Optimal predictive kernel regression via feature space principle components

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Title: Optimal predictive kernel regression via feature space principle components
Author: Fokoue, Ernest
Abstract: We propose a simple use of principal component analysis in feature space that allows the derivation of optimal predictive kernel regression. The proposed approach is shown to perform well on both artificial and real data. Despite its incredible simplicity, the proposed method is found to compete very well with sophisticated statistical approaches like the Relevance Vector Machine and the Support Vector Machine.
Record URI: http://hdl.handle.net/1850/13134
Date: 2011-01-01

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