A new fusion of grey wolf optimizer algorithm with a two-phase mutation for feature selection

•Anew Grey Wolf Optimizer algorithm with a Two-phase Mutation (TMGWO) is proposed.•Wrapper-based feature selection techniques are proposed using TMGWO algorithm.•The proposed algorithm is benchmarked on 35 standard UCI datasets.•TMGWO algorithm is compared with recent state-of-the-art algorithms.•A...

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Bibliographic Details
Published in:	Expert systems with applications Vol. 139; p. 112824
Main Authors:	Abdel-Basset, Mohamed, El-Shahat, Doaa, El-henawy, Ibrahim, de Albuquerque, Victor Hugo C., Mirjalili, Seyedali
Format:	Journal Article
Language:	English
Published:	New York Elsevier Ltd 01.01.2020 Elsevier BV
Subjects:	Accuracy Algorithms Classification Classifier, accuracy Cross-validation Data mining Datasets Euclidean geometry Feature selection Grey wolf optimization algorithm Mutation Optimization algorithms Particle swarm optimization Probabilistic methods Statistical analysis Wrapper method Classifier, accuracy Grey wolf optimization algorithm Feature selection Mutation Wrapper method Cross-validation
ISSN:	0957-4174, 1873-6793
Online Access:	Get full text
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