Abstract
Lagrangian support vector machine(LSVM) is a kind of method with good generalization ability. But, LSVM is not suitable for classification online because the computation complexity. So in this paper, a fast LSVM is proposed. This method can deduce running time because it fully utilizes the historical training results and reduces memory and calculates time. Finally, an example is accomplished to demonstrate the effect of fast LSVM.
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Yuan, J., Chen, Y., Yang, X. (2011). A Fast Lagrangian Support Vector Machine Model. 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_11
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DOI: https://doi.org/10.1007/978-3-642-23753-9_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23752-2
Online ISBN: 978-3-642-23753-9
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