Incorporating causal graphical prior knowledge into predictive modeling via simple data augmentation

Takeshi Teshima, Masashi Sugiyama

Abstract: Causal graphs (CGs) are compact representations of the knowledge of the data generating processes behind the data distributions. When a CG is available, e.g., from the domain knowledge, we can infe...