In this paper, we present two novel memetic algorithms (MAs) for gene selection. Both are synergies of Genetic Algorithm (wrapper methods) and local search methods (filter methods...
Abstract. Practical pattern classification and knowledge discovery problems require selecting a useful subset of features from a much larger set to represent the patterns to be cl...
Feature selection is the task of choosing a small set out of a given set of features that capture the relevant properties of the data. In the context of supervised classification ...
Aerial photos with LiDAR data were processed with genetic algorithms for not only the feature extraction but also orthographical image. DSM provided by LiDAR reduced the amount of...
In this paper a methodology for feature selection in unsupervised learning is proposed. It makes use of a multiobjective genetic algorithm where the minimization of the number of ...