Talip7/scikit-learn-issues-multilabel huggingface dataset:
Verbosity option is not working in GridSearchCV (Jupyter notebook)

### Describe the bug

So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) response.

The problem is that GridSearchCV doesn't show the elapsed time periodically, or any log, I am set`n_jobs = -1`, and `verbose = 1`. I tried setting `n_jobs` to other values, the same with `verbose`, but nothing happened.
Note that this didn't happen until I updated scikit-learn from version 0.22.1 to 1.0.2.

[lesteve](https://github.com/lesteve) in his response assumed that this problem is due to `ipykernel <6`, which is not the case with me.

### Steps/Code to Reproduce

```
from sklearn.model_selection import GridSearchCV
from sklearn.ensemble import RandomForestClassifier
from sklearn import datasets

iris = datasets.load_iris()
params = {'n_estimators':[10,20,30,40,50,60],
          'max_depth':[20,50,60,70,80]}
grid_obj = GridSearchCV(estimator=RandomForestClassifier(), param_grid=params, n_jobs=-1, verbose=1, cv=5)
grid_obj.fit(iris.data, iris.target)
```

### Expected Results

This is the output when using version 0.22.1
![image](https://user-images.githubusercontent.com/17684093/158401635-31755363-2108-41e7-8f7f-08985abd03b8.png)


### Actual Results

```Fitting 5 folds for each of 30 candidates, totalling 150 fits```

### Versions

```shell
System:
    python: 3.8.5 (default, Sep  3 2020, 21:29:08) [MSC v.1916 64 bit (AMD64)]
executable: D:\Programs\ApplicationsSetup\anaconda3\python.exe
   machine: Windows-10-10.0.19041-SP0

Python dependencies:
          pip: 21.2.2
   setuptools: 58.0.4
      sklearn: 1.0.2
        numpy: 1.19.2
        scipy: 1.6.2
       Cython: 0.29.25
       pandas: 1.4.1
   matplotlib: 3.5.1
       joblib: 1.1.0
threadpoolctl: 2.2.0


!jupyter --version
Selected Jupyter core packages...
IPython          : 7.31.1
ipykernel        : 6.4.1
ipywidgets       : 7.6.5
jupyter_client   : 6.1.12
jupyter_core     : 4.9.1
jupyter_server   : 1.13.5
jupyterlab       : 3.2.9
nbclient         : 0.5.11
nbconvert        : 6.1.0
nbformat         : 5.1.3
notebook         : 6.4.9
qtconsole        : 5.2.2
traitlets        : 5.1.1
```

COMMENT:
@lesteve I recall that you found the root of the problem when working on the `GridSearchCV` verbosity, isn't it?

Labels: Bug, module:model_selection, Needs Investigation
Verbosity option is not working in GridSearchCV (Jupyter notebook)

### Describe the bug

So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) response.

The problem is that GridSearchCV doesn't show the elapsed time periodically, or any log, I am set`n_jobs = -1`, and `verbose = 1`. I tried setting `n_jobs` to other values, the same with `verbose`, but nothing happened.
Note that this didn't happen until I updated scikit-learn from version 0.22.1 to 1.0.2.

[lesteve](https://github.com/lesteve) in his response assumed that this problem is due to `ipykernel <6`, which is not the case with me.

### Steps/Code to Reproduce

```
from sklearn.model_selection import GridSearchCV
from sklearn.ensemble import RandomForestClassifier
from sklearn import datasets

iris = datasets.load_iris()
params = {'n_estimators':[10,20,30,40,50,60],
          'max_depth':[20,50,60,70,80]}
grid_obj = GridSearchCV(estimator=RandomForestClassifier(), param_grid=params, n_jobs=-1, verbose=1, cv=5)
grid_obj.fit(iris.data, iris.target)
```

### Expected Results

This is the output when using version 0.22.1
![image](https://user-images.githubusercontent.com/17684093/158401635-31755363-2108-41e7-8f7f-08985abd03b8.png)


### Actual Results

```Fitting 5 folds for each of 30 candidates, totalling 150 fits```

### Versions

```shell
System:
    python: 3.8.5 (default, Sep  3 2020, 21:29:08) [MSC v.1916 64 bit (AMD64)]
executable: D:\Programs\ApplicationsSetup\anaconda3\python.exe
   machine: Windows-10-10.0.19041-SP0

Python dependencies:
          pip: 21.2.2
   setuptools: 58.0.4
      sklearn: 1.0.2
        numpy: 1.19.2
        scipy: 1.6.2
       Cython: 0.29.25
       pandas: 1.4.1
   matplotlib: 3.5.1
       joblib: 1.1.0
threadpoolctl: 2.2.0


!jupyter --version
Selected Jupyter core packages...
IPython          : 7.31.1
ipykernel        : 6.4.1
ipywidgets       : 7.6.5
jupyter_client   : 6.1.12
jupyter_core     : 4.9.1
jupyter_server   : 1.13.5
jupyterlab       : 3.2.9
nbclient         : 0.5.11
nbconvert        : 6.1.0
nbformat         : 5.1.3
notebook         : 6.4.9
qtconsole        : 5.2.2
traitlets        : 5.1.1
```

COMMENT:
Well my answer was in the issue linked in the top post: https://github.com/scikit-learn/scikit-learn/issues/22291#issuecomment-1022048818. You need to use `ipykernel >= 6` for outputs in subprocesses to be captured inside the notebook.

It looks like there may be a new bug in ipykernel though. As you say I don't get the output captured in the notebook but once I kill the kernel, I do get the output in the terminal where I start jupyter ...

Labels: Bug, module:model_selection, Needs Investigation
Verbosity option is not working in GridSearchCV (Jupyter notebook)

### Describe the bug

So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) response.

The problem is that GridSearchCV doesn't show the elapsed time periodically, or any log, I am set`n_jobs = -1`, and `verbose = 1`. I tried setting `n_jobs` to other values, the same with `verbose`, but nothing happened.
Note that this didn't happen until I updated scikit-learn from version 0.22.1 to 1.0.2.

[lesteve](https://github.com/lesteve) in his response assumed that this problem is due to `ipykernel <6`, which is not the case with me.

### Steps/Code to Reproduce

```
from sklearn.model_selection import GridSearchCV
from sklearn.ensemble import RandomForestClassifier
from sklearn import datasets

iris = datasets.load_iris()
params = {'n_estimators':[10,20,30,40,50,60],
          'max_depth':[20,50,60,70,80]}
grid_obj = GridSearchCV(estimator=RandomForestClassifier(), param_grid=params, n_jobs=-1, verbose=1, cv=5)
grid_obj.fit(iris.data, iris.target)
```

### Expected Results

This is the output when using version 0.22.1
![image](https://user-images.githubusercontent.com/17684093/158401635-31755363-2108-41e7-8f7f-08985abd03b8.png)


### Actual Results

```Fitting 5 folds for each of 30 candidates, totalling 150 fits```

### Versions

```shell
System:
    python: 3.8.5 (default, Sep  3 2020, 21:29:08) [MSC v.1916 64 bit (AMD64)]
executable: D:\Programs\ApplicationsSetup\anaconda3\python.exe
   machine: Windows-10-10.0.19041-SP0

Python dependencies:
          pip: 21.2.2
   setuptools: 58.0.4
      sklearn: 1.0.2
        numpy: 1.19.2
        scipy: 1.6.2
       Cython: 0.29.25
       pandas: 1.4.1
   matplotlib: 3.5.1
       joblib: 1.1.0
threadpoolctl: 2.2.0


!jupyter --version
Selected Jupyter core packages...
IPython          : 7.31.1
ipykernel        : 6.4.1
ipywidgets       : 7.6.5
jupyter_client   : 6.1.12
jupyter_core     : 4.9.1
jupyter_server   : 1.13.5
jupyterlab       : 3.2.9
nbclient         : 0.5.11
nbconvert        : 6.1.0
nbformat         : 5.1.3
notebook         : 6.4.9
qtconsole        : 5.2.2
traitlets        : 5.1.1
```

COMMENT:
- Setting `n_jobs=1` and `verbose=10`  indeed produced details about each fold of each candidate of the cross-validation.
- But setting `n_jobs=-1` and `verbose=10`, still gave no output even after running `.fit` a second time.
- Also setting `multiprocessing`  for back-end didn't change anything for me when `n_jobs=-1` and `verbose=10`.

The problem is that I need to set `n_jobs=-1` as I have a large dictionary of parameters to test.  So for a process that takes a long time, having a log that contained time elapsed for a number of tasks was useful to make a sense of how long the whole process is going to take.

Labels: Bug, module:model_selection, Needs Investigation
Verbosity option is not working in GridSearchCV (Jupyter notebook)

### Describe the bug

So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) response.

The problem is that GridSearchCV doesn't show the elapsed time periodically, or any log, I am set`n_jobs = -1`, and `verbose = 1`. I tried setting `n_jobs` to other values, the same with `verbose`, but nothing happened.
Note that this didn't happen until I updated scikit-learn from version 0.22.1 to 1.0.2.

[lesteve](https://github.com/lesteve) in his response assumed that this problem is due to `ipykernel <6`, which is not the case with me.

### Steps/Code to Reproduce

```
from sklearn.model_selection import GridSearchCV
from sklearn.ensemble import RandomForestClassifier
from sklearn import datasets

iris = datasets.load_iris()
params = {'n_estimators':[10,20,30,40,50,60],
          'max_depth':[20,50,60,70,80]}
grid_obj = GridSearchCV(estimator=RandomForestClassifier(), param_grid=params, n_jobs=-1, verbose=1, cv=5)
grid_obj.fit(iris.data, iris.target)
```

### Expected Results

This is the output when using version 0.22.1
![image](https://user-images.githubusercontent.com/17684093/158401635-31755363-2108-41e7-8f7f-08985abd03b8.png)


### Actual Results

```Fitting 5 folds for each of 30 candidates, totalling 150 fits```

### Versions

```shell
System:
    python: 3.8.5 (default, Sep  3 2020, 21:29:08) [MSC v.1916 64 bit (AMD64)]
executable: D:\Programs\ApplicationsSetup\anaconda3\python.exe
   machine: Windows-10-10.0.19041-SP0

Python dependencies:
          pip: 21.2.2
   setuptools: 58.0.4
      sklearn: 1.0.2
        numpy: 1.19.2
        scipy: 1.6.2
       Cython: 0.29.25
       pandas: 1.4.1
   matplotlib: 3.5.1
       joblib: 1.1.0
threadpoolctl: 2.2.0


!jupyter --version
Selected Jupyter core packages...
IPython          : 7.31.1
ipykernel        : 6.4.1
ipywidgets       : 7.6.5
jupyter_client   : 6.1.12
jupyter_core     : 4.9.1
jupyter_server   : 1.13.5
jupyterlab       : 3.2.9
nbclient         : 0.5.11
nbconvert        : 6.1.0
nbformat         : 5.1.3
notebook         : 6.4.9
qtconsole        : 5.2.2
traitlets        : 5.1.1
```

COMMENT:
I am also observing flaky behavior. On Linux, `ipykernel==6.9.2`, `sklearn==1.0.2`, this cell:

```
gs = GridSearchCV(clf, param_grid, n_jobs=-1, verbose=10)
gs.fit(X, y)
```

_sometimes_ it produces output, and sometimes it doesn't:


https://user-images.githubusercontent.com/316517/158595301-77659174-d0c4-48b1-a694-2efd1f59f3ec.mp4

Labels: Bug, module:model_selection, Needs Investigation
Verbosity option is not working in GridSearchCV (Jupyter notebook)

### Describe the bug

So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) response.

The problem is that GridSearchCV doesn't show the elapsed time periodically, or any log, I am set`n_jobs = -1`, and `verbose = 1`. I tried setting `n_jobs` to other values, the same with `verbose`, but nothing happened.
Note that this didn't happen until I updated scikit-learn from version 0.22.1 to 1.0.2.

[lesteve](https://github.com/lesteve) in his response assumed that this problem is due to `ipykernel <6`, which is not the case with me.

### Steps/Code to Reproduce

```
from sklearn.model_selection import GridSearchCV
from sklearn.ensemble import RandomForestClassifier
from sklearn import datasets

iris = datasets.load_iris()
params = {'n_estimators':[10,20,30,40,50,60],
          'max_depth':[20,50,60,70,80]}
grid_obj = GridSearchCV(estimator=RandomForestClassifier(), param_grid=params, n_jobs=-1, verbose=1, cv=5)
grid_obj.fit(iris.data, iris.target)
```

### Expected Results

This is the output when using version 0.22.1
![image](https://user-images.githubusercontent.com/17684093/158401635-31755363-2108-41e7-8f7f-08985abd03b8.png)


### Actual Results

```Fitting 5 folds for each of 30 candidates, totalling 150 fits```

### Versions

```shell
System:
    python: 3.8.5 (default, Sep  3 2020, 21:29:08) [MSC v.1916 64 bit (AMD64)]
executable: D:\Programs\ApplicationsSetup\anaconda3\python.exe
   machine: Windows-10-10.0.19041-SP0

Python dependencies:
          pip: 21.2.2
   setuptools: 58.0.4
      sklearn: 1.0.2
        numpy: 1.19.2
        scipy: 1.6.2
       Cython: 0.29.25
       pandas: 1.4.1
   matplotlib: 3.5.1
       joblib: 1.1.0
threadpoolctl: 2.2.0


!jupyter --version
Selected Jupyter core packages...
IPython          : 7.31.1
ipykernel        : 6.4.1
ipywidgets       : 7.6.5
jupyter_client   : 6.1.12
jupyter_core     : 4.9.1
jupyter_server   : 1.13.5
jupyterlab       : 3.2.9
nbclient         : 0.5.11
nbconvert        : 6.1.0
nbformat         : 5.1.3
notebook         : 6.4.9
qtconsole        : 5.2.2
traitlets        : 5.1.1
```

COMMENT:
FYI I opened https://github.com/ipython/ipykernel/issues/882 about the first issue in my earlier comment.

Labels: Bug, module:model_selection, Needs Investigation
Verbosity option is not working in GridSearchCV (Jupyter notebook)

### Describe the bug

So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) response.

The problem is that GridSearchCV doesn't show the elapsed time periodically, or any log, I am set`n_jobs = -1`, and `verbose = 1`. I tried setting `n_jobs` to other values, the same with `verbose`, but nothing happened.
Note that this didn't happen until I updated scikit-learn from version 0.22.1 to 1.0.2.

[lesteve](https://github.com/lesteve) in his response assumed that this problem is due to `ipykernel <6`, which is not the case with me.

### Steps/Code to Reproduce

```
from sklearn.model_selection import GridSearchCV
from sklearn.ensemble import RandomForestClassifier
from sklearn import datasets

iris = datasets.load_iris()
params = {'n_estimators':[10,20,30,40,50,60],
          'max_depth':[20,50,60,70,80]}
grid_obj = GridSearchCV(estimator=RandomForestClassifier(), param_grid=params, n_jobs=-1, verbose=1, cv=5)
grid_obj.fit(iris.data, iris.target)
```

### Expected Results

This is the output when using version 0.22.1
![image](https://user-images.githubusercontent.com/17684093/158401635-31755363-2108-41e7-8f7f-08985abd03b8.png)


### Actual Results

```Fitting 5 folds for each of 30 candidates, totalling 150 fits```

### Versions

```shell
System:
    python: 3.8.5 (default, Sep  3 2020, 21:29:08) [MSC v.1916 64 bit (AMD64)]
executable: D:\Programs\ApplicationsSetup\anaconda3\python.exe
   machine: Windows-10-10.0.19041-SP0

Python dependencies:
          pip: 21.2.2
   setuptools: 58.0.4
      sklearn: 1.0.2
        numpy: 1.19.2
        scipy: 1.6.2
       Cython: 0.29.25
       pandas: 1.4.1
   matplotlib: 3.5.1
       joblib: 1.1.0
threadpoolctl: 2.2.0


!jupyter --version
Selected Jupyter core packages...
IPython          : 7.31.1
ipykernel        : 6.4.1
ipywidgets       : 7.6.5
jupyter_client   : 6.1.12
jupyter_core     : 4.9.1
jupyter_server   : 1.13.5
jupyterlab       : 3.2.9
nbclient         : 0.5.11
nbconvert        : 6.1.0
nbformat         : 5.1.3
notebook         : 6.4.9
qtconsole        : 5.2.2
traitlets        : 5.1.1
```

COMMENT:
Ok, Thank you.

Labels: Bug, module:model_selection, Needs Investigation
Verbosity option is not working in GridSearchCV (Jupyter notebook)

### Describe the bug

So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) response.

The problem is that GridSearchCV doesn't show the elapsed time periodically, or any log, I am set`n_jobs = -1`, and `verbose = 1`. I tried setting `n_jobs` to other values, the same with `verbose`, but nothing happened.
Note that this didn't happen until I updated scikit-learn from version 0.22.1 to 1.0.2.

[lesteve](https://github.com/lesteve) in his response assumed that this problem is due to `ipykernel <6`, which is not the case with me.

### Steps/Code to Reproduce

```
from sklearn.model_selection import GridSearchCV
from sklearn.ensemble import RandomForestClassifier
from sklearn import datasets

iris = datasets.load_iris()
params = {'n_estimators':[10,20,30,40,50,60],
          'max_depth':[20,50,60,70,80]}
grid_obj = GridSearchCV(estimator=RandomForestClassifier(), param_grid=params, n_jobs=-1, verbose=1, cv=5)
grid_obj.fit(iris.data, iris.target)
```

### Expected Results

This is the output when using version 0.22.1
![image](https://user-images.githubusercontent.com/17684093/158401635-31755363-2108-41e7-8f7f-08985abd03b8.png)


### Actual Results

```Fitting 5 folds for each of 30 candidates, totalling 150 fits```

### Versions

```shell
System:
    python: 3.8.5 (default, Sep  3 2020, 21:29:08) [MSC v.1916 64 bit (AMD64)]
executable: D:\Programs\ApplicationsSetup\anaconda3\python.exe
   machine: Windows-10-10.0.19041-SP0

Python dependencies:
          pip: 21.2.2
   setuptools: 58.0.4
      sklearn: 1.0.2
        numpy: 1.19.2
        scipy: 1.6.2
       Cython: 0.29.25
       pandas: 1.4.1
   matplotlib: 3.5.1
       joblib: 1.1.0
threadpoolctl: 2.2.0


!jupyter --version
Selected Jupyter core packages...
IPython          : 7.31.1
ipykernel        : 6.4.1
ipywidgets       : 7.6.5
jupyter_client   : 6.1.12
jupyter_core     : 4.9.1
jupyter_server   : 1.13.5
jupyterlab       : 3.2.9
nbclient         : 0.5.11
nbconvert        : 6.1.0
nbformat         : 5.1.3
notebook         : 6.4.9
qtconsole        : 5.2.2
traitlets        : 5.1.1
```

COMMENT:
Have there same issue on both Apple M1 and Windows. Additionally, training seems to take exceptionally long time or completely hang up.

Labels: Bug, module:model_selection, Needs Investigation
Verbosity option is not working in GridSearchCV (Jupyter notebook)

### Describe the bug

So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) response.

The problem is that GridSearchCV doesn't show the elapsed time periodically, or any log, I am set`n_jobs = -1`, and `verbose = 1`. I tried setting `n_jobs` to other values, the same with `verbose`, but nothing happened.
Note that this didn't happen until I updated scikit-learn from version 0.22.1 to 1.0.2.

[lesteve](https://github.com/lesteve) in his response assumed that this problem is due to `ipykernel <6`, which is not the case with me.

### Steps/Code to Reproduce

```
from sklearn.model_selection import GridSearchCV
from sklearn.ensemble import RandomForestClassifier
from sklearn import datasets

iris = datasets.load_iris()
params = {'n_estimators':[10,20,30,40,50,60],
          'max_depth':[20,50,60,70,80]}
grid_obj = GridSearchCV(estimator=RandomForestClassifier(), param_grid=params, n_jobs=-1, verbose=1, cv=5)
grid_obj.fit(iris.data, iris.target)
```

### Expected Results

This is the output when using version 0.22.1
![image](https://user-images.githubusercontent.com/17684093/158401635-31755363-2108-41e7-8f7f-08985abd03b8.png)


### Actual Results

```Fitting 5 folds for each of 30 candidates, totalling 150 fits```

### Versions

```shell
System:
    python: 3.8.5 (default, Sep  3 2020, 21:29:08) [MSC v.1916 64 bit (AMD64)]
executable: D:\Programs\ApplicationsSetup\anaconda3\python.exe
   machine: Windows-10-10.0.19041-SP0

Python dependencies:
          pip: 21.2.2
   setuptools: 58.0.4
      sklearn: 1.0.2
        numpy: 1.19.2
        scipy: 1.6.2
       Cython: 0.29.25
       pandas: 1.4.1
   matplotlib: 3.5.1
       joblib: 1.1.0
threadpoolctl: 2.2.0


!jupyter --version
Selected Jupyter core packages...
IPython          : 7.31.1
ipykernel        : 6.4.1
ipywidgets       : 7.6.5
jupyter_client   : 6.1.12
jupyter_core     : 4.9.1
jupyter_server   : 1.13.5
jupyterlab       : 3.2.9
nbclient         : 0.5.11
nbconvert        : 6.1.0
nbformat         : 5.1.3
notebook         : 6.4.9
qtconsole        : 5.2.2
traitlets        : 5.1.1
```

COMMENT:
Are there any updates on this? I have the same problem on Apple M1. I'm also teaching machine learning and I see that most of my students also have this problem. We set n_jobs=4 for them. No verbosity setting gives any output while running, but the output appears after the job is completed (often even in a different cell. It's very annoying since it's demotivating for the students if they don't know how far along their gridsearch is

Labels: Bug, module:model_selection, Needs Investigation
Verbosity option is not working in GridSearchCV (Jupyter notebook)

### Describe the bug

So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) response.

The problem is that GridSearchCV doesn't show the elapsed time periodically, or any log, I am set`n_jobs = -1`, and `verbose = 1`. I tried setting `n_jobs` to other values, the same with `verbose`, but nothing happened.
Note that this didn't happen until I updated scikit-learn from version 0.22.1 to 1.0.2.

[lesteve](https://github.com/lesteve) in his response assumed that this problem is due to `ipykernel <6`, which is not the case with me.

### Steps/Code to Reproduce

```
from sklearn.model_selection import GridSearchCV
from sklearn.ensemble import RandomForestClassifier
from sklearn import datasets

iris = datasets.load_iris()
params = {'n_estimators':[10,20,30,40,50,60],
          'max_depth':[20,50,60,70,80]}
grid_obj = GridSearchCV(estimator=RandomForestClassifier(), param_grid=params, n_jobs=-1, verbose=1, cv=5)
grid_obj.fit(iris.data, iris.target)
```

### Expected Results

This is the output when using version 0.22.1
![image](https://user-images.githubusercontent.com/17684093/158401635-31755363-2108-41e7-8f7f-08985abd03b8.png)


### Actual Results

```Fitting 5 folds for each of 30 candidates, totalling 150 fits```

### Versions

```shell
System:
    python: 3.8.5 (default, Sep  3 2020, 21:29:08) [MSC v.1916 64 bit (AMD64)]
executable: D:\Programs\ApplicationsSetup\anaconda3\python.exe
   machine: Windows-10-10.0.19041-SP0

Python dependencies:
          pip: 21.2.2
   setuptools: 58.0.4
      sklearn: 1.0.2
        numpy: 1.19.2
        scipy: 1.6.2
       Cython: 0.29.25
       pandas: 1.4.1
   matplotlib: 3.5.1
       joblib: 1.1.0
threadpoolctl: 2.2.0


!jupyter --version
Selected Jupyter core packages...
IPython          : 7.31.1
ipykernel        : 6.4.1
ipywidgets       : 7.6.5
jupyter_client   : 6.1.12
jupyter_core     : 4.9.1
jupyter_server   : 1.13.5
jupyterlab       : 3.2.9
nbclient         : 0.5.11
nbconvert        : 6.1.0
nbformat         : 5.1.3
notebook         : 6.4.9
qtconsole        : 5.2.2
traitlets        : 5.1.1
```

COMMENT:
👍

Labels: Bug, module:model_selection, Needs Investigation