StandardScaler is stateless
#30840
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Hello @benHeid, thanks for reporting. I have checked and would also think it is a bug. This code returned from sklearn.preprocessing import StandardScaler, MinMaxScaler
print(StandardScaler()._get_tags()["stateless"])
print(MinMaxScaler()._get_tags()["stateless"])As a workaround please use the The issue is related to #30327. |
Actually it is the right way to do with the new tag infrastructure from sklearn.utils import get_tags
from sklearn.preprocessing import StandardScaler
get_tags(StandardScaler()).requires_fitAnd indeed, there is a bug with the conversion if the old tag infrastructure that we need to solve. |
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So the bug is here: https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/utils/_tags.py#L590 We should change to: "stateless": not new_tags.requires_fit, |
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@EmilyXinyi, would you like to take care of that? Don't feel obliged though, only if you like. |
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Describe the bug
The StandardScaler seems to be stateless in version 1.6.1. But fit changes the state of the StandardScaler if I got it correctly.
Steps/Code to Reproduce
Expected Results
False
Actual Results
True
Versions
System: python: 3.10.14 (main, Jul 18 2024, 22:40:44) [Clang 15.0.0 (clang-1500.1.0.2.5)] executable: ****/python machine: macOS-15.2-arm64-arm-64bit Python dependencies: sklearn: 1.6.1 pip: 24.1.2 setuptools: 71.0.3 numpy: 1.26.4 scipy: 1.13.1 Cython: 3.0.11 pandas: 2.2.3 matplotlib: 3.9.2 joblib: 1.4.2 threadpoolctl: 3.5.0 Built with OpenMP: True threadpoolctl info: user_api: blas internal_api: openblas num_threads: 8 prefix: libopenblas filepath: ****.dylib version: 0.3.23.dev threading_layer: pthreads architecture: armv8 user_api: blas internal_api: openblas num_threads: 8 prefix: libopenblas filepath: ***** version: 0.3.27 threading_layer: pthreads architecture: neoversen1 user_api: openmp internal_api: openmp num_threads: 8 prefix: libomp filepath: ***** version: NoneThe text was updated successfully, but these errors were encountered: