X-SOM and L-SOM: A double classification approach for missing value imputation

Authors:
Paul Merlin;Antti Sorjamaa;Bertrand Maillet;Amaury Lendasse
Affiliations:
A.A.Advisors - Variances and University of Paris-1 (CES/CNRS), 106 bv de l'hôpital, F-75647 Paris Cedex 13, France;Helsinki University of Technology - ICS, P.O. Box 5400, 02015 HUT, Finland;A.A.Advisors-QCG - Variances and University of Paris-1 (CES/CNRS and EIF), 106 bv de l'hôpital, F-75647 Paris Cedex 13, France;Helsinki University of Technology - ICS, P.O. Box 5400, 02015 HUT, Finland
Venue:
Neurocomputing
Year:
2010

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Abstract

In this paper, a new method for the determination of missing values in temporal databases is presented. It is based on a robust version of a nonlinear classification algorithm called self-organizing maps and it consists of a combination of two classifications in order to take advantage of spatial as well as temporal dependencies of the dataset. This double classification leads to a significant improvement of the estimation of the missing values. An application of the missing value imputation for hedge fund returns is presented.