Binary Aquila Optimizer for Selecting Effective Features from Medical Data: A COVID-19 Case Study

Medical technological advancements have led to the creation of various large datasets with numerous attributes. The presence of redundant and irrelevant features in datasets negatively influences algorithms and leads to decreases in the performance of the algorithms. Using effective features in data...

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Vydané v:	Mathematics (Basel) Ročník 10; číslo 11; s. 1929
Hlavní autori:	Nadimi-Shahraki, Mohammad H., Taghian, Shokooh, Mirjalili, Seyedali, Abualigah, Laith
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.06.2022
Predmet:	Algorithms binary metaheuristic algorithm Classification Coronaviruses COVID-19 Data mining Datasets Decision making Engineering Evolution Feature selection Genetic algorithms Heuristic methods Mathematical optimization Mathematics medical data nature-inspired algorithm Optimization Optimization algorithms Search algorithms transfer function Transfer functions Germany
ISSN:	2227-7390, 2227-7390
On-line prístup:	Získať plný text
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