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Extreme Value Model for Volatility Measure in Machine Learning Ensemble

  • Ryszard Szupiluk
  • Paweł RubachEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10841)

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.

Keywords

Prediction Blind separation Ensemble models Noise detection Theta noise measure 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Warsaw School of EconomicsWarsawPoland

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