["python","machine-learning","scikit-learn","classification"]
Save classifier to disk in scikit-learn

How do I save a trained Naive Bayes classifier to disk and use it to predict data? I have the following sample program from the scikit-learn website: from sklearn import datasets iris = datasets.load_iris() from sklearn.naive_bayes import GaussianNB gnb = GaussianNB() y_pred = gnb.fit(iris.data, iris.target).predict(iris.data) print "Number of mislabeled points : %d" % (iris.target != y_pred).sum()
Classifiers are just objects that can be pickled and dumped like any other. To continue your example: import cPickle # save the classifier with open('my_dumped_classifier.pkl', 'wb') as fid: cPickle.dump(gnb, fid) # load it again with open('my_dumped_classifier.pkl', 'rb') as fid: gnb_loaded = cPickle.load(fid)