This paper studies the influence of what are recognized as key issues in evolutionary multi-objective optimization: archiving (to keep track of the current non-dominated solutions...
Abstract— In previous work, we have shown that both unsupervised feature selection and the semi-supervised clustering problem can be usefully formulated as multiobjective optimiz...
Classification of texts potentially containing a complex and specific terminology requires the use of learning methods that do not rely on extensive feature engineering. In this w...
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...
Spectral feature selection identifies relevant features by measuring their capability of preserving sample similarity. It provides a powerful framework for both supervised and uns...