Bi-objective feature selection in high-dimensional datasets using improved binary chimp optimization algorithm
The machine learning process in high-dimensional datasets is far more complicated than in low-dimensional datasets. In high-dimensional datasets, Feature Selection (FS) is necessary to decrease the complexity of learning. However, FS in high-dimensional datasets is a complex process that requires th...
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| Vydané v: | International journal of machine learning and cybernetics Ročník 15; číslo 12; s. 6107 - 6148 |
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| Hlavní autori: | , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.12.2024
Springer Nature B.V |
| Predmet: | |
| ISSN: | 1868-8071, 1868-808X |
| On-line prístup: | Získať plný text |
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