def __init__()

in causalml/inference/tree/models.py [0:0]

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

    def __init__(self,
                 n_estimators=10,
                 max_features=10,
                 random_state=2019,
                 max_depth=5,
                 min_samples_leaf=100,
                 min_samples_treatment=10,
                 n_reg=10,
                 evaluationFunction=None,
                 control_name=None,
                 normalization=True,
                 n_jobs=-1):
        """
        Initialize the UpliftRandomForestClassifier class.
        """
        self.classes_ = {}
        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.evaluationFunction = evaluationFunction
        self.control_name = control_name
        self.n_jobs = n_jobs

        # Create forest
        self.uplift_forest = []
        for _ in range(n_estimators):
            uplift_tree = UpliftTreeClassifier(
                max_features=self.max_features, max_depth=self.max_depth,
                min_samples_leaf=self.min_samples_leaf,
                min_samples_treatment=self.min_samples_treatment,
                n_reg=self.n_reg,
                evaluationFunction=self.evaluationFunction,
                control_name=self.control_name,
                normalization=normalization)

            self.uplift_forest.append(uplift_tree)

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