Fair Models in Machine Learning
Fair models in machine learning
Cross-Validation for Fair Models
Profile Fair Models with Respect to Tuning Parameters
Obesity Levels
Fair Ridge Regression Model
Extract information from fair.model objects
Nonconvex Optimization for Regression with Fairness Constraints
Synthetic data set to test fair models
Zafar's Linear and Logistic Regressions
Fair machine learning regression models which take sensitive attributes into account in model estimation. Currently implementing Komiyama et al. (2018) <http://proceedings.mlr.press/v80/komiyama18a/komiyama18a.pdf>, Zafar et al. (2019) <https://www.jmlr.org/papers/volume20/18-262/18-262.pdf> and my own approach from Scutari, Panero and Proissl (2022) <https://link.springer.com/content/pdf/10.1007/s11222-022-10143-w.pdf> that uses ridge regression to enforce fairness.