sklearn中的mean_absolute_percentage_error 1. 解释什么是mean_absolute_percentage_errormean_absolute_percentage_error(MAPE)是一种回归损失函数,用于衡量预测值与真实值之间的相对误差。它计算的是预测值与真实值之差的绝对值相对于真实值绝对值的平均百分比。需要注意的是,尽管名字中包含“百分比”,但输出值并不在...
>>> from sklearn.metrics import mean_absolute_percentage_error >>> y_true = [3, -0.5, 2, 7] >>> y_pred = [2.5, 0.0, 2, 8] >>> mean_absolute_percentage_error(y_true, y_pred) 0.3273... >>> y_true = [[0.5, 1], [-1, 1], [7, -6]] >>> y_pred = [[0, 2]...
这是因为在 sktime 依赖项中使用了来自 sklearn 的私有方法。由于 sklearn 更新为 1.1.0，这个私有...
- :func:`sklearn.metrics.max_error` :pr:`29212` by :user:`Edoardo Abati <EdAbati>`; - :func:`sklearn.metrics.mean_absolute_error` :pr:`27736` by :user:`Edoardo Abati <EdAbati>` and :pr:`29143` by :user:`Tialo <Tialo>` and :user:`Loïc Estève <lesteve>`; - :func:`...
/home/circleci/project/sklearn/model_selection/_validation.py:997: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details: Traceback (most recent call last): File "/home/circleci/project/sklearn/metrics/_scorer.py", line 139, ...