class_docstr: A parent class for T-learner classifier classes.
class_docstr_tok: ["A","parent","class","for","T-learner","classifier","classes","."]
docstr: Initialize a T-learner classifier.
  
  Args:
      learner (model): a model to estimate control and treatment outcomes.
      control_learner (model, optional): a model to estimate control outcomes
      treatment_learner (model, optional): a model to estimate treatment outcomes
      ate_alpha (float, optional): the confidence level alpha of the ATE estimate
      control_name (str or int, optional): name of control group
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code: def __init__(
      self,
      learner=None,
      control_learner=None,
      treatment_learner=None,
      ate_alpha=0.05,
      control_name=0,
  ):
      """Initialize a T-learner classifier.
  
      Args:
          learner (model): a model to estimate control and treatment outcomes.
          control_learner (model, optional): a model to estimate control outcomes
          treatment_learner (model, optional): a model to estimate treatment outcomes
          ate_alpha (float, optional): the confidence level alpha of the ATE estimate
          control_name (str or int, optional): name of control group
      """
      super().__init__(
          learner=learner,
          control_learner=control_learner,
          treatment_learner=treatment_learner,
          ate_alpha=ate_alpha,
          control_name=control_name,
      )
  
imports: from copy import deepcopy
  import logging
  import numpy
  from packaging import version
  from scipy.stats import norm
  import sklearn
  from sklearn.exceptions import ConvergenceWarning
  from sklearn.neural_network import MLPRegressor
  from tqdm import tqdm
  from xgboost import XGBRegressor
  from causalml.inference.meta.base import BaseLearner
  from causalml.inference.meta.utils import check_treatment_vector, convert_pd_to_np
  from causalml.metrics import regression_metrics, classification_metrics
label_desc: Use image node_id 1 to create a new BaseTClassifier object from inherited base classes: BaseTLearner with example: obj = BaseTClassifier(learner, control_learner, treatment_learner, ate_alpha, control_name)