Enhanced Binary Kepler Optimization Algorithm for effective feature selection of supervised learning classification
Abstract This study proposes an Enhanced Binary Kepler Optimization Algorithm (BKOA-MUT) improves feature selection (FS) by integrating Kepler’s planetary motion laws with DE/rand and DE/best Mutation Approach. BKOA-MUT balances exploration and exploitation, effectively guiding search for optimal fe...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-04-01
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| Series: | Journal of Big Data |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40537-025-01125-6 |
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