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Conference papers
Path for Kernel Adaptive One-Class Support Vector Machine
Abstract : This paper proposes a Kernel Adaptive One Class SVM (KAOC-SVM) method based on the model introduced by A. Scholkopf and al. The aim is to find the solution path - the path of Lagrange multiplier a - as the kernel parameter changes from one value to another. It is similar to the regularization path approach proposed by Hastie and al., which finds the path when the regularization parameter ? changes from 0 to 1. In present case, the main difference is that the Lagrange multiplier paths are not piecewise linear anymore. Experimental results show that the proposed method is able to compute one-class SVMs with the same accuracy as traditional method but exploring all solutions combining 2 kernels. Simulation results are presented and CPU requirement is analyzed.
https://hal-utt.archives-ouvertes.fr/hal-02358669
Contributor : Jean-Baptiste Vu Van Connect in order to contact the contributor
Submitted on : Tuesday, November 12, 2019 - 9:35:28 AM
Last modification on : Friday, August 27, 2021 - 3:14:06 PM
Contributor : Jean-Baptiste Vu Van Connect in order to contact the contributor
Submitted on : Tuesday, November 12, 2019 - 9:35:28 AM
Last modification on : Friday, August 27, 2021 - 3:14:06 PM