SOM+EOF for finding missing values

In this paper, a new method for the determination of missing values in temporal databases is presented. This new method is based on two projection methods: a nonlinear one (Self-Organized Maps) and a linear one (Empirical Orthogonal Functions). The global methodology that is presented combines the advantages of both methods to get accurate candidates for missing values. An application of the determination of missing values for fund return database is presented.

• Type: Conference
• Year: 2007
• Where: ESANN
• Authors: Antti Sorjamaa, Paul Merlin, Bertrand Maillet, Amaury Lendasse
• Keywords: Empirical Orthogonal Functions, ESANN 2007, Missing Values, Neural Networks, Temporal Databases