B-MFO: A Binary Moth-Flame Optimization for Feature Selection from Medical Datasets

Advancements in medical technology have created numerous large datasets including many features. Usually, all captured features are not necessary, and there are redundant and irrelevant features, which reduce the performance of algorithms. To tackle this challenge, many metaheuristic algorithms are...

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Veröffentlicht in:	Computers (Basel) Jg. 10; H. 11; S. 136
Hauptverfasser:	Nadimi-Shahraki, Mohammad H., Banaie-Dezfouli, Mahdis, Zamani, Hoda, Taghian, Shokooh, Mirjalili, Seyedali
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 01.11.2021
Schlagworte:	Algorithms binary metaheuristic algorithms Butterflies & moths Classification Datasets Feature selection Heuristic methods medical datasets Medical diagnosis Methods Optimization Optimization algorithms swarm intelligence algorithms transfer function Transfer functions
ISSN:	2073-431X, 2073-431X
Online-Zugang:	Volltext
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