导入错误：无法导入cross_validation。

Question

我无法从sklearn库导入交叉验证；我使用sklearn版本0.20.0

from sklearn import cross_validation

代码的后面部分：

features_train, features_test, labels_train, labels_test = cross_validation.train_test_split(word_data, authors, test_size=0.1, random_state=42)

错误：

Traceback (most recent call last):
  File "D:\me\M.Sc\Udacity_ML_course\ud120-projects-  master\naive_bayes\nb_author_id.py", line 16, in <module>
    from email_preprocess import preprocess
  File "../tools/email_preprocess.py", line 8, in <module>
    from sklearn import cross_validation
ImportError: cannot import name cross_validation

Answer 1

cross_validation以前作为Scikit包*存在，但在某些时候被弃用。

如果您正在寻找代码指示的train_test_split，则它位于model_selection：

from sklearn import model_selection

features_train, features_test, labels_train, labels_test = model_selection.train_test_split(
    word_data, authors, test_size=0.1, random_state=42)

_{*看起来这在0.18中发生了变化。}

Answer 2

这是因为sklearn中没有cross_validation对象。你可能在寻找更像cross_validate函数的东西。你可以通过

from sklearn.model_selection import cross_validate

但是，您不需要导入任何交叉验证软件来执行列车测试拆分，因为这只是从数据中随机抽样。试试看

from sklearn.model_selection import train_test_split

接

features_train, features_test, labels_train, labels_test = train_test_split(word_data, authors, test_size=0.1, random_state=42)