Name
Abstract | ||
|---|---|---|
We provide the asymptotic distribution of the major indexes used in the statistical literature to quantify disparate treatment in machine learning. We aim at promoting the use of confidence intervals when testing the so-called group disparate impact. We illustrate on some examples the importance of using confidence intervals and not a single value. |
Year | Venue | Field |
|---|---|---|
2018 | arXiv: Machine Learning | Disparate impact,Disparate treatment,Artificial intelligence,Confidence interval,Machine learning,Mathematics,Asymptotic distribution |
DocType | Volume | Citations |
Journal | abs/1807.06362 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Philippe Besse | 1 | 19 | 3.09 |
| Eustasio del Barrio | 2 | 2 | 3.16 |
| Paula Gordaliza | 3 | 0 | 0.34 |
| Jean-Michel Loubes | 4 | 43 | 11.63 |