AI, Data Science, Predictions, Machine Learning, Causal Inference.
data. The test set MAE is 5.78, significantly larger than the XGBoost performance. The result of the counterfactual query (do(T=500mL), given [X = 18.2 years, T = 82mL, Y = 34.8 years]) is 76.2 years, with the MAE compared to ground truth of only 0.35 years vs 41.8 for XGBoost. Hence, CausalNet was