Practical selection of SVM parameters and noise estimation for SVM regression
نویسندگان
چکیده
منابع مشابه
Practical selection of SVM parameters and noise estimation for SVM regression
We investigate practical selection of hyper-parameters for support vector machines (SVM) regression (that is, epsilon-insensitive zone and regularization parameter C). The proposed methodology advocates analytic parameter selection directly from the training data, rather than re-sampling approaches commonly used in SVM applications. In particular, we describe a new analytical prescription for s...
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ژورنال
عنوان ژورنال: Neural Networks
سال: 2004
ISSN: 0893-6080
DOI: 10.1016/s0893-6080(03)00169-2