Integrating global and local application of random subspace ensemble

Article type: Research Article

Authors: Kotsiantis, Sotiris

Affiliations: Educational Software Development Laboratory, Department of Mathematics, University of Patras, Rio, Greece

Note: [] Corresponding author. Sotiris Kotsiantis, Educational Software Development Laboratory, Department of Mathematics, University of Patras, P.A. Box: 1399, Rio 26 504, Greece. Tel.: +30 2610 996769; Fax: +30 2610 997313; E-mail: sotos@math.upatras.gr

Abstract: Many data analysis problems involve an investigation of relationships between attributes in heterogeneous databases, where different prediction models can be more appropriate for different regions. We propose a technique of integrating global and local random subspace ensemble. We performed a comparison with other well known combining methods on standard benchmark datasets and the proposed technique gave better accuracy.

Keywords: Ensemble of classifiers, random subspace, combining classifiers

DOI: 10.3233/IFS-120763

Journal: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 2, pp. 731-739, 2014