Partial Dependence Plot

Partial dependence plots (PDPs) are visualization tools used to understand the relationship between a single feature and a machine learning model's predictions, averaging out the effects of other features. Current research focuses on improving PDP robustness against data perturbations and model biases, particularly in high-dimensional settings and dynamic environments, as well as addressing limitations when feature interactions are present. These efforts aim to enhance the reliability and interpretability of PDPs for model debugging, scientific discovery, and responsible AI, particularly in applications where understanding model behavior is crucial for trust and decision-making.