causalml/inference/meta/tlearner.py [306:329]:
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    def __init__(
        self,
        learner=None,
        control_learner=None,
        treatment_learner=None,
        ate_alpha=0.05,
        control_name=0,
    ):
        """Initialize a T-learner regressor.

        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,
        )
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causalml/inference/meta/tlearner.py [337:360]:
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    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,
        )
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