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About: 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 [...] Changes:Initial Announcement on mloss.org.
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About: Very simple code for training SVMs in the primal. Works particularly well on sparse linear problems. In the non-linear case the entire kernel matrix needs to be computed, so for large problems it is [...] Changes:Initial Announcement on mloss.org.
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