import numpy as np

def mean_abs_err(prediction, true_labels):
    """
    
    Calculates the mean absolute error

    Parameters:

        prediction : numpy.ndarray
                    A 1D :py:class:`numpy.ndarray` containing your prediction

        true_labels : numpy.ndarray
                     A 1D :py:class:`numpy.ndarray` containing the ground truth labels for
                     the input array, organized in the same order.
    Returns:
        float,
            The classification error rate
    """
    mae = (np.abs(prediction - true_labels)).sum() / len(prediction)
    return mae