Journal
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
Volume 26, Issue 10, Pages 2583-2588Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNNLS.2014.2379930
Keywords
Manifold clustering; plane-based clustering; twin support vector machine (TWSVM); unsupervised learning
Categories
Funding
- Zhejiang Provincial Natural Science Foundation of China [LQ12A01020]
- National Natural Science Foundation of China [11201426, 10971223, 11371365]
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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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