Classifying newsgroup topics with SVMs

Finally, it is time to build our state-of-the-art SVM-based newsgroup topic classifier using everything we just learned.

First we load and clean the dataset with the entire 20 groups as follows:

>>> categories = None
>>> data_train = fetch_20newsgroups(subset='train',
                          categories=categories, random_state=42)
>>> data_test = fetch_20newsgroups(subset='test',
                          categories=categories, random_state=42)
>>> cleaned_train = clean_text(data_train.data)
>>> label_train = data_train.target
>>> cleaned_test = clean_text(data_test.data)
>>> label_test = data_test.target
>>> term_docs_train = tfidf_vectorizer.fit_transform(cleaned_train)
>>> term_docs_test = tfidf_vectorizer.transform(cleaned_test)

As we have seen...