Classifier ensembles for changing environments

Abstract

We consider strategies for building classifier ensembles for non-stationary environments where the classification task changes during the operation of the ensemble. Individual classifier models capable of online learning are reviewed. The concept of "forgetting" is discussed. Online ensembles and strategies suitable for changing environments are summarized. © Springer-Verlag 2004.