A multi-objective optimization algorithm for feature selection problems

Feature selection (FS) is a critical step in data mining, and machine learning algorithms play a crucial role in algorithms performance. It reduces the processing time and accuracy of the categories. In this paper, three different solutions are proposed to FS. In the first solution, the Harris Hawks...

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Veröffentlicht in:	Engineering with computers Jg. 38; H. Suppl 3; S. 1845 - 1863
Hauptverfasser:	Abdollahzadeh, Benyamin, Gharehchopogh, Farhad Soleimanian
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Springer London 01.08.2022 Springer Nature B.V
Schlagworte:	Algorithms CAE) and Design Calculus of Variations and Optimal Control; Optimization Classical Mechanics Computer Science Computer-Aided Engineering (CAD Control Control methods Data mining Datasets Feature selection Machine learning Math. Applications in Chemistry Mathematical and Computational Engineering Multiple objective analysis Optimization algorithms Original Article Pareto optimization Standard data Statistical tests Systems Theory Multiobjective Feature selection Bonferroni–Holm Fruitfly optimization algorithm Family-wise error rate Harris hawks optimization
ISSN:	0177-0667, 1435-5663
Online-Zugang:	Volltext
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