Performance and Diversity Evaluation in Hybrid and Non-Hybrid Structures of Ensembles

Authors:
Anne M. P. Canuto;Lucas de Melo Oliveira;Joao C. Junior Xavier;Araken de M. Santos;Marjory C. C. Abreu
Affiliations:
Federal University of Rio Grande do Norte, Brazil;Federal University of Rio Grande do Norte, Brazil;Federal University of Rio Grande do Norte, Brazil;Federal University of Rio Grande do Norte, Brazil;Federal University of Rio Grande do Norte, Brazil
Venue:
HIS '05 Proceedings of the Fifth International Conference on Hybrid Intelligent Systems
Year:
2005

Citing 0
Cited 3

Investigating the influence of the choice of the ensemble members in accuracy and diversity of selection-based and fusion-based methods for ensembles

Pattern Recognition Letters
Using weighted dynamic classifier selection methods in ensembles with different levels of diversity

International Journal of Hybrid Intelligent Systems - Hybrid Intelligent systems in Ensembles
Using fuzzy, neural and fuzzy-neural combination methods in ensembles with different levels of diversity

ICANN'07 Proceedings of the 17th international conference on Artificial neural networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a wide evaluation of performance and diversity in Hybrid and non-hybrid structures of ensembles. In applying some diversity measures at the chosen ensemble, it is intended to analyse the effect of varying diversity in ensembles and how the variation of diversity can affect the performance of several combination methods (selection-based and combinationbased methods). Finally, it is also intended to understand the reasons that some combination methods are more affected by variation in diversity.