Título: Multi-Kernel Based PLS regression
Autores: Milidiú, Ruy L.; Rentería, Raúl P.
Resumo: MKPLS, a non-linear version of the Partial Least-Squares regression is presented. The non-linearity is introduced in the classical algorithm through the use of multiple kernel functions, thus providing an straightforward non-linear adaptation. MKPLS provides a multi-kernel based version for the PLS algorithm with a competitive modeling error. Experimental results show that the use of different kernels for the regression model enhances the predictive power when compared to a PLS regression based on only one function kernel.
Código DOI: 10.21528/CBRN2003-080
Artigo em PDF: 6CBRN_080.PDF
Arquivo BibTex: 6CBRN_080.bib