DELA: A dynamic online ensemble learning algorithm

This source preferred by Hamid Bouchachia and Emili Balaguer-Ballester

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Authors: Bouchachia, A. and Balaguer-Ballester, E.

Journal: 22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2014 - Proceedings

Pages: 491-496

ISBN: 9782874190957

The present paper investigates the problem of prediction in the context of dynamically changing environment, where data arrive over time. A Dynamic online Ensemble Learning Algorithm (DELA) is introduced. The adaptivity concerns three levels: structural adaptivity, combination adaptivity and model adaptivity. In particular, the structure of the ensemble is sought to evolve in order to be able to deal with the problem of data drift. The proposed online ensemble is evaluated on the stagger data set to show its predictive power in presence of data drift.

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