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...

詳細記述

書誌詳細
出版年:IEEE Access
第一著者: 2-s2.0-85125331226
フォーマット: 論文
言語:English
出版事項: Institute of Electrical and Electronics Engineers Inc. 2022
オンライン・アクセス: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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