module 'sklearn' has no attribute 'cross_validation'

python scikit-learn cross-validation
Naren picture Naren · Oct 4, 2017 · Viewed 48.7k times · Source

I am trying to split my dataset into training and testing dataset, but I am getting this error:

X_train,X_test,Y_train,Y_test = sklearn.cross_validation.train_test_split(X,df1['ENTRIESn_hourly'])

AttributeError                            Traceback (most recent call last)
<ipython-input-53-5445dab94861> in <module>()
----> 1 X_train,X_test,Y_train,Y_test = sklearn.cross_validation.train_test_split(X,df1['ENTRIESn_hourly'])

AttributeError: module 'sklearn' has no attribute 'cross_validation'

How can I handle this?

Answer

Brenden Petersen picture Brenden Petersen · Oct 4, 2017

sklearn does not automatically import its subpackages. If you only imported via: import sklearn, then it wont work. Import with import sklearn.cross_validation instead.

Furhter, sklearn.cross_validation will be deprecated in version 0.20. Use sklearn.model_selection.train_test_split instead.

Related questions

How to get Best Estimator on GridSearchCV (Random Forest Classifier Scikit)

I'm running GridSearch CV to optimize the parameters of a classifier in scikit. Once I'm done, I'd like to know which parameters were chosen as the best. Whenever I do so I get a AttributeError: 'RandomForestClassifier' object has no attribute …

Read More
How to use the a k-fold cross validation in scikit with naive bayes classifier and NLTK

I have a small corpus and I want to calculate the accuracy of naive Bayes classifier using 10-fold cross validation, how can do it.

Read More
scikit-learn cross validation, negative values with mean squared error

When I use the following code with Data matrix X of size (952,144) and output vector y of size (952), mean_squared_error metric returns negative values, which is unexpected. Do you have any idea? from sklearn.svm import SVR from sklearn …

Read More