Chen, Zhenpeng;
Zhang, Jie M;
Sarro, Federica;
Harman, Mark;
(2023)
A Comprehensive Empirical Study of Bias Mitigation Methods for Machine Learning Classifiers.
ACM Transactions on Software Engineering and Methodology
(In press).
Preview |
Text
TOSEM23-fairness.pdf - Accepted Version Download (4MB) | Preview |
| Type: | Article |
|---|---|
| Title: | A Comprehensive Empirical Study of Bias Mitigation Methods for Machine Learning Classifiers |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | https://arxiv.org/abs/2207.03277 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10163249 |
Downloads since deposit
4,380Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months
Archive Staff Only
 |
View Item |
