class_docstr: A parent class for DR-learner regressor classes.
  
  A DR-learner estimates treatment effects with machine learning models.
  
  Details of DR-learner are available at Kennedy (2020) (https://arxiv.org/abs/2004.14497).
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code: def __repr__(self):
      return (
          "{}(control_outcome_learner={},\n"
          "\ttreatment_outcome_learner={},\n"
          "\ttreatment_effect_learner={})".format(
              self.__class__.__name__,
              self.model_mu_c.__repr__(),
              self.model_mu_t.__repr__(),
              self.model_tau.__repr__(),
          )
      )
  
imports: from copy import deepcopy
  import logging
  import numpy
  import pandas
  from scipy.stats import norm
  from sklearn.model_selection import cross_val_predict, KFold
  from tqdm import tqdm
  from xgboost import XGBRegressor
  from causalml.inference.meta.base import BaseLearner
  from causalml.inference.meta.utils import check_treatment_vector, check_p_conditions, convert_pd_to_np
  from causalml.metrics import regression_metrics, classification_metrics
  from causalml.propensity import compute_propensity_score
label_desc: Use image node_id 2 for calling the BaseDRLearner obj's underlying member method code with example usage: obj.__repr__() and returns: str