Journal
APPLIED INTELLIGENCE
Volume 49, Issue 8, Pages 2807-2822Publisher
SPRINGER
DOI: 10.1007/s10489-019-01423-6
Keywords
Ensemble classification; Imbalanced classification; Feature space partitioning; Hybrid metaheuristics
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Funding
- Spanish Ministry of Economy and Competitiveness [TEC2013-45585-C2-2-R, TIN2014-56042-JIN]
- TIMON project
- European Union [636220, 769142]
- LOGISTAR project
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One of the most challenging issues when facing a classification problem is to deal with imbalanced datasets. Recently, ensemble classification techniques have proven to be very successful in addressing this problem. We present an ensemble classification approach based on feature space partitioning for imbalanced classification. A hybrid metaheuristic called GACE is used to optimize the different parameters related to the feature space partitioning. To assess the performance of the proposal, an extensive experimentation over imbalanced and real-world datasets compares different configurations and base classifiers. Its performance is competitive with that of reference techniques in the literature.
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