Examples
Working example notebooks are available in the example folder.
Follow the below links for an approximate ordering of example tutorials from introductory to advanced features.
- Meta-Learners Examples - Training, Estimation, Validation, Visualization
- Uplift Trees Example with Synthetic Data
- Meta-Learners Examples - Single/Multiple Treatment Cases
- Uplift Trees/Forests Visualization
- Model Interpretation with Feature Importance and SHAP Values
- Uplift Curves with TMLE Example
- DragonNet vs Meta-Learners Benchmark with IHDP + Synthetic Datasets
- 2SLS Benchmarks with NLSYM + Synthetic Datasets
- Sensitivity Analysis Examples
- Unit Selection Based on Counterfactual Logic by Li and Pearl (2019)
- Counterfactual Value Estimation Using Outcome Imputation by Li and Pearl (2019)
- Feature Selection for Uplift Trees by Zhao et al. (2020)
- Policy Learner by Athey and Wager (2018) with Binary Treatment
- CEVAE vs. Meta-Learners Benchmark with IHDP + Synthetic Datasets
- DR Learner vs. DR-IV Learner vs. X-Learner Benchmark with Synthetic Data
- Meta-Learner Benchmarks with Synthetic Data in Nie and Wager (2020)
- Causal Trees/Forests Treatment Effects Estimation and Tree Visualization
- Causal Trees/Forests Interpretation with Feature Importance and SHAP Values
- Logistic Regression Based Data Generation Function for Uplift Classification Problem
- Qini curves with multiple costly treatment arms