def make_uplift_classification()

in causalml/dataset/classification.py [0:0]

• 32 lines of code
• 1 McCabe index (conditional complexity)

def make_uplift_classification(
    n_samples=1000,
    treatment_name=["control", "treatment1", "treatment2", "treatment3"],
    y_name="conversion",
    n_classification_features=10,
    n_classification_informative=5,
    n_classification_redundant=0,
    n_classification_repeated=0,
    n_uplift_increase_dict={"treatment1": 2, "treatment2": 2, "treatment3": 2},
    n_uplift_decrease_dict={"treatment1": 0, "treatment2": 0, "treatment3": 0},
    delta_uplift_increase_dict={
        "treatment1": 0.02,
        "treatment2": 0.05,
        "treatment3": 0.1,
    },
    delta_uplift_decrease_dict={
        "treatment1": 0.0,
        "treatment2": 0.0,
        "treatment3": 0.0,
    },
    n_uplift_increase_mix_informative_dict={
        "treatment1": 1,
        "treatment2": 1,
        "treatment3": 1,
    },
    n_uplift_decrease_mix_informative_dict={
        "treatment1": 0,
        "treatment2": 0,
        "treatment3": 0,
    },
    positive_class_proportion=0.5,
    random_seed=20190101,