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A kernel extension to handle missing data

Autor
Nebot, G.; Belanche, Ll.
Tipus d'activitat
Presentació treball a congrés
Nom de l'edició
Twenty-ninth SGAI International Conference on Artificial Intelligence
Any de l'edició
2009
Data de presentació
2009
Llibre d'actes
Research and Development in Intelligent Systems XXVI
Pàgina inicial
165
Pàgina final
178
Editor
Springer-Verlag
DOI
https://doi.org/10.1007/978-1-84882-983-1_12 Obrir en finestra nova
Repositori
http://hdl.handle.net/2117/16222 Obrir en finestra nova
Resum
An extension for univariate kernels that deals with missing values is proposed. These extended kernels are shown to be valid Mercer kernels and can adapt to many types of variables, such as categorical or continuous. The proposed kernels are tested against standard RBF kernels in a variety of benchmark problems showing different amounts of missing values and variable types. Our experimental results are very satisfactory, because they usually yield slight to much better improvements over those ac...
Citació
Nebot, G.; Belanche, Ll. A kernel extension to handle missing data. A: SGAI International Conference on Artificial Intelligence. "Research and Development in Intelligent Systems XXVI". Cambridge: Springer-Verlag, 2009, p. 165-178.
Paraules clau
Univariate Kernels, Missing Values
Grup de recerca
IDEAI-UPC Intelligent Data Science and Artificial Intelligence
SOCO - Soft Computing

Participants

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