Python Sklearn train_test_split() : how to set Which Data is Taken for Training?

Question

对于以下 scikit-learn 函数:train_test_split() :

是否可以告诉函数在哪里设置数据的拆分？

或者换句话说:

我能否告诉函数 X_train, X_test 应该在分割点的左侧或右侧，而 y_train, y_test 应该在右侧？

(并且拆分真的以这种方式工作 - 或者只是在遵守拆分比率之前获取输入数据的任意行？)

如果无法告诉函数应采用哪些数据进行训练和测试:是否有任何等效替代方案可用于此用例？

Answer 1

来自 Scikit Learn 文档: 将数组或矩阵拆分为随机训练和测试子集..

>>> import numpy as np
>>> from sklearn.model_selection import train_test_split
>>> X, y = np.arange(10).reshape((5, 2)), range(5)
>>> X
array([[0, 1],
       [2, 3],
       [4, 5],
       [6, 7],
       [8, 9]])
>>> list(y)
[0, 1, 2, 3, 4]

>>> X_train, X_test, y_train, y_test = train_test_split(
...     X, y, test_size=0.33, random_state=42)
...
>>> X_train
array([[4, 5],
       [0, 1],
       [6, 7]])
>>> y_train
[2, 0, 3]
>>> X_test
array([[2, 3],
       [8, 9]])
>>> y_test
[1, 4]

你也可以关闭随机播放:

>>> train_test_split(y, shuffle=False)
[[0, 1, 2], [3, 4]]