An efficient binary chaotic symbiotic organisms search algorithm approaches for feature selection problems

Feature selection is one of the main steps in preprocessing data in machine learning, and its goal is to reduce features by removing additional and noisy features. Feature selection methods and feature reduction in a dataset must consider the accuracy of the classifying algorithms. Meta-heuristic al...

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Vydané v:	The Journal of supercomputing Ročník 77; číslo 8; s. 9102 - 9144
Hlavní autori:	Mohmmadzadeh, Hekmat, Gharehchopogh, Farhad Soleimanian
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.08.2021 Springer Nature B.V
Predmet:	Accuracy Algorithms Compilers Computer Science Datasets Feature selection Heuristic Heuristic methods High Performance Computing in Science and Engineering - CMMSE-2019 Interpreters Machine learning Mutation Mutualism Operators (mathematics) Organisms Processor Architectures Programming Languages Search algorithms Transfer functions Feature selection Binary symbiotic organisms search Optimization Classification
ISSN:	0920-8542, 1573-0484
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