def _mxentropy(y, y_bin, probs):
    """return negative mean cross entropy since we're maximizing the score
    for hillclimbing"""

    # clip away from extremes to avoid under/overflows
    eps = 1.0e-7
    clipped = np.clip(probs, eps, eps - 1.0)
    clipped /= clipped.sum(axis=1)[:, np.newaxis]

    return (y_bin * np.log(clipped)).sum() / y.shape[0]
dataset/ETHPy150Open dclambert/pyensemble/ensemble.py/_mxentropy/swapped operands of `-`