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2009
Springer

Sparse Linear Combination of SOMs for Data Imputation: Application to Financial Database

10 years 1 months ago
Sparse Linear Combination of SOMs for Data Imputation: Application to Financial Database
Abstract. This paper presents a new methodology for missing value imputation in a database. The methodology combines the outputs of several Self-Organizing Maps in order to obtain an accurate filling for the missing values. The maps are combined using MultiResponse Sparse Regression and the Hannan-Quinn Information Criterion. The new combination methodology removes the need for any lengthy cross-validation procedure, thus speeding up the computation significantly. Furthermore, the accuracy of the filling is improved, as demonstrated in the experiments.
Antti Sorjamaa, Francesco Corona, Yoan Miche, Paul
Added 25 May 2010
Updated 25 May 2010
Type Conference
Year 2009
Where WSOM
Authors Antti Sorjamaa, Francesco Corona, Yoan Miche, Paul Merlin, Bertrand Maillet, Eric Séverin, Amaury Lendasse
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