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An Empirical Analysis of Meta-learning for the Automatic Choice of Architecture and Components in Ensemble Systems.

, , and . BRACIS, page 1-6. IEEE Computer Society, (2014)

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Integrating complementary techniques for promoting diversity in classifier ensembles: A systematic study., , and . Neurocomputing, (2014)Directly Optimizing Topology-Preserving Maps with Evolutionary Algorithms., , and . ICONIP (1), volume 5506 of Lecture Notes in Computer Science, page 1180-1187. Springer, (2008)Self-organized and Social Models of Criminal Activity in Urban Environments., , , and . ANTS Workshop, volume 4150 of Lecture Notes in Computer Science, page 518-519. Springer, (2006)Tackling EEG signal classification with least squares support vector machines: A sensitivity analysis study., , and . Comput. Biol. Medicine, 40 (8): 705-714 (2010)A bio-inspired crime simulation model., , , , and . Decis. Support Syst., 48 (1): 282-292 (2009)Clustering ensembles: A hedonic game theoretical approach., and . Pattern Recognit., (2018)Ensembling Heterogeneous Learning Models with Boosting., and . ICONIP (1), volume 5863 of Lecture Notes in Computer Science, page 512-519. Springer, (2009)An Empirical Analysis of Meta-learning for the Automatic Choice of Architecture and Components in Ensemble Systems., , and . BRACIS, page 1-6. IEEE Computer Society, (2014)Tackling the biclustering problem with cooperative coevolutionary algorithms., and . ISDA, page 1189-1194. IEEE, (2010)Kernel machines for epilepsy diagnosis via EEG signal classification: A comparative study., and . Artif. Intell. Medicine, 53 (2): 83-95 (2011)