Various methods for ensemble selection and classifier combination have been designed to optimize the results of ensembles of classifiers. Genetic algorithm (GA) which uses the div...
Albert Hung-Ren Ko, Robert Sabourin, Alceu de Souz...
Random subspaces are a popular ensemble construction technique that improves the accuracy of weak classifiers. It has been shown, in different domains, that random subspaces combi...
In this work, the authors have evaluated almost 20 millions ensembles of classifiers generated by several methods. Trying to optimize those ensembles based on the nearest neighbou...
Guillaume Tremblay, Robert Sabourin, Patrick Maupi...
Most works based on diversity suggest that there exists only weak correlation between diversity and ensemble accuracy. We show that by combining the diversities with the classifica...
Albert Hung-Ren Ko, Robert Sabourin, Alceu de Souz...
Ensemble of Classifiers (EoC) has been shown effective in improving the performance of single classifiers by combining their outputs. By using diverse data subsets to train classi...
Albert Hung-Ren Ko, Robert Sabourin, Luiz E. Soare...