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MAINT add support for feature_names_in_#959

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4 changes: 4 additions & 0 deletionsdoc/whats_new/v0.10.rst
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Expand Up@@ -22,6 +22,10 @@ Compatibility
- Add support for automatic parameters validation as in scikit-learn >= 1.2.
:pr:`955` by :user:`Guillaume Lemaitre <glemaitre>`.

- Add support for `feature_names_in_` as well as `get_feature_names_out` for
all samplers.
:pr:`959` by :user:`Guillaume Lemaitre <glemaitre>`.

Deprecation
...........

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14 changes: 13 additions & 1 deletionimblearn/base.py
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Expand Up@@ -8,6 +8,12 @@

import numpy as np
from sklearn.base import BaseEstimator

try:
# scikit-learn >= 1.2
from sklearn.base import OneToOneFeatureMixin
except ImportError:
from sklearn.base import _OneToOneFeatureMixin as OneToOneFeatureMixin
from sklearn.preprocessing import label_binarize
from sklearn.utils.multiclass import check_classification_targets

Expand DownExpand Up@@ -133,7 +139,7 @@ class attribute, which is a dictionary `param_name: list of constraints`. See
)


class BaseSampler(SamplerMixin, _ParamsValidationMixin):
class BaseSampler(SamplerMixin,OneToOneFeatureMixin,_ParamsValidationMixin):
"""Base class for sampling algorithms.

Warning: This class should not be used directly. Use the derive classes
Expand DownExpand Up@@ -260,6 +266,12 @@ class FunctionSampler(BaseSampler):

.. versionadded:: 0.9

feature_names_in_ : ndarray of shape (`n_features_in_`,)
Names of features seen during `fit`. Defined only when `X` has feature
names that are all strings.

.. versionadded:: 0.10

See Also
--------
sklearn.preprocessing.FunctionTransfomer : Stateless transformer.
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6 changes: 6 additions & 0 deletionsimblearn/combine/_smote_enn.py
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Expand Up@@ -67,6 +67,12 @@ class SMOTEENN(BaseSampler):

.. versionadded:: 0.9

feature_names_in_ : ndarray of shape (`n_features_in_`,)
Names of features seen during `fit`. Defined only when `X` has feature
names that are all strings.

.. versionadded:: 0.10

See Also
--------
SMOTETomek : Over-sample using SMOTE followed by under-sampling removing
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6 changes: 6 additions & 0 deletionsimblearn/combine/_smote_tomek.py
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Expand Up@@ -66,6 +66,12 @@ class SMOTETomek(BaseSampler):

.. versionadded:: 0.9

feature_names_in_ : ndarray of shape (`n_features_in_`,)
Names of features seen during `fit`. Defined only when `X` has feature
names that are all strings.

.. versionadded:: 0.10

See Also
--------
SMOTEENN : Over-sample using SMOTE followed by under-sampling using Edited
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11 changes: 11 additions & 0 deletionsimblearn/metrics/pairwise.py
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Expand Up@@ -71,6 +71,17 @@ class ValueDifferenceMetric(BaseEstimator, _ParamsValidationMixin):
List of length `n_features` containing the conditional probabilities
for each category given a class.

n_features_in_ : int
Number of features in the input dataset.

.. versionadded:: 0.10

feature_names_in_ : ndarray of shape (`n_features_in_`,)
Names of features seen during `fit`. Defined only when `X` has feature
names that are all strings.

.. versionadded:: 0.10

See Also
--------
sklearn.neighbors.DistanceMetric : Interface for fast metric computation.
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6 changes: 6 additions & 0 deletionsimblearn/over_sampling/_adasyn.py
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Expand Up@@ -73,6 +73,12 @@ class ADASYN(BaseOverSampler):

.. versionadded:: 0.9

feature_names_in_ : ndarray of shape (`n_features_in_`,)
Names of features seen during `fit`. Defined only when `X` has feature
names that are all strings.

.. versionadded:: 0.10

See Also
--------
SMOTE : Over-sample using SMOTE.
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6 changes: 6 additions & 0 deletionsimblearn/over_sampling/_random_over_sampler.py
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Expand Up@@ -76,6 +76,12 @@ class RandomOverSampler(BaseOverSampler):

.. versionadded:: 0.9

feature_names_in_ : ndarray of shape (`n_features_in_`,)
Names of features seen during `fit`. Defined only when `X` has feature
names that are all strings.

.. versionadded:: 0.10

See Also
--------
BorderlineSMOTE : Over-sample using the borderline-SMOTE variant.
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18 changes: 18 additions & 0 deletionsimblearn/over_sampling/_smote/base.py
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Expand Up@@ -264,6 +264,12 @@ class SMOTE(BaseSMOTE):

.. versionadded:: 0.9

feature_names_in_ : ndarray of shape (`n_features_in_`,)
Names of features seen during `fit`. Defined only when `X` has feature
names that are all strings.

.. versionadded:: 0.10

See Also
--------
SMOTENC : Over-sample using SMOTE for continuous and categorical features.
Expand DownExpand Up@@ -442,6 +448,12 @@ class SMOTENC(SMOTE):

.. versionadded:: 0.9

feature_names_in_ : ndarray of shape (`n_features_in_`,)
Names of features seen during `fit`. Defined only when `X` has feature
names that are all strings.

.. versionadded:: 0.10

See Also
--------
SMOTE : Over-sample using SMOTE.
Expand DownExpand Up@@ -759,6 +771,12 @@ class SMOTEN(SMOTE):

.. versionadded:: 0.9

feature_names_in_ : ndarray of shape (`n_features_in_`,)
Names of features seen during `fit`. Defined only when `X` has feature
names that are all strings.

.. versionadded:: 0.10

See Also
--------
SMOTE : Over-sample using SMOTE.
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6 changes: 6 additions & 0 deletionsimblearn/over_sampling/_smote/cluster.py
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Expand Up@@ -93,6 +93,12 @@ class KMeansSMOTE(BaseSMOTE):

.. versionadded:: 0.9

feature_names_in_ : ndarray of shape (`n_features_in_`,)
Names of features seen during `fit`. Defined only when `X` has feature
names that are all strings.

.. versionadded:: 0.10

See Also
--------
SMOTE : Over-sample using SMOTE.
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12 changes: 12 additions & 0 deletionsimblearn/over_sampling/_smote/filter.py
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Expand Up@@ -100,6 +100,12 @@ class BorderlineSMOTE(BaseSMOTE):

.. versionadded:: 0.9

feature_names_in_ : ndarray of shape (`n_features_in_`,)
Names of features seen during `fit`. Defined only when `X` has feature
names that are all strings.

.. versionadded:: 0.10

See Also
--------
SMOTE : Over-sample using SMOTE.
Expand DownExpand Up@@ -352,6 +358,12 @@ class SVMSMOTE(BaseSMOTE):

.. versionadded:: 0.9

feature_names_in_ : ndarray of shape (`n_features_in_`,)
Names of features seen during `fit`. Defined only when `X` has feature
names that are all strings.

.. versionadded:: 0.10

See Also
--------
SMOTE : Over-sample using SMOTE.
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16 changes: 16 additions & 0 deletionsimblearn/tests/test_common.py
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Expand Up@@ -3,6 +3,7 @@
# Christos Aridas
# License: MIT

import warnings
from collections import OrderedDict

import numpy as np
Expand All@@ -19,6 +20,7 @@
from imblearn.under_sampling import NearMiss, RandomUnderSampler
from imblearn.utils.estimator_checks import (
_set_checking_parameters,
check_dataframe_column_names_consistency,
check_param_validation,
parametrize_with_checks,
)
Expand DownExpand Up@@ -92,3 +94,17 @@ def test_strategy_as_ordered_dict(Sampler):
X_res, y_res = sampler.fit_resample(X, y)
assert X_res.shape[0] == sum(strategy.values())
assert y_res.shape[0] == sum(strategy.values())


@pytest.mark.parametrize(
"estimator", _tested_estimators(), ids=_get_check_estimator_ids
)
def test_pandas_column_name_consistency(estimator):
_set_checking_parameters(estimator)
with ignore_warnings(category=(FutureWarning)):
with warnings.catch_warnings(record=True) as record:
check_dataframe_column_names_consistency(
estimator.__class__.__name__, estimator
)
for warning in record:
assert "was fitted without feature names" not in str(warning.message)
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Expand Up@@ -78,6 +78,12 @@ class ClusterCentroids(BaseUnderSampler):

.. versionadded:: 0.9

feature_names_in_ : ndarray of shape (`n_features_in_`,)
Names of features seen during `fit`. Defined only when `X` has feature
names that are all strings.

.. versionadded:: 0.10

See Also
--------
EditedNearestNeighbours : Under-sampling by editing samples.
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Expand Up@@ -69,6 +69,12 @@ class CondensedNearestNeighbour(BaseCleaningSampler):

.. versionadded:: 0.9

feature_names_in_ : ndarray of shape (`n_features_in_`,)
Names of features seen during `fit`. Defined only when `X` has feature
names that are all strings.

.. versionadded:: 0.10

See Also
--------
EditedNearestNeighbours : Undersample by editing samples.
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Expand Up@@ -76,6 +76,12 @@ class EditedNearestNeighbours(BaseCleaningSampler):

.. versionadded:: 0.9

feature_names_in_ : ndarray of shape (`n_features_in_`,)
Names of features seen during `fit`. Defined only when `X` has feature
names that are all strings.

.. versionadded:: 0.10

See Also
--------
CondensedNearestNeighbour : Undersample by condensing samples.
Expand DownExpand Up@@ -251,6 +257,12 @@ class RepeatedEditedNearestNeighbours(BaseCleaningSampler):

.. versionadded:: 0.9

feature_names_in_ : ndarray of shape (`n_features_in_`,)
Names of features seen during `fit`. Defined only when `X` has feature
names that are all strings.

.. versionadded:: 0.10

See Also
--------
CondensedNearestNeighbour : Undersample by condensing samples.
Expand DownExpand Up@@ -454,6 +466,12 @@ class without early stopping.

.. versionadded:: 0.9

feature_names_in_ : ndarray of shape (`n_features_in_`,)
Names of features seen during `fit`. Defined only when `X` has feature
names that are all strings.

.. versionadded:: 0.10

See Also
--------
CondensedNearestNeighbour: Under-sampling by condensing samples.
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Expand Up@@ -67,6 +67,12 @@ class InstanceHardnessThreshold(BaseUnderSampler):

.. versionadded:: 0.9

feature_names_in_ : ndarray of shape (`n_features_in_`,)
Names of features seen during `fit`. Defined only when `X` has feature
names that are all strings.

.. versionadded:: 0.10

See Also
--------
NearMiss : Undersample based on near-miss search.
Expand Down
6 changes: 6 additions & 0 deletionsimblearn/under_sampling/_prototype_selection/_nearmiss.py
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Expand Up@@ -72,6 +72,12 @@ class NearMiss(BaseUnderSampler):

.. versionadded:: 0.9

feature_names_in_ : ndarray of shape (`n_features_in_`,)
Names of features seen during `fit`. Defined only when `X` has feature
names that are all strings.

.. versionadded:: 0.10

See Also
--------
RandomUnderSampler : Random undersample the dataset.
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Expand Up@@ -83,6 +83,12 @@ class NeighbourhoodCleaningRule(BaseCleaningSampler):

.. versionadded:: 0.9

feature_names_in_ : ndarray of shape (`n_features_in_`,)
Names of features seen during `fit`. Defined only when `X` has feature
names that are all strings.

.. versionadded:: 0.10

See Also
--------
EditedNearestNeighbours : Undersample by editing noisy samples.
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Expand Up@@ -68,6 +68,12 @@ class OneSidedSelection(BaseCleaningSampler):

.. versionadded:: 0.9

feature_names_in_ : ndarray of shape (`n_features_in_`,)
Names of features seen during `fit`. Defined only when `X` has feature
names that are all strings.

.. versionadded:: 0.10

See Also
--------
EditedNearestNeighbours : Undersample by editing noisy samples.
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Expand Up@@ -50,6 +50,12 @@ class RandomUnderSampler(BaseUnderSampler):

.. versionadded:: 0.9

feature_names_in_ : ndarray of shape (`n_features_in_`,)
Names of features seen during `fit`. Defined only when `X` has feature
names that are all strings.

.. versionadded:: 0.10

See Also
--------
NearMiss : Undersample using near-miss samples.
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Expand Up@@ -48,6 +48,12 @@ class TomekLinks(BaseCleaningSampler):

.. versionadded:: 0.9

feature_names_in_ : ndarray of shape (`n_features_in_`,)
Names of features seen during `fit`. Defined only when `X` has feature
names that are all strings.

.. versionadded:: 0.10

See Also
--------
EditedNearestNeighbours : Undersample by samples edition.
Expand Down
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