PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Using the Delta test for variable selection
Emil Eirola, Elia Liitiäinen, Amaury Lendasse, Francesco Corona and Michel Verleysen
In: ESANN 2008, European Symposium on Artificial Neural Networks, April 23-25 2008, Bruges, Belgium.

Abstract

We propose that using an established noise variance estimator known as the Delta test as the target to minimise can provide an effective input selection methodology. Theoretical justifications and experimental results are presented.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:4814
Deposited By:Amaury Lendasse
Deposited On:24 March 2009