Ensemble learning is attracting much attention from pattern recognition and machine learning domains for good generalization. Both theoretical and experimental researches show tha...
Scientists increasingly use ensemble data sets to explore relationships present in dynamic systems. Ensemble data sets combine spatio-temporal simulation results generated using mu...
Kristin Potter, Andrew Wilson, Peer-Timo Bremer, D...
In this paper we propose a meta-evolutionary approach to improve on the performance of individual classifiers. In the proposed system, individual classifiers evolve, competing to ...
Background: The Ensembl project produces updates to its comparative genomics resources with each of its several releases per year. During each release cycle approximately two week...
Jessica Severin, Kathryn Beal, Albert J. Vilella, ...
Previously we proposed a scheme to generate fuzzy rule-based multiclassification systems by means of bagging, mutual information-based feature selection, and a multicriteria geneti...
Krzysztof Trawinski, Arnaud Quirin, Oscar Cord&oac...