scikit-learn
diff --git a/‎doc/whats_new.rst‎
Lines changed: 5 additions & 0 deletions b/‎doc/whats_new.rst‎
Lines changed: 5 additions & 0 deletions
diff --git a/‎sklearn/pipeline.py‎
Lines changed: 9 additions & 1 deletion b/‎sklearn/pipeline.py‎
Lines changed: 9 additions & 1 deletion
@@ -54,6 +54,11 @@ Miscellaneous
   :class:`pipeline.FeatureUnion` for showing progress and timing of each
      step. :issue:`8568` by :user:`Karan Desai <karandesai-96>`.
 
+- Added optional parameter ``verbose`` in functions `pipeline.make_pipeline`
+  and `pipeline.make_union` to extend the same functionality as the
+  corresponding classes. :issue:`9668` by
+  :user:`Baze Petrushev <petrushev>`.
+
 
 Bug fixes
 .........
 
@@ -601,6 +601,9 @@ def make_pipeline(*steps, **kwargs):
         inspect estimators within the pipeline. Caching the
         transformers is advantageous when fitting is time consuming.
 
+    verbose : boolean, optional
+        Verbosity mode.
+
     Examples
     --------
     >>> from sklearn.naive_bayes import GaussianNB
@@ -896,6 +899,9 @@ def make_union(*transformers, **kwargs):
     n_jobs : int, optional
         Number of jobs to run in parallel (default 1).
 
+    verbose : boolean, optional
+         Verbosity mode.
+
     Returns
     -------
     f : FeatureUnion
@@ -917,9 +923,11 @@ def make_union(*transformers, **kwargs):
            transformer_weights=None, verbose=False)
     """
     n_jobs = kwargs.pop('n_jobs', 1)
+    verbose = kwargs.pop('verbose', False)
     if kwargs:
         # We do not currently support `transformer_weights` as we may want to
         # change its type spec in make_union
         raise TypeError('Unknown keyword arguments: "{}"'
                         .format(list(kwargs.keys())[0]))
-    return FeatureUnion(_name_estimators(transformers), n_jobs=n_jobs)
+    return FeatureUnion(_name_estimators(transformers), n_jobs=n_jobs,
+                        verbose=verbose)