损失函数使用Huber损失函数，python中用什么库函数

在Python中，可以使用scikit-learn库中的Huber损失函数来计算损失。具体的代码如下所示：

from sklearn.metrics import mean_squared_error, mean_absolute_error
from sklearn.utils import check_array

def huber_loss(y_true, y_pred, epsilon=1.0):
    y_true = check_array(y_true)
    y_pred = check_array(y_pred)

    diff = y_true - y_pred
    mask = abs(diff) <= epsilon

    squared_loss = 0.5 * diff ** 2
    linear_loss = epsilon * (abs(diff) - 0.5 * epsilon)

    return np.where(mask, squared_loss, linear_loss)

# 示例
y_true = [1, 2, 3, 4, 5]
y_pred = [1.5, 2.5, 3.5, 4.5, 5.5]

loss = huber_loss(y_true, y_pred, epsilon=1.0)
print("Huber loss:", loss)

这段代码定义了一个名为`huber_loss`的函数，该函数接受真实值`y_true`和预测值`y_pred`作为输入，并返回Huber损失。你可以通过调整`epsilon`参数来控制Huber损失函数的平滑程度。