A case study on the application of instance selection techniques for Genetic Fuzzy Rule-Based Classifiers
Bruno Giglio, Francesco Marcelloni, Michela Fazzolari, Rafael Alcalá, Francisco Herrera · 2012
When considering data sets characterized by a large number of instances, the computational time required to apply Genetic Algorithms for generating Fuzzy Rule-Based Classifiers increases considerably, mainly due to the fitness evaluation. Another important problem associated to these kinds of data sets is an undesired increase of the obtained model complexity.