Fast Semi-supervised Classification Based on Bisecting Clustering

被引：0
|
作者：
Liu, Xiaolan [1 ,2 ]
Hao, Zhifeng [3 ]
Liu, Jingao [4 ]
Lin, Zhiyong [5 ]
机构：
[1] South China Univ Technol, Sch Comp Sci & Engn, Guangzhou, Guangdong, Peoples R China
[2] South China Univ Technol, Sch Sci, Guangzhou, Guangdong, Peoples R China
[3] Guangdong Univ Technol, Fac Comp, Guangzhou, Peoples R China
[4] Longtop Inc, Guangzhou, Peoples R China
[5] Guangdong Polytech Normal Univ, Dept Comp Sci, Guangzhou, Peoples R China
来源：
2ND IEEE INTERNATIONAL CONFERENCE ON ADVANCED COMPUTER CONTROL (ICACC 2010), VOL. 4 | 2010年
关键词：
semi-supervised learning; bisecting clustering; feature selection;
D O I：
10.1109/GCC.2010.50
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
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.
引用
收藏
页码：207 / 211
页数：5
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