@@ -89,12 +89,9 @@ def _make_geometric_sample(
8989 random_state = _random_state_docstring ,
9090)
9191class GeometricSMOTE (BaseOverSampler ):
92- """Class to to perform over-sampling using Geometric SMOTE.
93-
94- This algorithm is an implementation of Geometric SMOTE, a geometrically
95- enhanced drop-in replacement for SMOTE as presented in [1]_.
96-
97- Read more in the :ref:`User Guide <user_guide>`.
92+ """Class to to perform over-sampling using Geometric SMOTE. This algorithm is an
93+ implementation of Geometric SMOTE, a geometrically enhanced drop-in replacement
94+ for SMOTE as presented in [1]_. Read more in the :ref:`User Guide <user_guide>`.
9895
9996 Parameters
10097 ----------
@@ -123,7 +120,6 @@ class GeometricSMOTE(BaseOverSampler):
123120
124121 Attributes
125122 ----------
126-
127123 sampling_strategy_ : dict
128124 Dictionary containing the information to sample the dataset. The keys
129125 corresponds to the class labels from which to sample and the values
@@ -157,7 +153,6 @@ class GeometricSMOTE(BaseOverSampler):
157153
158154 References
159155 ----------
160-
161156 .. [1] G. Douzas, F. Bacao, "Geometric SMOTE:
162157 a geometrically enhanced drop-in replacement for SMOTE",
163158 Information Sciences, vol. 501, pp. 118-135, 2019.
@@ -168,7 +163,6 @@ class GeometricSMOTE(BaseOverSampler):
168163
169164 Examples
170165 --------
171-
172166 >>> from collections import Counter
173167 >>> from sklearn.datasets import make_classification
174168 >>> from imblearn.over_sampling import \
@@ -182,7 +176,6 @@ class GeometricSMOTE(BaseOverSampler):
182176 >>> X_res, y_res = gsmote.fit_resample(X, y)
183177 >>> print('Resampled dataset shape %s' % Counter(y_res))
184178 Resampled dataset shape Counter({{0: 900, 1: 900}})
185-
186179 """
187180
188181 def __init__ (
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