Chapter 22.08: Model-Based Imputation
We introduce model-based imputation, where a surrogate model is trained on the other features to predict the missing values, and discuss its drawbacks: sensitivity to the choice of surrogate model, the need for the surrogate to handle missing values itself, and per-feature hyperparameter tuning.