Sklearn saved classifier slow

sklearn_joblib_class_slow

from sklearn.datasets import fetch_20newsgroups

twenty = fetch_20newsgroups()


from sklearn.pipeline import Pipeline

from sklearn.feature_extraction.text import CountVectorizer

from sklearn.feature_extraction.text import TfidfTransformer

X = CountVectorizer().fit_transform(twenty.data)

X_tfidf = TfidfTransformer().fit_transform(X)

from sklearn.naive_bayes import MultinomialNB

from sklearn.naive_bayes import MultinomialNB

classifier = Pipeline([('vect',CountVectorizer()),('tfidf',TfidfTransformer()),('clf',MultinomialNB()),])

_ = classifier.fit(twenty.data,twenty.target)

from sklearn.externals import joblib

_ = joblib.dump(classifier,"test_speed.model",compress=9)



clf = joblib.load("test_speed.model")


clf.predict(["this is a good sentence for debugging this code I think. what do you think"])

#Wall time: 0.83 s