Binary Peacock Algorithm: A Novel Metaheuristic Approach for Feature Selection

Binary metaheuristic algorithms prove to be invaluable for solving binary optimization problems. This paper proposes a binary variant of the peacock algorithm (PA) for feature selection. PA, a recent metaheuristic algorithm, is built upon lekking and mating behaviors of peacocks and peahens. While d...

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Bibliographic Details
Published in:	Journal of classification Vol. 41; no. 2; pp. 216 - 244
Main Authors:	Banati, Hema, Sharma, Richa, Yadav, Asha
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.07.2024 Springer Nature B.V
Subjects:	Accuracy Algorithms Bioinformatics Classification Datasets Experiments Feature selection Heuristic methods Marketing Mathematics and Statistics Mating Optimization Pattern Recognition Psychometrics Random variables Rank tests Signal,Image and Speech Processing Statistical Theory and Methods Statistics Support vector machines Variants Binary metaheuristic algorithms Feature selection Optimization Binary peacock algorithm Classification
ISSN:	0176-4268, 1432-1343
Online Access:	Get full text
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