An Improved Binary Quantum-based Avian Navigation Optimizer Algorithm to Select Effective Feature Subset from Medical Data: A COVID-19 Case Study

Feature Subset Selection (FSS) is an NP-hard problem to remove redundant and irrelevant features particularly from medical data, and it can be effectively addressed by metaheuristic algorithms. However, existing binary versions of metaheuristic algorithms have issues with convergence and lack an eff...

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Vydané v:	Journal of bionics engineering Ročník 21; číslo 1; s. 426 - 446
Hlavní autori:	Fatahi, Ali, Nadimi-Shahraki, Mohammad H., Zamani, Hoda
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Singapore Springer Nature Singapore 01.01.2024 Springer Nature B.V
Predmet:	Algorithms Artificial Intelligence Biochemical Engineering Bioinformatics Biomaterials Biomedical Engineering and Bioengineering Biomedical Engineering/Biotechnology Convergence COVID-19 Datasets Effectiveness Engineering Heuristic methods Navigation Operators (mathematics) Preprocessing Research Article Search methods Transfer functions Feature subset selection Bioinspired Binary metaheuristic algorithms Medical datasets Optimization Machine learning
ISSN:	1672-6529, 2543-2141
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