Fast Semi-supervised Classification Based on Bisecting Clustering

摘要：

In this paper, we propose a fast semi-supervised learning algorithm based on the bisecting clustering. The key idea of the proposed algorithm is dividing data into two sub clusters each time by using bisecting clustering and parts of the features of the data. The time complexity of the algorithm is nearly linear to the data size. Numerical comparisons with several existing methods for the UCI datasets and benchmark datasets verify the effectiveness of our method.

关键词： semi-supervised learning bisecting clustering feature selection

作者: Xiaolan Liu Zhifeng Hao Jingao Liu Zhiyong Lin

作者单位: School of Computer Science and Engineering School of Science South China University of Technology Gu Faculty of Computer Guangdong University of Technology Guangzhou China Longtop Inc Guangzhou China Department of Computer Science Guangdong Polytechnic Normal University Guangzhou China

会议类型: 国际会议

会议名称: The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)

会议地点: 沈阳

会议语种:英文

页码: 207-211

在线出版日期: 2010-03-27（万方平台首次上网日期，不代表论文的发表时间）