diff --git a/.mailmap b/.mailmap index da54fb9eb9db5..a23cd42f3d6c3 100644 --- a/.mailmap +++ b/.mailmap @@ -27,6 +27,7 @@ Federico Vaggi Gael Varoquaux Gael Varoquaux Gilles Louppe +Harikrishnan S Hrishikesh Huilgolkar Immanuel Bayer Jake VanderPlas diff --git a/doc/datasets/twenty_newsgroups.rst b/doc/datasets/twenty_newsgroups.rst index 09f7f3bfc9d84..8d8a5fad2768f 100644 --- a/doc/datasets/twenty_newsgroups.rst +++ b/doc/datasets/twenty_newsgroups.rst @@ -86,9 +86,9 @@ for statistical analysis. This can be achieved with the utilities of the example that extract `TF-IDF`_ vectors of unigram tokens:: - >>> from sklearn.feature_extraction.text import Vectorizer + >>> from sklearn.feature_extraction.text import TfidfVectorizer >>> documents = [open(f).read() for f in newsgroups_train.filenames] - >>> vectorizer = Vectorizer() + >>> vectorizer = TfidfVectorizer() >>> vectors = vectorizer.fit_transform(documents) >>> vectors.shape (1073, 21108)