Experimental evaluation of two new GEP-based ensemble classifiers

Experimental evaluation of two new GEP-based ensemble classifiers
Joanna Je¸drzejowicza, [url=http://www.sciencedirect.com/science/article/pii/S0957417411003563#cor1][/url], , Piotr Je¸drzejowiczb,

Institute of Informatics, Gdańsk University, Wita Stwosza 57, 80-952 Gdańsk, Poland

b	Department of Information Systems, Gdynia Maritime University, Morska 83, 81-225 Gdynia, Poland

Available online 1 March 2011.

Abstract

The paper proposes applying Gene Expression Programming (GEP) to induce ensemble classifiers. Two new algorithms inducing such classifiers are proposed. The proposed ensemble classifiers use two different measures to select genes produced by the Gene Expression Programming procedure. Selection of genes from the set of the non-dominated ones in the process of meta-learning is supported by a genetic algorithm. Integration of genes (i.e. learners) is based on the majority voting. The proposed algorithms were validated experimentally using several datasets and the results were compared with those of other well established classification methods.

http://www.sciencedirect.com/science/article/pii/S0957417411003563