Individually fair optimal decision trees: Using a dynamic programming approach

In this paper, we tackle the problem of creating decision trees that are both optimal and individually fair. While decision trees are popular due to their interpretability, achieving optimality can be difficult. Existing approaches either lack scalability or fail to consider individual fairness. To address this, we define individual fairness as...