Abstract
Parameters selection is important in the research area of support vector machine. Based on flexible polyhedron search algorithm, this paper proposes automatic parameters selection for Lagrangian support vector machine. An equipment fault classification illustrates that lagrangian support vector machine based on particle swarm optimization has fine classification ability.
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Chen, Y., Yang, X. (2011). The Research of Lagrangian Support Vector Machine Based on Flexible Polyhedron Search Algorithm. In: Jin, D., Lin, S. (eds) Advances in Computer Science, Intelligent System and Environment. Advances in Intelligent and Soft Computing, vol 106. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23753-9_9
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DOI: https://doi.org/10.1007/978-3-642-23753-9_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23752-2
Online ISBN: 978-3-642-23753-9
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