Ensemble meta classifier with sampling and feature selection for data with multiclass imbalance problem
Ensemble learning by combining several single classifiers or another ensemble classifier is one of the procedures to solve the imbalance problem in multiclass data. However, this approach still faces the question of how the ensemble methods obtain their higher performance. In this paper, an investig...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English English |
| Published: |
Universiti Utara Malaysia
2021
|
| Subjects: | |
| Online Access: | https://eprints.ums.edu.my/id/eprint/29977/1/Ensemble%20meta%20classifier%20with%20sampling%20and%20feature%20selection%20for%20data%20with%20multiclass%20imbalance%20problem-Abstract.pdf https://eprints.ums.edu.my/id/eprint/29977/2/Ensemble%20meta%20classifier%20with%20sampling%20and%20feature%20selection%20for%20data%20with%20multiclass%20imbalance%20problem.pdf |
Internet
https://eprints.ums.edu.my/id/eprint/29977/1/Ensemble%20meta%20classifier%20with%20sampling%20and%20feature%20selection%20for%20data%20with%20multiclass%20imbalance%20problem-Abstract.pdfhttps://eprints.ums.edu.my/id/eprint/29977/2/Ensemble%20meta%20classifier%20with%20sampling%20and%20feature%20selection%20for%20data%20with%20multiclass%20imbalance%20problem.pdf