diff --git a/sklearn/mixture/dpgmm.py b/sklearn/mixture/dpgmm.py
index e0db5e568f013..700b63fdad31e 100644
--- a/sklearn/mixture/dpgmm.py
+++ b/sklearn/mixture/dpgmm.py
@@ -116,10 +116,7 @@ def _bound_state_log_lik(X, initial_bound, precs, means, covariance_type):
     return bound
 
 
-@deprecated("The DPGMM class is not working correctly and it's better "
-            "to not use it. DPGMM is deprecated in 0.18 and "
-            "will be removed in 0.20.")
-class DPGMM(_GMMBase):
+class _DPGMMBase(_GMMBase):
     """Variational Inference for the Infinite Gaussian Mixture Model.
 
     DPGMM stands for Dirichlet Process Gaussian Mixture Model, and it
@@ -211,16 +208,16 @@ class DPGMM(_GMMBase):
         algorithm, better for situations where there might be too little
         data to get a good estimate of the covariance matrix.
     """
-
     def __init__(self, n_components=1, covariance_type='diag', alpha=1.0,
                  random_state=None, tol=1e-3, verbose=0, min_covar=None,
                  n_iter=10, params='wmc', init_params='wmc'):
         self.alpha = alpha
-        super(DPGMM, self).__init__(n_components, covariance_type,
-                                    random_state=random_state,
-                                    tol=tol, min_covar=min_covar,
-                                    n_iter=n_iter, params=params,
-                                    init_params=init_params, verbose=verbose)
+        super(_DPGMMBase, self).__init__(n_components, covariance_type,
+                                         random_state=random_state,
+                                         tol=tol, min_covar=min_covar,
+                                         n_iter=n_iter, params=params,
+                                         init_params=init_params,
+                                         verbose=verbose)
 
     def _get_precisions(self):
         """Return precisions as a full matrix."""
@@ -619,10 +616,24 @@ def _fit(self, X, y=None):
         return z
 
 
-@deprecated("The VBGMM class is not working correctly and it's better"
-            " to not use it. VBGMM is deprecated in 0.18 and "
+@deprecated("The DPGMM class is not working correctly and it's better "
+            "to not use it. DPGMM is deprecated in 0.18 and "
+            "will be removed in 0.20.")
+class DPGMM(_DPGMMBase):
+    def __init__(self, n_components=1, covariance_type='diag', alpha=1.0,
+                 random_state=None, tol=1e-3, verbose=0, min_covar=None,
+                 n_iter=10, params='wmc', init_params='wmc'):
+        super(DPGMM, self).__init__(
+            n_components=n_components, covariance_type=covariance_type,
+            alpha=alpha, random_state=random_state, tol=tol, verbose=verbose,
+            min_covar=min_covar, n_iter=n_iter, params=params,
+            init_params=init_params)
+
+
+@deprecated("The VBGMM class is not working correctly and it's better "
+            "to not use it. VBGMM is deprecated in 0.18 and "
             "will be removed in 0.20.")
-class VBGMM(DPGMM):
+class VBGMM(_DPGMMBase):
     """Variational Inference for the Gaussian Mixture Model
 
     Variational inference for a Gaussian mixture model probability
diff --git a/sklearn/mixture/tests/test_dpgmm.py b/sklearn/mixture/tests/test_dpgmm.py
index 88a67170f8268..c636403db7672 100644
--- a/sklearn/mixture/tests/test_dpgmm.py
+++ b/sklearn/mixture/tests/test_dpgmm.py
@@ -182,12 +182,11 @@ class TestDPGMMWithFullCovars(unittest.TestCase, DPGMMTester):
     setUp = GMMTester._setUp
 
 
-@ignore_warnings(category=DeprecationWarning)
 def test_VBGMM_deprecation():
-    assert_warns_message(DeprecationWarning, "The VBGMM class is"
-                         " not working correctly and it's better"
-                         " to not use it. VBGMM is deprecated in 0.18"
-                         " and will be removed in 0.20.", VBGMM)
+    assert_warns_message(
+        DeprecationWarning,
+        "The VBGMM class is not working correctly and it's better to not use "
+        "it. VBGMM is deprecated in 0.18 and will be removed in 0.20.", VBGMM)
 
 
 class VBGMMTester(GMMTester):
diff --git a/sklearn/mixture/tests/test_gmm.py b/sklearn/mixture/tests/test_gmm.py
index f6765d18b4dbb..500e11117a5a1 100644
--- a/sklearn/mixture/tests/test_gmm.py
+++ b/sklearn/mixture/tests/test_gmm.py
@@ -309,7 +309,7 @@ def test_train_1d(self, params='wmc'):
         with ignore_warnings(category=DeprecationWarning):
             g.fit(X)
             trainll = g.score(X)
-            if isinstance(g, mixture.DPGMM):
+            if isinstance(g, mixture.dpgmm._DPGMMBase):
                 self.assertTrue(np.sum(np.abs(trainll / 100)) < 5)
             else:
                 self.assertTrue(np.sum(np.abs(trainll / 100)) < 2)