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Using an iterative linear solver in an interior-point method for generating support vector machines.
- Source :
- Computational Optimization & Applications; Nov2010, Vol. 47 Issue 3, p431-453, 23p
- Publication Year :
- 2010
-
Abstract
- This paper concerns the generation of support vector machine classifiers for solving the pattern recognition problem in machine learning. A method is proposed based on interior-point methods for convex quadratic programming. This interior-point method uses a linear preconditioned conjugate gradient method with a novel preconditioner to compute each iteration from the previous. An implementation is developed by adapting the object-oriented package OOQP to the problem structure. Numerical results are provided, and computational experience is discussed. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09266003
- Volume :
- 47
- Issue :
- 3
- Database :
- Complementary Index
- Journal :
- Computational Optimization & Applications
- Publication Type :
- Academic Journal
- Accession number :
- 55642680
- Full Text :
- https://doi.org/10.1007/s10589-008-9228-z