python - Python机器学习标签和功能

给定一个具有10,000个观测值和50个特征以及一个标签的数据集，假设火车/测试的比例为75％/ 25％，那么X_train，y_train，X_test和y_test的尺寸是多少？应该是

X_train:(2500, 50)
y_train: (2500, )
X_test: (7500, 50)
y_test: (7500, )

要么

X_train: (7500, 50)
y_train: (7500, )
X_test: (2500, 50)
y_test: (2500, )

最佳答案

您可以使用train_test_split中的sklearn自己查看：

import numpy as np
from sklearn.model_selection import train_test_split

n = 10000
p = 50
X = np.random.random((n,p))
y = np.random.randint(0,2,n)

test = 0.25
d = {}
d["X_train"], d["X_test"], d["y_train"], d["y_test"] = train_test_split(X,y,test_size=test)

for split in d:
    print(split, d[split].shape)

X_train (7500, 50)
X_test (2500, 50)
y_train (7500,)
y_test (2500,)

关于python - Python机器学习标签和功能，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/46015464/