2026-05-30T17:20:42Zhttps://riuma.uma.es/rest/oai/requestoai:riuma.uma.es:10630/324752026-02-03T11:10:14Zcom_10630_2254col_10630_37953
RIUMA. Repositorio Institucional de la Universidad de Málaga
author
Nematzadeh, Hossein
author
García-Nieto, José Manuel
author
Navas-Delgado, Ismael
author
Aldana-Montes, José Francisco
2024-08-29T10:22:05Z
2024-08-29T10:22:05Z
2024
Hossein Nematzadeh, José García-Nieto, Ismael Navas-Delgado, José F. Aldana-Montes, Feature selection using a classification error impurity algorithm and an adaptive genetic algorithm improved with an external repository, Knowledge-Based Systems, Volume 301, 2024, 112345, ISSN 0950-7051, https://doi.org/10.1016/j.knosys.2024.112345
https://hdl.handle.net/10630/32475
10.1016/j.knosys.2024.112345
Feature selection in small-sample high-dimensional datasets enhances classification accuracy and reduces computational time for model training. This paper introduces the filter Classification Error Impurity (CEI) as a frequency-based ranker that improves upon existing methods by better identifying non-linear patterns. According to this, the top features identified by the ensemble of CEI, along with Mutual Information (MI) and Fisher Ratio (FR), form the feature space utilized by the Adaptive Genetic Algorithm with External Repository (AGAwER) to identify the optimal feature combination in a wrapper approach. AGAwER leverages an external repository, incorporating the best solutions to enrich the Genetic Algorithm’s (GA) population, thus promoting diversity and enhancing exploration. As a result, a hybrid method called CMF-AGAwER is proposed, which surpasses existing modern feature selection methods. The implementation and data are accessible on GitHub at https://github.com/KhaosResearch/CMF-AGAwER.
eng
Atribución 4.0 Internacional
Algoritmos genéticos
Programación genética (Informática)
Sistemas expertos
Ingeniería del software
Feature selection using a classification error impurity algorithm and an adaptive genetic algorithm improved with an external repository
journal article
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