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