我使用的是Ubuntu 14.04中的python 2.7。我用这些命令安装了scikit-learn, numpy和matplotlib:

sudo apt-get install build-essential python-dev python-numpy \
python-numpy-dev python-scipy libatlas-dev g++ python-matplotlib \
ipython

但是当我导入这些包时:

from sklearn.cross_validation import train_test_split

它返回给我这个错误:

ImportError: No module named sklearn.cross_validation

我需要做什么?


当前回答

确保你已经安装了Anaconda,然后使用conda创建一个virtualenv。这将确保所有导入工作正常

Python 2.7.9 |Anaconda 2.2.0 (64-bit)| (default, Mar  9 2015, 16:20:48) 
[GCC 4.4.7 20120313 (Red Hat 4.4.7-1)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
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>>> from sklearn.cross_validation import train_test_split

其他回答

这可能是由于sklearn.cross_validation的弃用。 请替换sklearn。使用sklearn.model_selection进行交叉验证

Ref - https://github.com/amueller/scipy_2015_sklearn_tutorial/issues/60

像这样更改代码

# from sklearn.cross_validation import train_test_split
from sklearn.model_selection import train_test_split

sklearn。Cross_validation现在改为sklearn.model_selection

只使用

from sklearn.model_selection import train_test_split

我想那会有用的。

如果你有需要运行不同版本的代码,你可以这样做:

import sklearn
if sklearn.__version__ > '0.18':
    from sklearn.model_selection import train_test_split
else:
    from sklearn.cross_validation import train_test_split

但这并不理想,因为您将包版本作为字符串进行比较,这通常有效,但并不总是如此。如果你愿意安装打包,这是一个更好的方法:

from packaging.version import parse
import sklearn
if parse(sklearn.__version__) > parse('0.18'):
    from sklearn.model_selection import train_test_split
else:
    from sklearn.cross_validation import train_test_split

Train_test_split是sklearn模块的一部分。因此,您可能需要从Model_selection导入模块

代码:

from sklearn.model_selection import train_test_split