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While importing "from imblearn.over_sampling import SMOTE", getting import error. Please check and help. I tried upgrading sklearn, but the upgrade was undone with 'OSError'. Firsty installed imbalance-learn through pip.

!pip install -U imbalanced-learn

  • Using jupyter notebook

  • Windows 10

  • sklearn version - 0.24.1

  • numpy version - 1.19.5

     --------------------------------------------------------------------------
 ImportError                               Traceback (most recent call last)

    in ----> 1 from imblearn.over_sampling import SMOTE

    ~\anaconda3\lib\site-packages\imblearn_init_.py in 35 import types 36 ---> 37 from . import combine 38 from . import ensemble 39 from . import exceptions

    ~\anaconda3\lib\site-packages\imblearn\combine_init_.py in 3 """ 4 ----> 5 from ._smote_enn import SMOTEENN 6 from ._smote_tomek import SMOTETomek 7

    ~\anaconda3\lib\site-packages\imblearn\combine_smote_enn.py in 8 from sklearn.utils import check_X_y 9 ---> 10 from ..base import BaseSampler 11 from ..over_sampling import SMOTE 12 from ..over_sampling.base import BaseOverSampler

    ~\anaconda3\lib\site-packages\imblearn\base.py in 13 from sklearn.utils.multiclass import check_classification_targets 14 ---> 15 from .utils import check_sampling_strategy, check_target_type 16 from .utils._validation import ArraysTransformer 17 from .utils._validation import _deprecate_positional_args

    ~\anaconda3\lib\site-packages\imblearn\utils_init_.py in 5 from ._docstring import Substitution 6 ----> 7 from ._validation import check_neighbors_object 8 from ._validation import check_target_type 9 from ._validation import check_sampling_strategy

    ~\anaconda3\lib\site-packages\imblearn\utils_validation.py in 14 from sklearn.base import clone 15 from sklearn.neighbors._base import KNeighborsMixin ---> 16 from sklearn.neighbors import NearestNeighbors 17 from sklearn.utils import column_or_1d 18 from sklearn.utils.multiclass import type_of_target

    ~\anaconda3\lib\site-packages\sklearn\neighbors_init_.py in 14 from ._nearest_centroid import NearestCentroid 15 from ._kde import KernelDensity ---> 16 from ._lof import LocalOutlierFactor 17 from ._nca import NeighborhoodComponentsAnalysis 18 from ._base import VALID_METRICS, VALID_METRICS_SPARSE

    ~\anaconda3\lib\site-packages\sklearn\neighbors_lof.py in 10 from ..base import OutlierMixin 11 ---> 12 from ..utils.metaestimators import available_if 13 from ..utils.validation import check_is_fitted 14 from ..utils import check_array

    ImportError: cannot import name 'available_if' from 'sklearn.utils.metaestimators' (C:\Users\dks_m\anaconda3\lib\site-packages\sklearn\utils\metaestimators.py)

ouflak
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Piyush
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7 Answers7

8

IF in jupyter , restart the kernel.This fixed!

manjunath
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I believe the issue is with python versioning of scikit-learn. I was able to resolve by reinstalling the Python3 version:

pip uninstall scikit-learn -y

pip3 install scikit-learn

Remember to restart terminal/notebook after package updates.

This gives me scikit-learn v1.0.2 which resolves error in Python3

Adam
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Try using anaconda prompt for installation. It works for me.

Piyush
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  • Your answer could be improved with additional supporting information. Please [edit] to add further details, such as citations or documentation, so that others can confirm that your answer is correct. You can find more information on how to write good answers [in the help center](/help/how-to-answer). – Community Oct 17 '21 at 13:24
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That usually happens when 2 different versions of packages do not match. If you are using the jupyter notebook, restarting your environment is going to solve your issue.

Elvin Aghammadzada
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Good day all. What helped me is installing pycaret=='2.3.10 ' and scikit-learn='0.23.2' at the same time. These two version are compatible and all works fine. I installed scikit-learn using conda as the older versions are not available through pip, and I installed Pycaret using pip3. I hope this helps all who have struggled to get this working like I did.

KYS
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If using databricks : Go-to: view -> view spark ui -> Libraries -> install new -> Library Source -> PyPi -> add package name : imbalanced-learn -> install -> Restart the cluster

// Do not install from active notebook using cli command.

MSS
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Downgrading the sklearn did the job for me

pip install scikit-learn==1.2.0
Ajay Pyatha
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