Saving a cross-validation trained model in Scikit

Question

I have trained a model in scikit-learn using Cross-Validation and Naive Bayes classifier. How can I persist this model to later run against new instances?

Here is simply what I have, I can get the CV scores but I don't know how to have access to the trained model

gnb = GaussianNB() 
scores = cross_validation.cross_val_score(gnb, data_numpy[0],data_numpy[1], cv=10)

Answer 1

cross_val_score doesn't changes your estimator, and it will not return fitted estimator. It just returns score of estimator of cross validation.

To fit your estimator - you should call fit on it explicitly with provided dataset. To save (serialize) it - you can use pickle:

# To fit your estimator
gnb.fit(data_numpy[0], data_numpy[1])
# To serialize
import pickle
with open('our_estimator.pkl', 'wb') as fid:
    pickle.dump(gnb, fid)
# To deserialize estimator later
with open('our_estimator.pkl', 'rb') as fid:
    gnb = pickle.load(fid)