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Conference Papers Year : 2019

Stacking Strong Ensembles of Classifiers

Stamatios-Aggelos N. Alexandropoulos
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Christos Aridas
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Sotiris Kotsiantis
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Michael N. Vrahatis
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A variety of methods have been developed in order to tackle a classification problem in the field of decision support systems. A hybrid prediction scheme which combines several classifiers, rather than selecting a single robust method, is a good alternative solution. In order to address this issue, we have provided an ensemble of classifiers to create a hybrid decision support system. This method based on stacking variant methodology that combines strong ensembles to make predictions. The presented hybrid method has been compared with other known-ensembles. The experiments conducted on several standard benchmark datasets showed that the proposed scheme gives promising results in terms of accuracy in most of the cases.
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Dates and versions

hal-02331304 , version 1 (24-10-2019)





Stamatios-Aggelos N. Alexandropoulos, Christos Aridas, Sotiris Kotsiantis, Michael N. Vrahatis. Stacking Strong Ensembles of Classifiers. 15th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), May 2019, Hersonissos, Greece. pp.545-556, ⟨10.1007/978-3-030-19823-7_46⟩. ⟨hal-02331304⟩
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