Man pages for Nth-iteration-labs/emcite
Batch Mode Active Learning for Individual Treatment Effect Estimation
| af | Acquisition function, selects $n_2$ units from the test set |
| dgp | Create data according to simulation setting |
| fit_gradient_descent | Fit stochastic gradient descent |
| predict_ite | Predict ITE from trained BART model on given data |
| retrain_and_metrics | Retrain and evaluate the model based on PEHE |
| sampling_data | Create n_1+n_2 dataset |
| sgd_py | Run model in python |
| split_data | Split the data into train and test set |
| train_model | Train BART model for ITE estimation |
