def __init__()

in causalml/inference/tree/uplift.pyx [0:0]

• 37 lines of code
• 3 McCabe index (conditional complexity)

    def __init__(self,
                 control_name,
                 n_estimators=10,
                 max_features=10,
                 random_state=None,
                 max_depth=5,
                 min_samples_leaf=100,
                 min_samples_treatment=10,
                 n_reg=10,
                 early_stopping_eval_diff_scale=1,
                 evaluationFunction='KL',
                 normalization=True,
                 honesty=False,
                 estimation_sample_size=0.5,
                 n_jobs=-1,
                 joblib_prefer: str = "threads"):

        """
        Initialize the UpliftRandomForestClassifier class.
        """
        self.n_estimators = n_estimators
        self.max_features = max_features
        self.random_state = random_state
        self.max_depth = max_depth
        self.min_samples_leaf = min_samples_leaf
        self.min_samples_treatment = min_samples_treatment
        self.n_reg = n_reg
        self.early_stopping_eval_diff_scale = early_stopping_eval_diff_scale
        self.evaluationFunction = evaluationFunction
        self.control_name = control_name
        self.normalization = normalization
        self.honesty = honesty
        self.n_jobs = n_jobs
        self.joblib_prefer = joblib_prefer

        assert control_name is not None and isinstance(control_name, str), \
            f"control_group should be string but {control_name} is passed"
        self.control_name = control_name
        self.classes_ = [control_name]
        self.n_class = 1

        if self.n_jobs == -1:
            self.n_jobs = mp.cpu_count()