ST-AL: a hybridized search based metaheuristic computational algorithm towards optimization of high dimensional industrial datasets

The rapid growth of data generated by several applications like engineering, biotechnology, energy, and others has become a crucial challenge in the high dimensional data mining. The large amounts of data, especially those with high dimensions, may contain many irrelevant, redundant, or noisy featur...

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Vydané v:	Soft computing (Berlin, Germany) Ročník 27; číslo 18; s. 13553 - 13581
Hlavní autori:	Mostafa, Reham R., El-Attar, Noha E., Sabbeh, Sahar F., Vidyarthi, Ankit, Hashim, Fatma A.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Germany Springer Nature B.V 01.09.2023 Springer Berlin Heidelberg
Predmet:	Accuracy Algorithms Benchmarks Classification Data mining Datasets Exploitation Feature selection Focus Genetic algorithms Global optimization Heuristic Heuristic methods Hybridization Machine learning Methods Optimization algorithms Optimization techniques Performance evaluation Search process High dimensional search space Metaheuristic algorithm Feature optimization Sooty tern optimization Ant lion optimization
ISSN:	1432-7643, 1433-7479
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