An efficient hybrid filter-wrapper method based on improved Harris Hawks optimization for feature selection
The two-stage hybrid method effectively selects the optimal subset of features, improving the performance of classification algorithms on high-dimensional datasets. This approach addresses the challenges posed by the abundance of features, low number of samples, and imbalanced class samples, demonstrating its potential for application in various fields.
Authors
- Mohammad Mehdi Pourhashem Kallehbasti (ORCID: https://orcid.org/0000-0001-9484-6813)
- Ali Kermani (ORCID: https://orcid.org/0000-0001-9298-7970)
- Jamshid Pirgazi (ORCID: https://orcid.org/0000-0002-2461-1143)
- Ali Ghanbari Sorkhi (ORCID: https://orcid.org/0000-0001-7064-5857)
Institutions
- University of Science and Technology of Mazandaran (IR)
Publication Details
- Journal
- Bioimpacts
- Published
- 2024-10-01
- DOI
- https://doi.org/10.34172/bi.30340
- Citations
- 5
- Primary Topic
- Advanced Algorithms and Applications
- Type
- article
- Field-Weighted Citation Impact
- 1.64