title: SGDClassifier with HashingVectorizer and TfidfTransformer
body: <p>I would like to understand if it is possible to train an online SGDClassifier (with partial_fit) using HashingVectorizer and TfidfTransformer. Simply joining them in a Pipeline will not work as TfidfTransformer is stateful so that would break the online learning process. <a href="https://stackoverflow.com/questions/24517793/online-version-of-scikit-learns-tfidfvectorizer">This post</a> says it's not possible to use tf-idf in an online fashion but a comment on <a href="https://stackoverflow.com/questions/17931865/using-partial-fit-with-scikit-pipeline">this post</a> suggests that it may somehow be possible: <em>"In particular if you use stateful transformers as TfidfTransformer you will need to do several passes on your data"</em>. Is that possible without loading the whole training set into memory? If so, how? If not, is there an alternative solution to combine HashingVectorizer with tf-idf on large datasets?</p>