Description:

Code for automatically selecting the kernel parameters of an SVM. It is based on a gradient descent minimization of either the radius/margin bound, the leave-one-out error, a validation error or the marginalized likelihood.

Included is also a special code for learning a linear combination of kernels.

Changes to previous version:

Initial Announcement on mloss.org.

BibTeX Entry: Download

Corresponding Paper BibTeX Entry: Download

Supported Operating Systems: Linux, Windows, Macos

Data Formats: None

Tags: Support Vector Machine, Kernel Methods

Archive: download here

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