Integrating global and local application of random subspace ensemble

Authors:
Sotiris Kotsiantis
Affiliations:
Educational Software Development Laboratory, Department of Mathematics, University of Patras, Rio, Greece
Venue:
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Year:
2014

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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.