MNT make working_with_text_data compile w/o warnings
@@ -441,7 +441,7 @@ parameter combinations in parallel with the ``n_jobs`` parameter. If we give
this parameter a value of ``-1``, grid search will detect how many cores
are installed and use them all::
- >>> gs_clf = GridSearchCV(text_clf, parameters, n_jobs=-1)
+ >>> gs_clf = GridSearchCV(text_clf, parameters, cv=5, iid=False, n_jobs=-1)
The grid search instance behaves like a normal ``scikit-learn``
model. Let's perform the search on a smaller subset of the training data
@@ -465,7 +465,7 @@ mean score and the parameters setting corresponding to that score::
...
clf__alpha: 0.001
tfidf__use_idf: True
- vect__ngram_range: (1, 1)
+ vect__ngram_range: (1, 2)
A more detailed summary of the search is available at ``gs_clf.cv_results_``.
