Function data_handling

machine_learning/xgboost_classifier.py:10–21

>>> data_handling(({'data':'[5.1, 3.5, 1.4, 0.2]','target':([0])})) ('[5.1, 3.5, 1.4, 0.2]', [0]) >>> data_handling( ... {'data': '[4.9, 3.0, 1.4, 0.2], [4.7, 3.2, 1.3, 0.2]', 'target': ([0, 0])} ... ) ('[4.9, 3.0, 1.4, 0.2], [4.7, 3.2, 1.3, 0.2]', [0, 0])

(data: dict)

def data_handling(data: dict) -> tuple:
    # Split dataset into features and target
    # data is features
    """
    >>> data_handling(({'data':'[5.1, 3.5, 1.4, 0.2]','target':([0])}))
    ('[5.1, 3.5, 1.4, 0.2]', [0])
    >>> data_handling(
    ...     {'data': '[4.9, 3.0, 1.4, 0.2], [4.7, 3.2, 1.3, 0.2]', 'target': ([0, 0])}
    ... )
    ('[4.9, 3.0, 1.4, 0.2], [4.7, 3.2, 1.3, 0.2]', [0, 0])
    """
    return (data["data"], data["target"])


def xgboost(features: np.ndarray, target: np.ndarray) -> XGBClassifier: