Title: Robust cross-validation score function for non-linear function estimation
Authors: De Brabanter, Joseph
Pelckmans, Kristiaan
Suykens, Johan
Vandewalle, Joos #
Issue Date: 2002
Publisher: Springer-verlag berlin
Host Document: Artificial neural networks - icann 2002 vol:2415 pages:713-719
Conference: International Conference on Artificial Neural Networks (ICANN 2002) location:Madrid, Spain date:Aug. 2002
Abstract: In this paper a new method for tuning regularisation parameters or other hyperparameters of a learning process (non-linear function estimation) is proposed, called robust cross-validation score function (CVS-foldRobust). CVS-foldRobust is effective for dealing with outliers and non-Gaussian noise distributions on the data. Illustrative simulation results are given to demonstrate that the CVS-foldRobust method outperforms other cross-validation methods.
Description: \emph{Proc. of the International Conference on Artificial Neural Networks (ICANN 2002)}, Madrid, Spain, Aug. 2002
ISSN: 0302-9743
Publication status: published
KU Leuven publication type: IC
Appears in Collections:ESAT - STADIUS, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics
Technologiecluster ESAT Elektrotechnische Engineering
Electrical Engineering (ESAT) TC, Technology Campuses Ghent and Aalst
# (joint) last author

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