metalearners

• metalearners package
  • Submodules
    • metalearners.cross_fit_estimator module
      • CrossFitEstimator
    • metalearners.data_generation module
      • generate_categoricals()
      • generate_numericals()
      • generate_covariates()
      • insert_missing()
      • generate_treatment()
      • compute_experiment_outputs()
    • metalearners.drlearner module
      • DRLearner
    • metalearners.explainer module
      • Explainer
    • metalearners.metalearner module
      • MetaLearner
    • metalearners.outcome_functions module
      • constant_treatment_effect()
      • no_treatment_effect()
      • linear_treatment_effect()
    • metalearners.rlearner module
      • r_loss()
      • RLearner
    • metalearners.slearner module
      • SLearner
    • metalearners.tlearner module
      • TLearner
    • metalearners.utils module
      • metalearner_factory()
      • simplify_output()
    • metalearners.xlearner module
      • XLearner
  • Module contents
    • DRLearner
      • DRLearner.nuisance_model_specifications()
      • DRLearner.treatment_model_specifications()
      • DRLearner.fit()
      • DRLearner.predict()
      • DRLearner.evaluate()
      • DRLearner.explainer()
      • DRLearner.feature_importances()
      • DRLearner.fit_nuisance()
      • DRLearner.fit_treatment()
      • DRLearner.predict_conditional_average_outcomes()
      • DRLearner.predict_nuisance()
      • DRLearner.predict_treatment()
      • DRLearner.shap_values()
    • RLearner
      • RLearner.nuisance_model_specifications()
      • RLearner.treatment_model_specifications()
      • RLearner.fit()
      • RLearner.predict()
      • RLearner.evaluate()
      • RLearner.explainer()
      • RLearner.feature_importances()
      • RLearner.fit_nuisance()
      • RLearner.fit_treatment()
      • RLearner.predict_nuisance()
      • RLearner.predict_treatment()
      • RLearner.shap_values()
    • SLearner
      • SLearner.nuisance_model_specifications()
      • SLearner.treatment_model_specifications()
      • SLearner.fit()
      • SLearner.predict()
      • SLearner.evaluate()
      • SLearner.predict_conditional_average_outcomes()
      • SLearner.explainer()
      • SLearner.feature_importances()
      • SLearner.fit_nuisance()
      • SLearner.fit_treatment()
      • SLearner.predict_nuisance()
      • SLearner.predict_treatment()
      • SLearner.shap_values()
    • TLearner
      • TLearner.nuisance_model_specifications()
      • TLearner.treatment_model_specifications()
      • TLearner.fit()
      • TLearner.predict()
      • TLearner.evaluate()
      • TLearner.explainer()
      • TLearner.feature_importances()
      • TLearner.fit_nuisance()
      • TLearner.fit_treatment()
      • TLearner.predict_conditional_average_outcomes()
      • TLearner.predict_nuisance()
      • TLearner.predict_treatment()
      • TLearner.shap_values()
    • XLearner
      • XLearner.nuisance_model_specifications()
      • XLearner.treatment_model_specifications()
      • XLearner.fit()
      • XLearner.predict()
      • XLearner.evaluate()
      • XLearner.explainer()
      • XLearner.feature_importances()
      • XLearner.fit_nuisance()
      • XLearner.fit_treatment()
      • XLearner.predict_conditional_average_outcomes()
      • XLearner.predict_nuisance()
      • XLearner.predict_treatment()
      • XLearner.shap_values()