'function' 对象没有属性 'train_test_split'

Question

我是在 Python 中实施机器学习的新手，目前正在按照 YouTube 教程尝试 KNN 分类。这是代码。

import numpy as np
#from sklearn.model_selection import train_test_split
from sklearn.model_selection import cross_validate
import pandas as pd

df=pd.read_csv('breast-cancer-wisconsin.data.txt')
df.replace('?', -99999, inplace=True)
df.drop(['id'],1,inplace=True)

X=np.array(df.drop(['class'],1))
y=np.array(df['class'])

X_train, X_test, y_train, y_test=cross_validate.train_test_split(X,y,test_size=0.2)

我收到以下错误：-

X_train, X_test, y_train, y_test=cross_validate.train_test_split(X,y,test_size=0.2)
AttributeError: 'function' object has no attribute 'train_test_split'

我尝试将 train_test_split 导入为

 from sklearn.model_selection import train_test_split

但后来我得到了同样的错误。任何帮助表示赞赏。谢谢！

Answer 1

train_test_split是一个单独的模块（docs），不能与cross_validate结合使用；这里的正确用法是（假设 scikit-learn v0.20）：

from sklearn.model_selection import train_test_split
# [...]
X_train, X_test, y_train, y_test=train_test_split(X,y,test_size=0.2)

Answer 2

sklearn.cross_validation 已在 0.20 版中弃用。

使用sklearn.model_selection.train_test_split

Answer 3

我正在观看与 2021 年 4 月相同的教程和正确答案，如下所示：

from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X,y,test_size=0.2)

这里是课程的完整代码：

import numpy as np
from sklearn import preprocessing, neighbors
from sklearn.model_selection import train_test_split
import pandas as pd

df= pd.read_csv('breast-cancer-wisconsin.data')
# print(df.head())

df.replace('?', -99999, inplace=True)

df.drop(['id'], 1, inplace=True)
# print(df.columns)


X= np.array(df.drop(['class'],1))
y= np.array(df['class'])

X_train, X_test, y_train, y_test = train_test_split(X,y,test_size=0.2)

clf = neighbors.KNeighborsClassifier()
clf.fit(X_train,y_train)


accuracy= clf.score(X_test,y_test)
print(accuracy)

'function' 对象没有属性 'train_test_split'

'function' object has no attribute 'train_test_split'

python

python-3.x

scikit-learn

cross-validation