Grasshopper Optimization Algorithm with Crossover Operators for Feature Selection and Solving Engineering Problems

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Grasshopper Optimization Algorithm with Crossover Operators for Feature Selection and Solving Engineering Problems

Feature selection (FS) is an irreplaceable phase that makes data mining more efficient. It effectively enhances the implementation and decreases the computational problem of learning models. The comprehensive and greedy algorithms are not suitable for the present growing number of features when dete...

書目詳細資料
發表在:	IEEE Access
主要作者:	2-s2.0-85125331226
格式:	Article
語言:	English
出版:	Institute of Electrical and Electronics Engineers Inc. 2022
在線閱讀:	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125331226&doi=10.1109%2fACCESS.2022.3153038&partnerID=40&md5=384f2b8910e5d109c1a4785423aea347

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