DOC Add links to text/plot_hashing_vs_dict_vectorizer.py example (scikit-learn#26967)

Author: Tialo

sklearn/feature_extraction/_dict_vectorizer.py

@@ -42,6 +42,9 @@ class DictVectorizer(TransformerMixin, BaseEstimator):
     Features that do not occur in a sample (mapping) will have a zero value
     in the resulting array/matrix.
 
+    For an efficiency comparision of the different feature extractors, see
+    :ref:`sphx_glr_auto_examples_text_plot_hashing_vs_dict_vectorizer.py`.
+
     Read more in the :ref:`User Guide <dict_feature_extraction>`.
 
     Parameters

sklearn/feature_extraction/_hash.py

@@ -34,6 +34,9 @@ class FeatureHasher(TransformerMixin, BaseEstimator):
     where memory is tight, e.g. when running prediction code on embedded
     devices.
 
+    For an efficiency comparision of the different feature extractors, see
+    :ref:`sphx_glr_auto_examples_text_plot_hashing_vs_dict_vectorizer.py`.
+
     Read more in the :ref:`User Guide <feature_hashing>`.
 
     .. versionadded:: 0.13

sklearn/feature_extraction/text.py

@@ -602,6 +602,9 @@ class HashingVectorizer(
 
     The hash function employed is the signed 32-bit version of Murmurhash3.
 
+    For an efficiency comparision of the different feature extractors, see
+    :ref:`sphx_glr_auto_examples_text_plot_hashing_vs_dict_vectorizer.py`.
+
     Read more in the :ref:`User Guide <text_feature_extraction>`.
 
     Parameters
@@ -933,6 +936,9 @@ class CountVectorizer(_VectorizerMixin, BaseEstimator):
     that does some kind of feature selection then the number of features will
     be equal to the vocabulary size found by analyzing the data.
 
+    For an efficiency comparision of the different feature extractors, see
+    :ref:`sphx_glr_auto_examples_text_plot_hashing_vs_dict_vectorizer.py`.
+
     Read more in the :ref:`User Guide <text_feature_extraction>`.
 
     Parameters
@@ -1758,6 +1764,9 @@ class TfidfVectorizer(CountVectorizer):
     For an example of usage, see
     :ref:`sphx_glr_auto_examples_text_plot_document_classification_20newsgroups.py`.
 
+    For an efficiency comparision of the different feature extractors, see
+    :ref:`sphx_glr_auto_examples_text_plot_hashing_vs_dict_vectorizer.py`.
+
     Read more in the :ref:`User Guide <text_feature_extraction>`.
 
     Parameters