diff --git a/bob/learn/em/gmm.py b/bob/learn/em/gmm.py
index 1a439e142cc16eed28993f10c5db16c0a2ff3084..d9ae87b4111e9bac008a95ee8d8869d003242fc8 100644
--- a/bob/learn/em/gmm.py
+++ b/bob/learn/em/gmm.py
@@ -183,7 +183,9 @@ class GMMStats:
         Second order statistic
     """
 
-    def __init__(self, n_gaussians: int, n_features: int) -> None:
+    def __init__(self, n_gaussians: int, n_features: int, **kwargs) -> None:
+        super().__init__(**kwargs)
+
         self.n_gaussians = n_gaussians
         self.n_features = n_features
         self.log_likelihood = 0
diff --git a/bob/learn/em/kmeans.py b/bob/learn/em/kmeans.py
index 61af76ec9a54dce65c43d7439ecbbb8a78b61031..6cd29e4cf33de36a7792702cf383a5fb2c62666c 100644
--- a/bob/learn/em/kmeans.py
+++ b/bob/learn/em/kmeans.py
@@ -202,6 +202,7 @@ class KMeansMachine(BaseEstimator):
         random_state: Union[int, np.random.RandomState] = 0,
         init_max_iter: Union[int, None] = 5,
         oversampling_factor: float = 2,
+        **kwargs,
     ) -> None:
         """
         Parameters
@@ -219,6 +220,8 @@ class KMeansMachine(BaseEstimator):
             The maximum number of iterations for the initialization part.
         """
 
+        super().__init__(**kwargs)
+
         if n_clusters < 1:
             raise ValueError("The Number of cluster should be greater thant 0.")
         self.n_clusters = n_clusters
diff --git a/bob/learn/em/wccn.py b/bob/learn/em/wccn.py
index 47d5b80463ebb74e0c1e7f8b8dccc1f52ed31529..32a4e80788c135a5b5a8c5c07d3c5fc1abc59eaf 100644
--- a/bob/learn/em/wccn.py
+++ b/bob/learn/em/wccn.py
@@ -34,7 +34,8 @@ class WCCN(TransformerMixin, BaseEstimator):
 
     """
 
-    def __init__(self, pinv=False):
+    def __init__(self, pinv=False, **kwargs):
+        super().__init__(**kwargs)
         self.pinv = pinv
 
     def fit(self, X, y):
diff --git a/bob/learn/em/whitening.py b/bob/learn/em/whitening.py
index bf81a36203580120e2d3f90664bed38401809d58..4b78da8dbd3c3a2fa75bade6a31dd4d11c535938 100644
--- a/bob/learn/em/whitening.py
+++ b/bob/learn/em/whitening.py
@@ -41,7 +41,8 @@ class Whitening(TransformerMixin, BaseEstimator):
 
     """
 
-    def __init__(self, pinv: bool = False):
+    def __init__(self, pinv: bool = False, **kwargs):
+        super().__init__(**kwargs)
         self.pinv = pinv
 
     def fit(self, X, y=None):