Moses Openja, Gabriel Laberge and Foutse Khomh
Article (2024)
An external link is available for this item| Department: | Department of Computer Engineering and Software Engineering |
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| PolyPublie URL: | https://publications.polymtl.ca/57222/ |
| Journal Title: | Empirical Software Engineering (vol. 29, no. 1) |
| Publisher: | Springer |
| DOI: | 10.1007/s10664-023-10409-5 |
| Official URL: | https://doi.org/10.1007/s10664-023-10409-5 |
| Date Deposited: | 29 Jan 2024 14:38 |
| Last Modified: | 08 Apr 2025 07:26 |
| Cite in APA 7: | Openja, M., Laberge, G., & Khomh, F. (2024). Detection and evaluation of bias-inducing features in machine learning. Empirical Software Engineering, 29(1), 71 pages. https://doi.org/10.1007/s10664-023-10409-5 |
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