4. Utility Classes and Functions

4.1. Utility Classes

utils.DMLDummyRegressor()	A dummy regressor that raises an AttributeError when attempting to access its fit, predict, or set_params methods.
utils.DMLDummyClassifier()	A dummy classifier that raises an AttributeError when attempting to access its fit, predict, set_params, or predict_proba methods.
utils.DoubleMLBLP(orth_signal, basis[, is_gate])	Best linear predictor (BLP) for DoubleML with orthogonal signals.
utils.DoubleMLPolicyTree(orth_signal, features)	Policy Tree fitting for DoubleML.
utils.GlobalRegressor(base_estimator)	A global regressor that ignores the attribute sample_weight when being fit to ensure a global fit.
utils.GlobalClassifier(base_estimator)	A global classifier that ignores the attribute sample_weight when being fit to ensure a global fit.

4.2. Utility Functions

utils.gain_statistics(dml_long, dml_short)

Compute gain statistics as benchmark values for sensitivity parameters cf_d and cf_y.