— Both theory and a wealth of empirical studies have established that ensembles are more accurate than single predictive models. Unfortunately, the problem of how to maximize ens...
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...
Feature selection for ensembles has shown to be an effective strategy for ensemble creation. In this paper we present an ensemble feature selection approach based on a hierarchica...
Luiz E. Soares de Oliveira, Robert Sabourin, Fl&aa...
This paper studies the strategies for multi-objective optimization in a dynamic environment. In particular, we focus on problems with objective replacement, where some objectives ...
—Machine learning is inherently a multiobjective task. Traditionally, however, either only one of the objectives is adopted as the cost function or multiple objectives are aggreg...