Research on Tangent Circular Arc Smooth Support Vector Machine (TCA-SSVM)Algorithm

摘要：

Data classification problem is a flourishing research field.Classification is the process of finding the common properties among different patterns and classifying them into classes.SVM (Support Vector Machine)is one of classifier for solving binary classification problem.In traditional SVM solution algorithms,objective function is a strictly convex unconstrained optimization problem,but is un-differentiable due to plus function x+,which precludes the most used optimization algorithms.A new smoothing technology which replaces the plus function by an accurate tangent circular arc polynomial for solving SVM classification algorithm is proposed in this paper.We also prescribe a DFP Quasi-Newton algorithm to solve the proposed classifier.Numerical results and comparisons are given to demonstrate the effectiveness.

关键词： Classification SVM smooth technology tangent circular arc polynomial DFP Quasi-Newton

作者: YAN-FENG FAN DE-XIAN ZHANG

作者单位: College of Information Science and Engineering Henan University of Technology Zhengzhou 450001,China

会议类型: 国际会议

会议名称: 2008 IEEE International Conference on Onformation and Automation(IEEE 信息与自动化国际会议)

会议地点: 张家界

会议语种:英文

页码: 1322-1327

在线出版日期: 2008-06-20（万方平台首次上网日期，不代表论文的发表时间）