I have a python error for numpy implementation for a shapley value model

Question

I want to insert this code into my python

import random
import warnings
import numpy as np
from sklearn.datasets import load_breast_cancer
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
from sklearn.linear_model import LogisticRegression
from sklearn.pipeline import make_pipeline

warnings.filterwarnings("ignore")

And the error is:

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-8-6c2b9bf4cfd2> in <module>
      2 import warnings
      3 import numpy as np
----> 4 from sklearn.datasets import load_breast_cancer
      5 from sklearn.model_selection import train_test_split
      6 from sklearn.preprocessing import StandardScaler

~/opt/anaconda3/lib/python3.8/site-packages/sklearn/datasets/__init__.py in <module>
     20 from ._lfw import fetch_lfw_pairs
     21 from ._lfw import fetch_lfw_people
---> 22 from ._twenty_newsgroups import fetch_20newsgroups
     23 from ._twenty_newsgroups import fetch_20newsgroups_vectorized
     24 from ._openml import fetch_openml

~/opt/anaconda3/lib/python3.8/site-packages/sklearn/datasets/_twenty_newsgroups.py in <module>
     43 from ._base import _fetch_remote
     44 from ._base import RemoteFileMetadata
---> 45 from ..feature_extraction.text import CountVectorizer
     46 from .. import preprocessing
     47 from ..utils import check_random_state, Bunch

~/opt/anaconda3/lib/python3.8/site-packages/sklearn/feature_extraction/__init__.py in <module>
      7 from ._dict_vectorizer import DictVectorizer
      8 from ._hash import FeatureHasher
----> 9 from .image import img_to_graph, grid_to_graph
     10 from . import text
     11 

~/opt/anaconda3/lib/python3.8/site-packages/sklearn/feature_extraction/image.py in <module>
    170 @_deprecate_positional_args
    171 def grid_to_graph(n_x, n_y, n_z=1, *, mask=None, return_as=sparse.coo_matrix,
--> 172                   dtype=np.int):
    173     """Graph of the pixel-to-pixel connections
    174 

~/opt/anaconda3/lib/python3.8/site-packages/numpy/__init__.py in __getattr__(attr)
    303 
    304         if attr in __former_attrs__:
--> 305             raise AttributeError(__former_attrs__[attr])
    306 
    307         # Importing Tester requires importing all of UnitTest which is not a

AttributeError: module 'numpy' has no attribute 'int'.
`np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:
    https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations

I have installed numpy new as it looks like there is a problem as I understood with all these "int" within numpy.

but it doesnt resolve the problem it is still the same problem.

Does anybody has a idea how i can resolve this problem? Or maybe somebody has experience with the same problem for shapley value models.

Answer 1

Your sklearn and numpy versions are incompatible (see error message all the way at the bottom). A quick fix would be to downgrade numpy to 1.19.5.

pip install --force-reinstall numpy==1.19.5

Better would be to upgrade both packages as suggested in this question, as Python 3.8 is still activately supported.

pip install scikit-learn numpy --upgrade