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GEP-Based Ensemble Classifier with Drift-Detection

  • Joanna JȩdrzejowiczEmail author
  • Piotr Jȩdrzejowicz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11311)

Abstract

The paper proposes a new ensemble classifier using Gene Expression Programming as the induction engine. The approach aims at predicting unknown class labels for datasets with concept drift. For constructing the proposed ensemble we use the two-level scheme where at the lower level base classifiers are induced and at the upper level, the meta-classifier is produced. The classification process is controlled by the well-known early drift detection mechanism. To validate the approach computational experiment has been carried out. Its results confirmed that the proposed classifier performs well.

Keywords

Gene Expression Programming Classifier ensemble Datasets with concept drift 

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Institute of Informatics, Faculty of Mathematics, Physics and InformaticsUniversity of GdańskGdańskPoland
  2. 2.Department of Information SystemsGdynia Maritime UniversityGdyniaPoland

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