def METHOD_NAME():
    data = pd.DataFrame(
        {
            "regression_unique_enough": [float(x) for x in range(100)],
            "regression_not_unique_enough": [float(1) for x in range(100)],
        },
    )
    uniqueness_check = UniquenessDataCheck(problem_type="regression")
    assert uniqueness_check.validate(data) == [
        DataCheckWarning(
            message="Input columns 'regression_not_unique_enough' for regression problem type are not unique enough.",
            data_check_name=uniqueness_data_check_name,
            message_code=DataCheckMessageCode.NOT_UNIQUE_ENOUGH,
            details={
                "columns": ["regression_not_unique_enough"],
                "uniqueness_score": {"regression_not_unique_enough": 0.0},
            },
            action_options=[
                DataCheckActionOption(
                    DataCheckActionCode.DROP_COL,
                    data_check_name=uniqueness_data_check_name,
                    metadata={"columns": ["regression_not_unique_enough"]},
                ),
            ],
        ).to_dict(),
    ]
    data = pd.DataFrame(
        {
            "multiclass_too_unique": ["Cats", "Are", "Absolutely", "The", "Best"] * 20,
            "multiclass_not_too_unique": ["Cats", "Cats", "Best", "Best", "Best"] * 20,
        },
    )
    uniqueness_check = UniquenessDataCheck(problem_type="multiclass")
    assert uniqueness_check.validate(data) == [
        DataCheckWarning(
            message="Input columns 'multiclass_too_unique' for multiclass problem type are too unique.",
            data_check_name=uniqueness_data_check_name,
            message_code=DataCheckMessageCode.TOO_UNIQUE,
            details={
                "columns": ["multiclass_too_unique"],
                "uniqueness_score": {"multiclass_too_unique": 0.7999999999999999},
            },
            action_options=[
                DataCheckActionOption(
                    DataCheckActionCode.DROP_COL,
                    data_check_name=uniqueness_data_check_name,
                    metadata={"columns": ["multiclass_too_unique"]},
                ),
            ],
        ).to_dict(),
    ]