ModuleNotFoundError: No module named 'sklearn.preprocessing._data'

Question

My question is similar to this .

I also use pickle to save & load model. I meet the below error during pickle.load( )

from sklearn.preprocessing import StandardScaler
# SAVE
scaler = StandardScaler().fit(X_train)
X_trainScale = scaler.transform(X_train)
pickle.dump(scaler, open('scaler.scl','wb'))

# =================
# LOAD
sclr = pickle.load(open('scaler.scl','rb'))  # => ModuleNotFoundError: No module named 'sklearn.preprocessing._data'
X_testScale = sclr.transform(X_test)

ModuleNotFoundError: No module named 'sklearn.preprocessing._data'

It looks like a sklearn version issue. My sklearn version is 0.20.3, Python version is 3.7.3.

But I am using Python in an Anaconda .zip file. Is it possible to solve this without updating the version of sklearn?

Answer 1

I had exactly the same error message with StandardScaler using Anaconda.

Fixed it by running:

conda update --all

I think the issue was caused by running the pickle dump for creating the scaler file on a machine with a newer version of scikit-learn, and then trying to run pickle load on machine with an older version of scikit-learn. (It gave the error when running pickle load on the machine with the older version of scikit-learn but no error when running pickle load on the machine with the newer version of scikit-learn. Both windows machines). Perhaps this is due to more recent versions using a different naming convention for functions regarding underscores (as mentioned above)?

Anaconda would not let me update the scikit-learn library on it's own, because it claimed it required the older version (for some reason I could not understand). Perhaps another library was using it? So I had to fix it by updating all the libraries at the same time, which worked.

Answer 2

通过 pip install -U scikit-learn 升级到兼容版本的 sklearn

Answer 3

This very specific problem occurs when there is sklearn version mismatch. For example, trying to deserialize a sklearn(>= 0.22.X) object dumped with another sklearn version < 0.22.X. Sklearn introduced a change between those version, check their release website for mo information

Answer 4

安装旧版本的 sklearn pip install "scikit-learn==0.19.0"

Answer 5

I was facing a similar issue after updating scikit-learn. In my case, the culprit was QuantileTransformer . Changing

from sklearn.preprocessing.data import QuantileTransformer

to

from sklearn.preprocessing import QuantileTransformer

worked for me.

Answer 6

从 sklearn 导入 preprocessing._data 作为 StandardScaler