causalkit.eda.eda.CausalEDA.outcome_fit#
- CausalEDA.outcome_fit(outcome_model=None)[source]#
Fit a regression model to predict outcome from confounders only.
Uses a preprocessing+CatBoost regressor pipeline with K-fold cross_val_predict to generate out-of-fold predictions. CatBoost uses all available threads and handles categorical features natively. Returns an OutcomeModel instance containing predicted outcomes and diagnostic methods.
The outcome model predicts the baseline outcome from confounders only, excluding treatment. This is essential for proper causal analysis.
- Parameters:
outcome_model (Optional[Any]) – Custom regression model to use. If None, uses CatBoostRegressor.
- Returns:
An OutcomeModel instance with methods for: - scores: RMSE and MAE regression metrics - shap: SHAP values DataFrame property for outcome prediction
- Return type: