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...
| Published in: | IEEE Access |
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| Main Author: | |
| Format: | Article |
| Language: | English |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2022
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125331226&doi=10.1109%2fACCESS.2022.3153038&partnerID=40&md5=384f2b8910e5d109c1a4785423aea347 |