html_url stringlengths 57 57 | labels listlengths 1 6 | text stringlengths 32 258k | issue_number int64 22.4k 33k |
|---|---|---|---|
https://github.com/scikit-learn/scikit-learn/issues/29697 | [
"Bug"
] | GaussianProcessRegressor: wrong std and cov results when n_features>1 and no y normalization
### Describe the bug
When `n_features > 1` and `normalization_y` is `False`, the `GaussianProcessRegressor.predict` seems to return bad std and cov results, as it doesn't consider the scale of the different features (while it... | 29,697 |
https://github.com/scikit-learn/scikit-learn/issues/29697 | [
"Bug"
] | GaussianProcessRegressor: wrong std and cov results when n_features>1 and no y normalization
### Describe the bug
When `n_features > 1` and `normalization_y` is `False`, the `GaussianProcessRegressor.predict` seems to return bad std and cov results, as it doesn't consider the scale of the different features (while it... | 29,697 |
https://github.com/scikit-learn/scikit-learn/issues/29697 | [
"Bug"
] | GaussianProcessRegressor: wrong std and cov results when n_features>1 and no y normalization
### Describe the bug
When `n_features > 1` and `normalization_y` is `False`, the `GaussianProcessRegressor.predict` seems to return bad std and cov results, as it doesn't consider the scale of the different features (while it... | 29,697 |
https://github.com/scikit-learn/scikit-learn/issues/29695 | [
"Needs Triage"
] | ⚠️ CI failed on Wheel builder (last failure: Aug 21, 2024) ⚠️
**CI failed on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/10483139590)** (Aug 21, 2024)
COMMENT:
## CI is no longer failing! ✅
[Successful run](https://github.com/scikit-learn/scikit-learn/actions/runs/10501460588) on Aug 22... | 29,695 |
https://github.com/scikit-learn/scikit-learn/issues/29692 | [
"New Feature",
"Needs Triage"
] | Add Diebold Mariano test for distinguishing forecasts
### Describe the workflow you want to enable
I would like to be able to compare whether one forecast is statistically better than another.
### Describe your proposed solution
Under certain conditions, the *Diebold-Mariano* test achieves this. There's an example ... | 29,692 |
https://github.com/scikit-learn/scikit-learn/issues/29684 | [
"Needs Triage"
] | ⚠️ CI failed on Wheel builder (last failure: Aug 17, 2024) ⚠️
**CI failed on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/10429290896)** (Aug 17, 2024)
COMMENT:
## CI is no longer failing! ✅
[Successful run](https://github.com/scikit-learn/scikit-learn/actions/runs/10437578688) on Aug 18... | 29,684 |
https://github.com/scikit-learn/scikit-learn/issues/29679 | [
"Bug",
"Needs Triage"
] | Arguments in train_test_split not being recognised.
### Describe the bug
When using the train_test_split function, arguments such as "test_size" and "random_state" are not being recognized, generating an unexpected keyword argument TypeError.
### Steps/Code to Reproduce
```
x_train, x_test, y_train, y_test = tra... | 29,679 |
https://github.com/scikit-learn/scikit-learn/issues/29679 | [
"Bug",
"Needs Triage"
] | Arguments in train_test_split not being recognised.
### Describe the bug
When using the train_test_split function, arguments such as "test_size" and "random_state" are not being recognized, generating an unexpected keyword argument TypeError.
### Steps/Code to Reproduce
```
x_train, x_test, y_train, y_test = tra... | 29,679 |
https://github.com/scikit-learn/scikit-learn/issues/29678 | [
"Bug"
] | root_mean_squared_log_error & mean_squared_log_error: ValueError should be raised only if y_true or y_pred contain a value below -1, not below 0
### Describe the bug
For the `sklearn.metrics.root_mean_squared_log_error(y_true, y_pred)` & `sklearn.metrics.mean_squared_log_error(y_true, y_pred)` evaluation metrics, if ... | 29,678 |
https://github.com/scikit-learn/scikit-learn/issues/29678 | [
"Bug"
] | root_mean_squared_log_error & mean_squared_log_error: ValueError should be raised only if y_true or y_pred contain a value below -1, not below 0
### Describe the bug
For the `sklearn.metrics.root_mean_squared_log_error(y_true, y_pred)` & `sklearn.metrics.mean_squared_log_error(y_true, y_pred)` evaluation metrics, if ... | 29,678 |
https://github.com/scikit-learn/scikit-learn/issues/29678 | [
"Bug"
] | root_mean_squared_log_error & mean_squared_log_error: ValueError should be raised only if y_true or y_pred contain a value below -1, not below 0
### Describe the bug
For the `sklearn.metrics.root_mean_squared_log_error(y_true, y_pred)` & `sklearn.metrics.mean_squared_log_error(y_true, y_pred)` evaluation metrics, if ... | 29,678 |
https://github.com/scikit-learn/scikit-learn/issues/29678 | [
"Bug"
] | root_mean_squared_log_error & mean_squared_log_error: ValueError should be raised only if y_true or y_pred contain a value below -1, not below 0
### Describe the bug
For the `sklearn.metrics.root_mean_squared_log_error(y_true, y_pred)` & `sklearn.metrics.mean_squared_log_error(y_true, y_pred)` evaluation metrics, if ... | 29,678 |
https://github.com/scikit-learn/scikit-learn/issues/29678 | [
"Bug"
] | root_mean_squared_log_error & mean_squared_log_error: ValueError should be raised only if y_true or y_pred contain a value below -1, not below 0
### Describe the bug
For the `sklearn.metrics.root_mean_squared_log_error(y_true, y_pred)` & `sklearn.metrics.mean_squared_log_error(y_true, y_pred)` evaluation metrics, if ... | 29,678 |
https://github.com/scikit-learn/scikit-learn/issues/29678 | [
"Bug"
] | root_mean_squared_log_error & mean_squared_log_error: ValueError should be raised only if y_true or y_pred contain a value below -1, not below 0
### Describe the bug
For the `sklearn.metrics.root_mean_squared_log_error(y_true, y_pred)` & `sklearn.metrics.mean_squared_log_error(y_true, y_pred)` evaluation metrics, if ... | 29,678 |
https://github.com/scikit-learn/scikit-learn/issues/29673 | [
"New Feature",
"Needs Investigation",
"Array API"
] | Array API backends support for MLX
It would be great to get the scikit-learn Array API back-end to be compatible with MLX (which is mostly conformant with the array API).
Here is an example which currently does not work for a few reasons:
```python
from sklearn.datasets import make_classification
from sklearn... | 29,673 |
https://github.com/scikit-learn/scikit-learn/issues/29673 | [
"New Feature",
"Needs Investigation",
"Array API"
] | Array API backends support for MLX
It would be great to get the scikit-learn Array API back-end to be compatible with MLX (which is mostly conformant with the array API).
Here is an example which currently does not work for a few reasons:
```python
from sklearn.datasets import make_classification
from sklearn... | 29,673 |
https://github.com/scikit-learn/scikit-learn/issues/29673 | [
"New Feature",
"Needs Investigation",
"Array API"
] | Array API backends support for MLX
It would be great to get the scikit-learn Array API back-end to be compatible with MLX (which is mostly conformant with the array API).
Here is an example which currently does not work for a few reasons:
```python
from sklearn.datasets import make_classification
from sklearn... | 29,673 |
https://github.com/scikit-learn/scikit-learn/issues/29673 | [
"New Feature",
"Needs Investigation",
"Array API"
] | Array API backends support for MLX
It would be great to get the scikit-learn Array API back-end to be compatible with MLX (which is mostly conformant with the array API).
Here is an example which currently does not work for a few reasons:
```python
from sklearn.datasets import make_classification
from sklearn... | 29,673 |
https://github.com/scikit-learn/scikit-learn/issues/29673 | [
"New Feature",
"Needs Investigation",
"Array API"
] | Array API backends support for MLX
It would be great to get the scikit-learn Array API back-end to be compatible with MLX (which is mostly conformant with the array API).
Here is an example which currently does not work for a few reasons:
```python
from sklearn.datasets import make_classification
from sklearn... | 29,673 |
https://github.com/scikit-learn/scikit-learn/issues/29673 | [
"New Feature",
"Needs Investigation",
"Array API"
] | Array API backends support for MLX
It would be great to get the scikit-learn Array API back-end to be compatible with MLX (which is mostly conformant with the array API).
Here is an example which currently does not work for a few reasons:
```python
from sklearn.datasets import make_classification
from sklearn... | 29,673 |
https://github.com/scikit-learn/scikit-learn/issues/29673 | [
"New Feature",
"Needs Investigation",
"Array API"
] | Array API backends support for MLX
It would be great to get the scikit-learn Array API back-end to be compatible with MLX (which is mostly conformant with the array API).
Here is an example which currently does not work for a few reasons:
```python
from sklearn.datasets import make_classification
from sklearn... | 29,673 |
https://github.com/scikit-learn/scikit-learn/issues/29673 | [
"New Feature",
"Needs Investigation",
"Array API"
] | Array API backends support for MLX
It would be great to get the scikit-learn Array API back-end to be compatible with MLX (which is mostly conformant with the array API).
Here is an example which currently does not work for a few reasons:
```python
from sklearn.datasets import make_classification
from sklearn... | 29,673 |
https://github.com/scikit-learn/scikit-learn/issues/29673 | [
"New Feature",
"Needs Investigation",
"Array API"
] | Array API backends support for MLX
It would be great to get the scikit-learn Array API back-end to be compatible with MLX (which is mostly conformant with the array API).
Here is an example which currently does not work for a few reasons:
```python
from sklearn.datasets import make_classification
from sklearn... | 29,673 |
https://github.com/scikit-learn/scikit-learn/issues/29673 | [
"New Feature",
"Needs Investigation",
"Array API"
] | Array API backends support for MLX
It would be great to get the scikit-learn Array API back-end to be compatible with MLX (which is mostly conformant with the array API).
Here is an example which currently does not work for a few reasons:
```python
from sklearn.datasets import make_classification
from sklearn... | 29,673 |
https://github.com/scikit-learn/scikit-learn/issues/29670 | [
"Needs Triage"
] | ⚠️ CI failed on Wheel builder (last failure: Aug 14, 2024) ⚠️
**CI failed on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/10381054335)** (Aug 14, 2024)
COMMENT:
Seems false positive, there's a download error. | 29,670 |
https://github.com/scikit-learn/scikit-learn/issues/29665 | [
"Performance",
"Regression",
"module:manifold"
] | TSNE performance regression in 1.5
### Describe the bug
The performance of TSNE transformation reduces when using n_jobs as 25 for the newer version w.r.t. 1.3.1.
version 1.3.1
```
df = np.random.rand(30000, 3)
tsne = TSNE(n_components=2, random_state=42, n_jobs=25, verbose=10, n_iter=1500)
```
1.5.1
```
df ... | 29,665 |
https://github.com/scikit-learn/scikit-learn/issues/29665 | [
"Performance",
"Regression",
"module:manifold"
] | TSNE performance regression in 1.5
### Describe the bug
The performance of TSNE transformation reduces when using n_jobs as 25 for the newer version w.r.t. 1.3.1.
version 1.3.1
```
df = np.random.rand(30000, 3)
tsne = TSNE(n_components=2, random_state=42, n_jobs=25, verbose=10, n_iter=1500)
```
1.5.1
```
df ... | 29,665 |
https://github.com/scikit-learn/scikit-learn/issues/29665 | [
"Performance",
"Regression",
"module:manifold"
] | TSNE performance regression in 1.5
### Describe the bug
The performance of TSNE transformation reduces when using n_jobs as 25 for the newer version w.r.t. 1.3.1.
version 1.3.1
```
df = np.random.rand(30000, 3)
tsne = TSNE(n_components=2, random_state=42, n_jobs=25, verbose=10, n_iter=1500)
```
1.5.1
```
df ... | 29,665 |
https://github.com/scikit-learn/scikit-learn/issues/29665 | [
"Performance",
"Regression",
"module:manifold"
] | TSNE performance regression in 1.5
### Describe the bug
The performance of TSNE transformation reduces when using n_jobs as 25 for the newer version w.r.t. 1.3.1.
version 1.3.1
```
df = np.random.rand(30000, 3)
tsne = TSNE(n_components=2, random_state=42, n_jobs=25, verbose=10, n_iter=1500)
```
1.5.1
```
df ... | 29,665 |
https://github.com/scikit-learn/scikit-learn/issues/29665 | [
"Performance",
"Regression",
"module:manifold"
] | TSNE performance regression in 1.5
### Describe the bug
The performance of TSNE transformation reduces when using n_jobs as 25 for the newer version w.r.t. 1.3.1.
version 1.3.1
```
df = np.random.rand(30000, 3)
tsne = TSNE(n_components=2, random_state=42, n_jobs=25, verbose=10, n_iter=1500)
```
1.5.1
```
df ... | 29,665 |
https://github.com/scikit-learn/scikit-learn/issues/29665 | [
"Performance",
"Regression",
"module:manifold"
] | TSNE performance regression in 1.5
### Describe the bug
The performance of TSNE transformation reduces when using n_jobs as 25 for the newer version w.r.t. 1.3.1.
version 1.3.1
```
df = np.random.rand(30000, 3)
tsne = TSNE(n_components=2, random_state=42, n_jobs=25, verbose=10, n_iter=1500)
```
1.5.1
```
df ... | 29,665 |
https://github.com/scikit-learn/scikit-learn/issues/29665 | [
"Performance",
"Regression",
"module:manifold"
] | TSNE performance regression in 1.5
### Describe the bug
The performance of TSNE transformation reduces when using n_jobs as 25 for the newer version w.r.t. 1.3.1.
version 1.3.1
```
df = np.random.rand(30000, 3)
tsne = TSNE(n_components=2, random_state=42, n_jobs=25, verbose=10, n_iter=1500)
```
1.5.1
```
df ... | 29,665 |
https://github.com/scikit-learn/scikit-learn/issues/29665 | [
"Performance",
"Regression",
"module:manifold"
] | TSNE performance regression in 1.5
### Describe the bug
The performance of TSNE transformation reduces when using n_jobs as 25 for the newer version w.r.t. 1.3.1.
version 1.3.1
```
df = np.random.rand(30000, 3)
tsne = TSNE(n_components=2, random_state=42, n_jobs=25, verbose=10, n_iter=1500)
```
1.5.1
```
df ... | 29,665 |
https://github.com/scikit-learn/scikit-learn/issues/29663 | [
"Bug",
"Needs Triage"
] | `fetch_20newsgroups_vectorized` gives HTTP Error 403 Forbidden
### Describe the bug
This was also recently reported on [StackOverflow](https://stackoverflow.com/questions/78398259/lda-in-python-shows-403-error-in-fetching-20newsgroups-dataset). It appears that https://ndownloader.figshare.com is down.
### Steps/Code... | 29,663 |
https://github.com/scikit-learn/scikit-learn/issues/29655 | [
"Bug",
"Needs Triage"
] | GradientBoostingClassifier feature_importances_ is all zero
### Describe the bug
I'm using GradientBoostingClassifier on a rather small dataset (n=75) for classification & feature selection.
I'm grid searching (in cross validation) the best hyper-parameters for my data and on some grids I get 0 importance for every ... | 29,655 |
https://github.com/scikit-learn/scikit-learn/issues/29655 | [
"Bug",
"Needs Triage"
] | GradientBoostingClassifier feature_importances_ is all zero
### Describe the bug
I'm using GradientBoostingClassifier on a rather small dataset (n=75) for classification & feature selection.
I'm grid searching (in cross validation) the best hyper-parameters for my data and on some grids I get 0 importance for every ... | 29,655 |
https://github.com/scikit-learn/scikit-learn/issues/29655 | [
"Bug",
"Needs Triage"
] | GradientBoostingClassifier feature_importances_ is all zero
### Describe the bug
I'm using GradientBoostingClassifier on a rather small dataset (n=75) for classification & feature selection.
I'm grid searching (in cross validation) the best hyper-parameters for my data and on some grids I get 0 importance for every ... | 29,655 |
https://github.com/scikit-learn/scikit-learn/issues/29652 | [
"Needs Triage"
] | ⚠️ CI failed on Wheel builder (last failure: Aug 11, 2024) ⚠️
**CI failed on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/10336780837)** (Aug 11, 2024)
COMMENT:
## CI is no longer failing! ✅
[Successful run](https://github.com/scikit-learn/scikit-learn/actions/runs/10345565152) on Aug 12... | 29,652 |
https://github.com/scikit-learn/scikit-learn/issues/29650 | [
"Documentation",
"Build / CI"
] | Expand build from source docs for debugging with meson
From https://github.com/scikit-learn/scikit-learn/pull/29594#issuecomment-2260154987 and https://github.com/scikit-learn/scikit-learn/pull/29594#issuecomment-2260158387:
> Could you please open a follow-up PR that expands either our "build from source" document... | 29,650 |
https://github.com/scikit-learn/scikit-learn/issues/29648 | [
"Bug",
"Needs Triage"
] | GaussianNB(priors=...) is useless
### Describe the bug
If I set the class priors to be very small for classes 0 and 2 and very large for class 1, I expect my predictions to be of class 1. However, I get class 0. It seems to be that `GaussianNB(priors=...)` is useless.
### Steps/Code to Reproduce
```python
fr... | 29,648 |
https://github.com/scikit-learn/scikit-learn/issues/29648 | [
"Bug",
"Needs Triage"
] | GaussianNB(priors=...) is useless
### Describe the bug
If I set the class priors to be very small for classes 0 and 2 and very large for class 1, I expect my predictions to be of class 1. However, I get class 0. It seems to be that `GaussianNB(priors=...)` is useless.
### Steps/Code to Reproduce
```python
fr... | 29,648 |
https://github.com/scikit-learn/scikit-learn/issues/29648 | [
"Bug",
"Needs Triage"
] | GaussianNB(priors=...) is useless
### Describe the bug
If I set the class priors to be very small for classes 0 and 2 and very large for class 1, I expect my predictions to be of class 1. However, I get class 0. It seems to be that `GaussianNB(priors=...)` is useless.
### Steps/Code to Reproduce
```python
fr... | 29,648 |
https://github.com/scikit-learn/scikit-learn/issues/29643 | [
"Documentation",
"Needs Triage"
] | Update Twitter to X Throughout the Repository
### Describe the issue linked to the documentation
With the recent rebranding of Twitter to X, several references to **Twitter** in the `scikit-learn` repository need to be updated to reflect this change. This includes updating URLs and any textual references across multi... | 29,643 |
https://github.com/scikit-learn/scikit-learn/issues/29643 | [
"Documentation",
"Needs Triage"
] | Update Twitter to X Throughout the Repository
### Describe the issue linked to the documentation
With the recent rebranding of Twitter to X, several references to **Twitter** in the `scikit-learn` repository need to be updated to reflect this change. This includes updating URLs and any textual references across multi... | 29,643 |
https://github.com/scikit-learn/scikit-learn/issues/29643 | [
"Documentation",
"Needs Triage"
] | Update Twitter to X Throughout the Repository
### Describe the issue linked to the documentation
With the recent rebranding of Twitter to X, several references to **Twitter** in the `scikit-learn` repository need to be updated to reflect this change. This includes updating URLs and any textual references across multi... | 29,643 |
https://github.com/scikit-learn/scikit-learn/issues/29643 | [
"Documentation",
"Needs Triage"
] | Update Twitter to X Throughout the Repository
### Describe the issue linked to the documentation
With the recent rebranding of Twitter to X, several references to **Twitter** in the `scikit-learn` repository need to be updated to reflect this change. This includes updating URLs and any textual references across multi... | 29,643 |
https://github.com/scikit-learn/scikit-learn/issues/29643 | [
"Documentation",
"Needs Triage"
] | Update Twitter to X Throughout the Repository
### Describe the issue linked to the documentation
With the recent rebranding of Twitter to X, several references to **Twitter** in the `scikit-learn` repository need to be updated to reflect this change. This includes updating URLs and any textual references across multi... | 29,643 |
https://github.com/scikit-learn/scikit-learn/issues/29643 | [
"Documentation",
"Needs Triage"
] | Update Twitter to X Throughout the Repository
### Describe the issue linked to the documentation
With the recent rebranding of Twitter to X, several references to **Twitter** in the `scikit-learn` repository need to be updated to reflect this change. This includes updating URLs and any textual references across multi... | 29,643 |
https://github.com/scikit-learn/scikit-learn/issues/29643 | [
"Documentation",
"Needs Triage"
] | Update Twitter to X Throughout the Repository
### Describe the issue linked to the documentation
With the recent rebranding of Twitter to X, several references to **Twitter** in the `scikit-learn` repository need to be updated to reflect this change. This includes updating URLs and any textual references across multi... | 29,643 |
https://github.com/scikit-learn/scikit-learn/issues/29642 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_Runs.pylatest_conda_forge_mkl (last failure: Aug 09, 2024) ⚠️
**CI failed on [Linux_Runs.pylatest_conda_forge_mkl](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=69335&view=logs&j=dde5042c-7464-5d47-9507-31bdd2ee0a3a)** (Aug 09, 2024)
- Test Collection Failure
COMMENT:
##... | 29,642 |
https://github.com/scikit-learn/scikit-learn/issues/29640 | [
"Bug",
"Needs Triage"
] | BinMapper within HGBT does not handle sample weights
### Describe the bug
BinMapper under _hist_gradient_boosting does not accept sample weights as input leading to mismatch of bin thresholds outputted when calculating weighted versus repeated samples. Linked to Issue #27117
### Steps/Code to Reproduce
```pyt... | 29,640 |
https://github.com/scikit-learn/scikit-learn/issues/29640 | [
"Bug",
"Needs Triage"
] | BinMapper within HGBT does not handle sample weights
### Describe the bug
BinMapper under _hist_gradient_boosting does not accept sample weights as input leading to mismatch of bin thresholds outputted when calculating weighted versus repeated samples. Linked to Issue #27117
### Steps/Code to Reproduce
```pyt... | 29,640 |
https://github.com/scikit-learn/scikit-learn/issues/29633 | [
"Bug"
] | test_svm fails on i386 with scipy 1.13
### Describe the bug
scipy 1.13 is triggering test failure in test_svc_ovr_tie_breaking[NuSVC] on i386 architecture.
The error can be seeing in debian CI tests, https://ci.debian.net/packages/s/scikit-learn/unstable/i386/
Full test log at https://ci.debian.net/packages/s/s... | 29,633 |
https://github.com/scikit-learn/scikit-learn/issues/29633 | [
"Bug"
] | test_svm fails on i386 with scipy 1.13
### Describe the bug
scipy 1.13 is triggering test failure in test_svc_ovr_tie_breaking[NuSVC] on i386 architecture.
The error can be seeing in debian CI tests, https://ci.debian.net/packages/s/scikit-learn/unstable/i386/
Full test log at https://ci.debian.net/packages/s/s... | 29,633 |
https://github.com/scikit-learn/scikit-learn/issues/29633 | [
"Bug"
] | test_svm fails on i386 with scipy 1.13
### Describe the bug
scipy 1.13 is triggering test failure in test_svc_ovr_tie_breaking[NuSVC] on i386 architecture.
The error can be seeing in debian CI tests, https://ci.debian.net/packages/s/scikit-learn/unstable/i386/
Full test log at https://ci.debian.net/packages/s/s... | 29,633 |
https://github.com/scikit-learn/scikit-learn/issues/29633 | [
"Bug"
] | test_svm fails on i386 with scipy 1.13
### Describe the bug
scipy 1.13 is triggering test failure in test_svc_ovr_tie_breaking[NuSVC] on i386 architecture.
The error can be seeing in debian CI tests, https://ci.debian.net/packages/s/scikit-learn/unstable/i386/
Full test log at https://ci.debian.net/packages/s/s... | 29,633 |
https://github.com/scikit-learn/scikit-learn/issues/29633 | [
"Bug"
] | test_svm fails on i386 with scipy 1.13
### Describe the bug
scipy 1.13 is triggering test failure in test_svc_ovr_tie_breaking[NuSVC] on i386 architecture.
The error can be seeing in debian CI tests, https://ci.debian.net/packages/s/scikit-learn/unstable/i386/
Full test log at https://ci.debian.net/packages/s/s... | 29,633 |
https://github.com/scikit-learn/scikit-learn/issues/29633 | [
"Bug"
] | test_svm fails on i386 with scipy 1.13
### Describe the bug
scipy 1.13 is triggering test failure in test_svc_ovr_tie_breaking[NuSVC] on i386 architecture.
The error can be seeing in debian CI tests, https://ci.debian.net/packages/s/scikit-learn/unstable/i386/
Full test log at https://ci.debian.net/packages/s/s... | 29,633 |
https://github.com/scikit-learn/scikit-learn/issues/29630 | [
"New Feature"
] | Maintenance releases for 1.1.x and 1.2.x with numpy < 2.0?
### Describe the workflow you want to enable
Having an environment file or requirement file with scikit-learn=1.1 or scikit-learn=1.2 will break, since neither supports numpy 2.0 but doesn't declare that.
Example:
```bash
$ conda create -n sklearn_nump... | 29,630 |
https://github.com/scikit-learn/scikit-learn/issues/29630 | [
"New Feature"
] | Maintenance releases for 1.1.x and 1.2.x with numpy < 2.0?
### Describe the workflow you want to enable
Having an environment file or requirement file with scikit-learn=1.1 or scikit-learn=1.2 will break, since neither supports numpy 2.0 but doesn't declare that.
Example:
```bash
$ conda create -n sklearn_nump... | 29,630 |
https://github.com/scikit-learn/scikit-learn/issues/29630 | [
"New Feature"
] | Maintenance releases for 1.1.x and 1.2.x with numpy < 2.0?
### Describe the workflow you want to enable
Having an environment file or requirement file with scikit-learn=1.1 or scikit-learn=1.2 will break, since neither supports numpy 2.0 but doesn't declare that.
Example:
```bash
$ conda create -n sklearn_nump... | 29,630 |
https://github.com/scikit-learn/scikit-learn/issues/29630 | [
"New Feature"
] | Maintenance releases for 1.1.x and 1.2.x with numpy < 2.0?
### Describe the workflow you want to enable
Having an environment file or requirement file with scikit-learn=1.1 or scikit-learn=1.2 will break, since neither supports numpy 2.0 but doesn't declare that.
Example:
```bash
$ conda create -n sklearn_nump... | 29,630 |
https://github.com/scikit-learn/scikit-learn/issues/29630 | [
"New Feature"
] | Maintenance releases for 1.1.x and 1.2.x with numpy < 2.0?
### Describe the workflow you want to enable
Having an environment file or requirement file with scikit-learn=1.1 or scikit-learn=1.2 will break, since neither supports numpy 2.0 but doesn't declare that.
Example:
```bash
$ conda create -n sklearn_nump... | 29,630 |
https://github.com/scikit-learn/scikit-learn/issues/29630 | [
"New Feature"
] | Maintenance releases for 1.1.x and 1.2.x with numpy < 2.0?
### Describe the workflow you want to enable
Having an environment file or requirement file with scikit-learn=1.1 or scikit-learn=1.2 will break, since neither supports numpy 2.0 but doesn't declare that.
Example:
```bash
$ conda create -n sklearn_nump... | 29,630 |
https://github.com/scikit-learn/scikit-learn/issues/29630 | [
"New Feature"
] | Maintenance releases for 1.1.x and 1.2.x with numpy < 2.0?
### Describe the workflow you want to enable
Having an environment file or requirement file with scikit-learn=1.1 or scikit-learn=1.2 will break, since neither supports numpy 2.0 but doesn't declare that.
Example:
```bash
$ conda create -n sklearn_nump... | 29,630 |
https://github.com/scikit-learn/scikit-learn/issues/29630 | [
"New Feature"
] | Maintenance releases for 1.1.x and 1.2.x with numpy < 2.0?
### Describe the workflow you want to enable
Having an environment file or requirement file with scikit-learn=1.1 or scikit-learn=1.2 will break, since neither supports numpy 2.0 but doesn't declare that.
Example:
```bash
$ conda create -n sklearn_nump... | 29,630 |
https://github.com/scikit-learn/scikit-learn/issues/29630 | [
"New Feature"
] | Maintenance releases for 1.1.x and 1.2.x with numpy < 2.0?
### Describe the workflow you want to enable
Having an environment file or requirement file with scikit-learn=1.1 or scikit-learn=1.2 will break, since neither supports numpy 2.0 but doesn't declare that.
Example:
```bash
$ conda create -n sklearn_nump... | 29,630 |
https://github.com/scikit-learn/scikit-learn/issues/29629 | [
"Bug",
"Needs Triage"
] | plot_tree fails with ValueError Invalid RGBA argument
### Describe the bug
When using `plot_tree` with `filled=True` (so the nodes are colored), one sometimes gets a `ValueError` such as
```
Invalid RGBA argument: '#cb 3-8d'
```
The same `plot_tree` will work fine if `filled=False`, and draw a decision tree. Be... | 29,629 |
https://github.com/scikit-learn/scikit-learn/issues/29629 | [
"Bug",
"Needs Triage"
] | plot_tree fails with ValueError Invalid RGBA argument
### Describe the bug
When using `plot_tree` with `filled=True` (so the nodes are colored), one sometimes gets a `ValueError` such as
```
Invalid RGBA argument: '#cb 3-8d'
```
The same `plot_tree` will work fine if `filled=False`, and draw a decision tree. Be... | 29,629 |
https://github.com/scikit-learn/scikit-learn/issues/29629 | [
"Bug",
"Needs Triage"
] | plot_tree fails with ValueError Invalid RGBA argument
### Describe the bug
When using `plot_tree` with `filled=True` (so the nodes are colored), one sometimes gets a `ValueError` such as
```
Invalid RGBA argument: '#cb 3-8d'
```
The same `plot_tree` will work fine if `filled=False`, and draw a decision tree. Be... | 29,629 |
https://github.com/scikit-learn/scikit-learn/issues/29629 | [
"Bug",
"Needs Triage"
] | plot_tree fails with ValueError Invalid RGBA argument
### Describe the bug
When using `plot_tree` with `filled=True` (so the nodes are colored), one sometimes gets a `ValueError` such as
```
Invalid RGBA argument: '#cb 3-8d'
```
The same `plot_tree` will work fine if `filled=False`, and draw a decision tree. Be... | 29,629 |
https://github.com/scikit-learn/scikit-learn/issues/29629 | [
"Bug",
"Needs Triage"
] | plot_tree fails with ValueError Invalid RGBA argument
### Describe the bug
When using `plot_tree` with `filled=True` (so the nodes are colored), one sometimes gets a `ValueError` such as
```
Invalid RGBA argument: '#cb 3-8d'
```
The same `plot_tree` will work fine if `filled=False`, and draw a decision tree. Be... | 29,629 |
https://github.com/scikit-learn/scikit-learn/issues/29629 | [
"Bug",
"Needs Triage"
] | plot_tree fails with ValueError Invalid RGBA argument
### Describe the bug
When using `plot_tree` with `filled=True` (so the nodes are colored), one sometimes gets a `ValueError` such as
```
Invalid RGBA argument: '#cb 3-8d'
```
The same `plot_tree` will work fine if `filled=False`, and draw a decision tree. Be... | 29,629 |
https://github.com/scikit-learn/scikit-learn/issues/29629 | [
"Bug",
"Needs Triage"
] | plot_tree fails with ValueError Invalid RGBA argument
### Describe the bug
When using `plot_tree` with `filled=True` (so the nodes are colored), one sometimes gets a `ValueError` such as
```
Invalid RGBA argument: '#cb 3-8d'
```
The same `plot_tree` will work fine if `filled=False`, and draw a decision tree. Be... | 29,629 |
https://github.com/scikit-learn/scikit-learn/issues/29627 | [
"Bug",
"Needs Triage"
] | Performance Degradation in FeatureUnion with String Columns when concatenate the outputs of the transformers
### Describe the bug
I am experiencing significant performance degradation when using FeatureUnion in a Pipeline with DataFrames that include string columns set to be concatenated in the passthrough, the execu... | 29,627 |
https://github.com/scikit-learn/scikit-learn/issues/29627 | [
"Bug",
"Needs Triage"
] | Performance Degradation in FeatureUnion with String Columns when concatenate the outputs of the transformers
### Describe the bug
I am experiencing significant performance degradation when using FeatureUnion in a Pipeline with DataFrames that include string columns set to be concatenated in the passthrough, the execu... | 29,627 |
https://github.com/scikit-learn/scikit-learn/issues/29627 | [
"Bug",
"Needs Triage"
] | Performance Degradation in FeatureUnion with String Columns when concatenate the outputs of the transformers
### Describe the bug
I am experiencing significant performance degradation when using FeatureUnion in a Pipeline with DataFrames that include string columns set to be concatenated in the passthrough, the execu... | 29,627 |
https://github.com/scikit-learn/scikit-learn/issues/29627 | [
"Bug",
"Needs Triage"
] | Performance Degradation in FeatureUnion with String Columns when concatenate the outputs of the transformers
### Describe the bug
I am experiencing significant performance degradation when using FeatureUnion in a Pipeline with DataFrames that include string columns set to be concatenated in the passthrough, the execu... | 29,627 |
https://github.com/scikit-learn/scikit-learn/issues/29627 | [
"Bug",
"Needs Triage"
] | Performance Degradation in FeatureUnion with String Columns when concatenate the outputs of the transformers
### Describe the bug
I am experiencing significant performance degradation when using FeatureUnion in a Pipeline with DataFrames that include string columns set to be concatenated in the passthrough, the execu... | 29,627 |
https://github.com/scikit-learn/scikit-learn/issues/29626 | [
"Enhancement",
"module:neighbors"
] | Add optional return of STD for kNeighboursRegressor
### Describe the workflow you want to enable
I would like to propose to add the option to get the standard deviation from the KNeighborsRegressor. The `.predict()` function already delivers the mean, as that's the way the target is calculated, so adding the standard... | 29,626 |
https://github.com/scikit-learn/scikit-learn/issues/29626 | [
"Enhancement",
"module:neighbors"
] | Add optional return of STD for kNeighboursRegressor
### Describe the workflow you want to enable
I would like to propose to add the option to get the standard deviation from the KNeighborsRegressor. The `.predict()` function already delivers the mean, as that's the way the target is calculated, so adding the standard... | 29,626 |
https://github.com/scikit-learn/scikit-learn/issues/29626 | [
"Enhancement",
"module:neighbors"
] | Add optional return of STD for kNeighboursRegressor
### Describe the workflow you want to enable
I would like to propose to add the option to get the standard deviation from the KNeighborsRegressor. The `.predict()` function already delivers the mean, as that's the way the target is calculated, so adding the standard... | 29,626 |
https://github.com/scikit-learn/scikit-learn/issues/29626 | [
"Enhancement",
"module:neighbors"
] | Add optional return of STD for kNeighboursRegressor
### Describe the workflow you want to enable
I would like to propose to add the option to get the standard deviation from the KNeighborsRegressor. The `.predict()` function already delivers the mean, as that's the way the target is calculated, so adding the standard... | 29,626 |
https://github.com/scikit-learn/scikit-learn/issues/29626 | [
"Enhancement",
"module:neighbors"
] | Add optional return of STD for kNeighboursRegressor
### Describe the workflow you want to enable
I would like to propose to add the option to get the standard deviation from the KNeighborsRegressor. The `.predict()` function already delivers the mean, as that's the way the target is calculated, so adding the standard... | 29,626 |
https://github.com/scikit-learn/scikit-learn/issues/29626 | [
"Enhancement",
"module:neighbors"
] | Add optional return of STD for kNeighboursRegressor
### Describe the workflow you want to enable
I would like to propose to add the option to get the standard deviation from the KNeighborsRegressor. The `.predict()` function already delivers the mean, as that's the way the target is calculated, so adding the standard... | 29,626 |
https://github.com/scikit-learn/scikit-learn/issues/29626 | [
"Enhancement",
"module:neighbors"
] | Add optional return of STD for kNeighboursRegressor
### Describe the workflow you want to enable
I would like to propose to add the option to get the standard deviation from the KNeighborsRegressor. The `.predict()` function already delivers the mean, as that's the way the target is calculated, so adding the standard... | 29,626 |
https://github.com/scikit-learn/scikit-learn/issues/29626 | [
"Enhancement",
"module:neighbors"
] | Add optional return of STD for kNeighboursRegressor
### Describe the workflow you want to enable
I would like to propose to add the option to get the standard deviation from the KNeighborsRegressor. The `.predict()` function already delivers the mean, as that's the way the target is calculated, so adding the standard... | 29,626 |
https://github.com/scikit-learn/scikit-learn/issues/29626 | [
"Enhancement",
"module:neighbors"
] | Add optional return of STD for kNeighboursRegressor
### Describe the workflow you want to enable
I would like to propose to add the option to get the standard deviation from the KNeighborsRegressor. The `.predict()` function already delivers the mean, as that's the way the target is calculated, so adding the standard... | 29,626 |
https://github.com/scikit-learn/scikit-learn/issues/29621 | [
"Bug"
] | mirrors-prettier pre-commit has been archived so maybe should be replaced
### Describe the bug
Noticed your [mirrors-prettier pre-commit](https://github.com/pre-commit/mirrors-prettier) has been archived. I was going to suggest you remove and/or look for alternative linters for the scss / js files.
### Steps/Code to... | 29,621 |
https://github.com/scikit-learn/scikit-learn/issues/29621 | [
"Bug"
] | mirrors-prettier pre-commit has been archived so maybe should be replaced
### Describe the bug
Noticed your [mirrors-prettier pre-commit](https://github.com/pre-commit/mirrors-prettier) has been archived. I was going to suggest you remove and/or look for alternative linters for the scss / js files.
### Steps/Code to... | 29,621 |
https://github.com/scikit-learn/scikit-learn/issues/29621 | [
"Bug"
] | mirrors-prettier pre-commit has been archived so maybe should be replaced
### Describe the bug
Noticed your [mirrors-prettier pre-commit](https://github.com/pre-commit/mirrors-prettier) has been archived. I was going to suggest you remove and/or look for alternative linters for the scss / js files.
### Steps/Code to... | 29,621 |
https://github.com/scikit-learn/scikit-learn/issues/29620 | [
"API",
"help wanted"
] | `base_estimator` in `Chain` classes while `estimator` is the convention in `Bagging` and `MultiOutput` classes?
### Describe the issue linked to the documentation
Currently most ensembling methods in `scikit-learn` such as [bagging methods](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.BaggingCla... | 29,620 |
https://github.com/scikit-learn/scikit-learn/issues/29620 | [
"API",
"help wanted"
] | `base_estimator` in `Chain` classes while `estimator` is the convention in `Bagging` and `MultiOutput` classes?
### Describe the issue linked to the documentation
Currently most ensembling methods in `scikit-learn` such as [bagging methods](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.BaggingCla... | 29,620 |
https://github.com/scikit-learn/scikit-learn/issues/29620 | [
"API",
"help wanted"
] | `base_estimator` in `Chain` classes while `estimator` is the convention in `Bagging` and `MultiOutput` classes?
### Describe the issue linked to the documentation
Currently most ensembling methods in `scikit-learn` such as [bagging methods](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.BaggingCla... | 29,620 |
https://github.com/scikit-learn/scikit-learn/issues/29620 | [
"API",
"help wanted"
] | `base_estimator` in `Chain` classes while `estimator` is the convention in `Bagging` and `MultiOutput` classes?
### Describe the issue linked to the documentation
Currently most ensembling methods in `scikit-learn` such as [bagging methods](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.BaggingCla... | 29,620 |
https://github.com/scikit-learn/scikit-learn/issues/29616 | [
"New Feature"
] | Student-t Mixture Model
### Describe the workflow you want to enable
Gaussian mixtures are extremely useful, but many datasets are noisy enough that a GMM fit can be challenging. In these cases, adding a degree of freedom by using a t distribution instead of a normal distribution can make fitting significantly simple... | 29,616 |
https://github.com/scikit-learn/scikit-learn/issues/29616 | [
"New Feature"
] | Student-t Mixture Model
### Describe the workflow you want to enable
Gaussian mixtures are extremely useful, but many datasets are noisy enough that a GMM fit can be challenging. In these cases, adding a degree of freedom by using a t distribution instead of a normal distribution can make fitting significantly simple... | 29,616 |
https://github.com/scikit-learn/scikit-learn/issues/29616 | [
"New Feature"
] | Student-t Mixture Model
### Describe the workflow you want to enable
Gaussian mixtures are extremely useful, but many datasets are noisy enough that a GMM fit can be challenging. In these cases, adding a degree of freedom by using a t distribution instead of a normal distribution can make fitting significantly simple... | 29,616 |
https://github.com/scikit-learn/scikit-learn/issues/29616 | [
"New Feature"
] | Student-t Mixture Model
### Describe the workflow you want to enable
Gaussian mixtures are extremely useful, but many datasets are noisy enough that a GMM fit can be challenging. In these cases, adding a degree of freedom by using a t distribution instead of a normal distribution can make fitting significantly simple... | 29,616 |
https://github.com/scikit-learn/scikit-learn/issues/29610 | [
"Bug",
"Build / CI"
] | ⚠️ CI failed on Wheel builder (last failure: Aug 08, 2024) ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/10295577740)** (Aug 08, 2024)
COMMENT:
- The failure for the `cp313t-manylinux_x86_64-manylinux2014` build seems related to https://github.com/scikit-learn/s... | 29,610 |
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