A survey on datasets for fairness-aware machine learning.
An object of class bn.fit. Refer to the documentation of bnlearn for details.
A discrete Bayesian network modeling law school admission records. The DAG was taken from the referenced paper and the probabilities learned from the associated dataset. The vertices are:
The student's family income bracket (1, 2, 3, 4, 5);
Whether the student will work full-time or part-time (1, 2);
The student's LSAT score (<=37, 37);
Whether the student is male or female (female, male);
Whether the student passed the bar exam on the first try (negative, positive);
Race (non-white, white);
Tier (1, 2, 3, 4, 5, 6);
The student's undergraduate GPA (<3,3, >=3.3);
The first year law school GPA (<=0, >0);
The cumulative law school GPA (<=0, >0);
Le Quy, T., Roy, A., Iosifidis, V., Zhang, W., & Ntoutsi, E. (2022). A survey on datasets for fairness-aware machine learning. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 12(3), e1452.