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‎imblearn/base.py

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# Christos Aridas
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# License: MIT
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from __future__ import division
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import warnings
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from abc import ABCMeta, abstractmethod
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‎imblearn/combine/_smote_enn.py

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# Christos Aridas
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# License: MIT
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from __future__ import division
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from sklearn.base import clone
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from sklearn.utils import check_X_y
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‎imblearn/combine/_smote_tomek.py

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# Christos Aridas
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# License: MIT
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from __future__ import division
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from sklearn.base import clone
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from sklearn.utils import check_X_y
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‎imblearn/metrics/_classification.py

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# Dariusz Brzezinski
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# License: MIT
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from __future__ import division
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import warnings
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import functools
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‎imblearn/metrics/tests/test_classification.py

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# Christos Aridas
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# License: MIT
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from __future__ import division
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from functools import partial
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import numpy as np

‎imblearn/over_sampling/_adasyn.py

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# Christos Aridas
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# License: MIT
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from __future__ import division
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import numpy as np
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from scipy import sparse
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‎imblearn/over_sampling/_random_over_sampler.py

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# Authors: Guillaume Lemaitre <g.lemaitre58@gmail.com>
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# Christos Aridas
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# License: MIT
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from __future__ import division
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from collections import Counter
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‎imblearn/over_sampling/_smote.py

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# Dzianis Dudnik
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# License: MIT
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from __future__ import division
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import math
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import types
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import warnings
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if self.kmeans_estimator_.n_clusters != 1 else -np.inf
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)
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def _find_cluster_sparsity(self, X):
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"""Compute the cluster sparsity."""
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euclidean_distances = pairwise_distances(X, metric="euclidean",

‎imblearn/pipeline.py

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# Guillaume Lemaitre <g.lemaitre58@gmail.com>
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# License: BSD
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from __future__ import division
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from collections import defaultdict
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from itertools import islice
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‎imblearn/tensorflow/_generator.py

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"""Implement generators for ``tensorflow`` which will balance the data."""
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from __future__ import division
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from scipy.sparse import issparse
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from sklearn.base import clone

‎imblearn/tensorflow/tests/test_generator.py

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from __future__ import division
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import pytest
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import numpy as np
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from scipy import sparse

‎imblearn/under_sampling/_prototype_generation/_cluster_centroids.py

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# Christos Aridas
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# License: MIT
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from __future__ import division
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import numpy as np
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from scipy import sparse
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‎imblearn/under_sampling/_prototype_selection/_condensed_nearest_neighbour.py

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# Christos Aridas
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# License: MIT
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from __future__ import division
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from collections import Counter
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import numpy as np

‎imblearn/under_sampling/_prototype_selection/_edited_nearest_neighbours.py

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# Christos Aridas
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# License: MIT
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from __future__ import division
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from collections import Counter
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import numpy as np

‎imblearn/under_sampling/_prototype_selection/_instance_hardness_threshold.py

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# Christos Aridas
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# License: MIT
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from __future__ import division
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from collections import Counter
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import numpy as np

‎imblearn/under_sampling/_prototype_selection/_nearmiss.py

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# Christos Aridas
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# License: MIT
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from __future__ import division
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import warnings
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from collections import Counter
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‎imblearn/under_sampling/_prototype_selection/_neighbourhood_cleaning_rule.py

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# Christos Aridas
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# License: MIT
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from __future__ import division
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from collections import Counter
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import numpy as np

‎imblearn/under_sampling/_prototype_selection/_one_sided_selection.py

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# Christos Aridas
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# License: MIT
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from __future__ import division
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from collections import Counter
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import numpy as np

‎imblearn/under_sampling/_prototype_selection/_random_under_sampler.py

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# Christos Aridas
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# License: MIT
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from __future__ import division
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import numpy as np
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from sklearn.utils import check_array

‎imblearn/under_sampling/_prototype_selection/_tomek_links.py

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# Christos Aridas
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# License: MIT
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from __future__ import division
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import numpy as np
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from sklearn.neighbors import NearestNeighbors
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from sklearn.utils import safe_indexing

‎imblearn/utils/_validation.py

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# Authors: Guillaume Lemaitre <g.lemaitre58@gmail.com>
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# License: MIT
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from __future__ import division
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import warnings
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from collections import OrderedDict

‎imblearn/utils/estimator_checks.py

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# Authors: Guillaume Lemaitre <g.lemaitre58@gmail.com>
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# License: MIT
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from __future__ import division
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import sys
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import traceback
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