期刊
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
卷 26, 期 10, 页码 2583-2588出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNNLS.2014.2379930
关键词
Manifold clustering; plane-based clustering; twin support vector machine (TWSVM); unsupervised learning
类别
资金
- Zhejiang Provincial Natural Science Foundation of China [LQ12A01020]
- National Natural Science Foundation of China [11201426, 10971223, 11371365]
The twin support vector machine (TWSVM) is one of the powerful classification methods. In this brief, a TWSVM-type clustering method, called twin support vector clustering (TWSVC), is proposed. Our TWSVC includes both linear and nonlinear versions. It determines k cluster center planes by solving a series of quadratic programming problems. To make TWSVC more efficient and stable, an initialization algorithm based on the nearest neighbor graph is also suggested. The experimental results on several benchmark data sets have shown a comparable performance of our TWSVC.
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