nilslacroix

Sorry the parameter is in the preprocessor pipeline.

Also if you call this preprocessor with a gridsearch and even when preprocessor stays at n_jobs=1, the same error appears. So it my guess is that when multiple fits are...

System: python: 3.10.4 | packaged by conda-forge | (main, Mar 24 2022, 17:38:57) [GCC 10.3.0] executable: /home/xxxxx/anaconda3/envs/MASTER/bin/python machine: Linux-4.15.0-154-generic-x86_64-with-glibc2.27 Python dependencies: sklearn: 1.2.dev0 pip: 22.0.4 setuptools: 62.1.0 numpy: 1.22.3 scipy:...

This maybe explains why the warnings can not be turned off, with `filter.warnings ` when the setting only applies to the main thread/process, but the problem is caused by some...

But then this code would trigger the warning as well: ``` pt = PowerTransformer(method="yeo-johnson") pt.fit(pd.DataFrame(X_train["YearModernization"])) ``` which it does not. Or am I wrong?

> Can someone craft a minimal reproducer with a single column dataset, possibly syntactically generated? Here is a minimal reproducer, but you have to use this dataset: [dataset.zip](https://github.com/scikit-learn/scikit-learn/files/8662083/dataset.zip) ``` from...

sklearnex.svm.SVR is also buggy. Using .predict() on the same X_test set in a pipeline with preprocessors and encoders yiels different predictions. Just do it like ~50 times in a row...

I confirmed this bug happens (at least the scoring) when using AMD Hardware. Please at least implement a warning message, which checks the current CPU so people get a notice...

I thought so too, but when I use the parameters above I get an error because the matrice is too big, and the given sice is exactly what I describe....

For `X_test = 149689` and `X_train = 152363` during the prediction I got this error. As you can see method is plus and cv=5 for a standard default lgbm regressor....