Determination of hyper-parameters for kernel based classification and regression
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Date
2005-11-07T11:39:49Z
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Abstract
We investigate methods to determine appropriate choices of the hyper-parameters for kernel based methods. Support vector classification, kernel logistic regression and support vector regression are considered. Grid search, Nelder-Mead algorithm
and pattern search algorithm are used.
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Keywords
convex risk minimization, kernel logistic regression, statistical machine learning, support vector machine, support vector regression