DOC TfidfVectorizer, CountVectorizer fixed_vocabulary_ documentation (#14372)

mandalbiswadip · qinhanmin2014 · commit ef8e3c980f08 · 2019-07-15T15:31:47.000+08:00
diff --git a/sklearn/feature_extraction/text.py b/sklearn/feature_extraction/text.py
@@ -825,6 +825,10 @@ class CountVectorizer(BaseEstimator, VectorizerMixin):
     vocabulary_ : dict
         A mapping of terms to feature indices.
 
+    fixed_vocabulary_: boolean
+        True if a fixed vocabulary of term to indices mapping
+        is provided by the user
+
     stop_words_ : set
         Terms that were ignored because they either:
 
@@ -1497,6 +1501,10 @@ class TfidfVectorizer(CountVectorizer):
     vocabulary_ : dict
         A mapping of terms to feature indices.
 
+    fixed_vocabulary_: boolean
+        True if a fixed vocabulary of term to indices mapping
+        is provided by the user
+
     idf_ : array, shape (n_features)
         The inverse document frequency (IDF) vector; only defined
         if ``use_idf`` is True.
