Kernel Methods and Machine Learning

Kernel Methods and Machine Learning

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Covering the fundamentals of kernel-based learning theory, this is an essential resource for graduate students and professionals in computer science.The following parameters were adopted: Iƒ = 2.5 for RBF and TRBF3 kernels, C = 10 for SVM, and I = 0.1 for KRR and ... The prediction accuracies and running times reported here were obtained by executing MATLAB classification codes on anbsp;...

Title:Kernel Methods and Machine Learning
Author:S. Y. Kung
Publisher:Cambridge University Press - 2014-04-17


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