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...
| الحاوية / القاعدة: | IEEE Access |
|---|---|
| المؤلف الرئيسي: | |
| التنسيق: | مقال |
| اللغة: | English |
| منشور في: |
Institute of Electrical and Electronics Engineers Inc.
2022
|
| الوصول للمادة أونلاين: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125331226&doi=10.1109%2fACCESS.2022.3153038&partnerID=40&md5=384f2b8910e5d109c1a4785423aea347 |