X-SOM and L-SOM: A double classification approach for missing value imputation
Paul Merlin, Antti Sorjamaa, Bertrand Maillet and Amaury Lendasse
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.