diff --git a/imblearn/over_sampling/_smote/geometric.py b/imblearn/over_sampling/_smote/geometric.py
index 66e52d1a1..2e7f3ca45 100644
--- a/imblearn/over_sampling/_smote/geometric.py
+++ b/imblearn/over_sampling/_smote/geometric.py
@@ -89,12 +89,9 @@ def _make_geometric_sample(
     random_state=_random_state_docstring,
 )
 class GeometricSMOTE(BaseOverSampler):
-    """Class to to perform over-sampling using Geometric SMOTE.
-
-    This algorithm is an implementation of Geometric SMOTE, a geometrically
-    enhanced drop-in replacement for SMOTE as presented in [1]_.
-
-    Read more in the :ref:`User Guide <user_guide>`.
+    """Class to to perform over-sampling using Geometric SMOTE. This algorithm is an
+    implementation of Geometric SMOTE, a geometrically enhanced drop-in replacement
+    for SMOTE as presented in [1]_. Read more in the :ref:`User Guide <user_guide>`.
 
     Parameters
     ----------
@@ -123,7 +120,6 @@ class GeometricSMOTE(BaseOverSampler):
 
     Attributes
     ----------
-
     sampling_strategy_ : dict
         Dictionary containing the information to sample the dataset. The keys
         corresponds to the class labels from which to sample and the values
@@ -157,7 +153,6 @@ class GeometricSMOTE(BaseOverSampler):
 
     References
     ----------
-
     .. [1] G. Douzas, F. Bacao, "Geometric SMOTE:
        a geometrically enhanced drop-in replacement for SMOTE",
        Information Sciences, vol. 501, pp. 118-135, 2019.
@@ -168,7 +163,6 @@ class GeometricSMOTE(BaseOverSampler):
 
     Examples
     --------
-
     >>> from collections import Counter
     >>> from sklearn.datasets import make_classification
     >>> from imblearn.over_sampling import \
@@ -182,7 +176,6 @@ class GeometricSMOTE(BaseOverSampler):
     >>> X_res, y_res = gsmote.fit_resample(X, y)
     >>> print('Resampled dataset shape %s' % Counter(y_res))
     Resampled dataset shape Counter({{0: 900, 1: 900}})
-
     """
 
     def __init__(