Partial Dependence
An explainability technique that shows the marginal effect one or two specific features have on the predicted outcome of a machine learning model.
Think of It Like This
Like checking how the price of a house changes if you only increase the square footage, while keeping the location and age exactly the same.
Partial Dependence Plots (PDP) isolate a feature to visualize whether its relationship with the target is linear, monotonic, or complex. It works by averaging the model's predictions over the marginal distribution of all other features. While highly useful for interpreting black-box models, it assumes the features are perfectly independent.