITHM FOR SOLVING CONVEX HULL PROBLEM AND ITS APPLICATION TO FEATURE SELECTION

摘要：

A new method to solve the convex hull problem in n-dimensional spaces is proposed in this paper. At each step, a new point is added into the convex hull if the point is judged to be out of the current convex hull by a linear programming model. For the linear separable classification problem, if an instance is regarded as a point of the instances space, the overlap does not still occur between the convex hulls of different classes after a feature is deleted, then we can delete that feature. Repeat this process, an algorithm for feature selection is given. Experimental results show the effectiveness of the algorithm.

关键词： Convez Hull Linear Programming Problem Feature Selection

作者: FENG GUO XI-ZHAO WANG YAN LI

作者单位: Key Lab.of Machine Learning and Computational Intelligence, College of Mathematics and Computer Science, Hebei University, Baoding, 071002, Hebei, China

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 369-373

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）