Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/8295
Title: Fast and convergence-guaranteed algorithm for linear separation
Authors: Liu, Z
Zhang, D 
Li, Y
Keywords: Classification
Complexity
Convergence
Efficiency
Linear separation problem
Issue Date: 2010
Source: Science in China, series F : Information sciences, 2010, v. 53, no. 4, p. 729-737 How to cite?
Journal: Science in China, Series F: Information Sciences 
Abstract: Efficient linear separation algorithms are important for pattern classification applications. In this paper, an algorithm is developed to solve linear separation problems in n-dimensional space. Its convergence feature is proved. The proposed algorithm is proved to converge to a correct solution whenever the two sets are separable. The complexity of the proposed algorithm is analyzed, and experiments on both randomly generated examples and real application problems were carried out. While analysis shows that its time complexity is lower than SVM that needs computations for quadratic programming optimization, experiment results show that the developed algorithm is more efficient than the least-mean-square (LMS), and the Perceptron.
URI: http://hdl.handle.net/10397/8295
ISSN: 1009-2757
DOI: 10.1007/s11432-010-0037-5
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