期刊
NEUROCOMPUTING
卷 55, 期 1-2, 页码 39-55出版社
ELSEVIER
DOI: 10.1016/S0925-2312(03)00379-5
关键词
classification; Lagrangian support vector machines; Newton method; myeloma
An implicit Lagrangian [Math. Programming Ser. B 62 (1993) 277] formulation of a support vector machine classifier that led to a highly effective iterative scheme [J. Machine Learn. Res. 1 (2001) 161] is solved here by a finite Newton method. The proposed method, which is extremely fast and terminates in 6 or 7 iterations, can handle classification problems in very high dimensional spaces, e.g. over 28,000, in a few seconds on a 400 MHz Pentium II machine. The method can also handle problems with large datasets and requires no specialized software other than a commonly available solver for a system of linear equations. Finite termination of the proposed method is established in this work. (C) 2003 Elsevier B.V. All rights reserved.
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