Extreme value model for volatility measure in machine learning ensemble

Abstract

This paper presents a method of model aggregation using multivariate decompositions where the main problem is to properly identify the components that carry noise. We develop a volatility measure which uses generalized extreme value decomposition. It is applied to destructive and constructive latent component classification. A practical experiment was conducted in order to validate the effectiveness of the introduced method.