html_url stringlengths 57 57 | labels listlengths 1 6 | text stringlengths 32 258k | issue_number int64 22.4k 33k | embedding listlengths 768 768 |
|---|---|---|---|---|
https://github.com/scikit-learn/scikit-learn/issues/32048 | [
"New Feature",
"Needs Decision - Include Feature"
] | Leiden Clustering
### Describe the workflow you want to enable
The "Leiden" Clustering algorithm is considered one of the most powerful clustering algorithms, often outperforming competitors by a wide margin.
The algorithm fulfils the inclusion criteria: its now 6 years old, has some 5200 citations.
Currently, it ... | 32,048 | [
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https://github.com/scikit-learn/scikit-learn/issues/32048 | [
"New Feature",
"Needs Decision - Include Feature"
] | Leiden Clustering
### Describe the workflow you want to enable
The "Leiden" Clustering algorithm is considered one of the most powerful clustering algorithms, often outperforming competitors by a wide margin.
The algorithm fulfils the inclusion criteria: its now 6 years old, has some 5200 citations.
Currently, it ... | 32,048 | [
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https://github.com/scikit-learn/scikit-learn/issues/32048 | [
"New Feature",
"Needs Decision - Include Feature"
] | Leiden Clustering
### Describe the workflow you want to enable
The "Leiden" Clustering algorithm is considered one of the most powerful clustering algorithms, often outperforming competitors by a wide margin.
The algorithm fulfils the inclusion criteria: its now 6 years old, has some 5200 citations.
Currently, it ... | 32,048 | [
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... |
https://github.com/scikit-learn/scikit-learn/issues/32048 | [
"New Feature",
"Needs Decision - Include Feature"
] | Leiden Clustering
### Describe the workflow you want to enable
The "Leiden" Clustering algorithm is considered one of the most powerful clustering algorithms, often outperforming competitors by a wide margin.
The algorithm fulfils the inclusion criteria: its now 6 years old, has some 5200 citations.
Currently, it ... | 32,048 | [
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https://github.com/scikit-learn/scikit-learn/issues/32046 | [
"Documentation",
"Needs Triage"
] | rendering of 'routing' note in the documentation
### Describe the issue linked to the documentation
the rendering of this section seems to be over-indented leading to some funky rendering in html:
example:
https://scikit-learn.org/stable/modules/generated/sklearn.cross_decomposition.CCA.html#sklearn.cross_decomposi... | 32,046 | [
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https://github.com/scikit-learn/scikit-learn/issues/32046 | [
"Documentation",
"Needs Triage"
] | rendering of 'routing' note in the documentation
### Describe the issue linked to the documentation
the rendering of this section seems to be over-indented leading to some funky rendering in html:
example:
https://scikit-learn.org/stable/modules/generated/sklearn.cross_decomposition.CCA.html#sklearn.cross_decomposi... | 32,046 | [
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https://github.com/scikit-learn/scikit-learn/issues/32045 | [
"Bug",
"Documentation"
] | make sphinx directive about version more sklearn specific
### Describe the issue linked to the documentation
This is minor issue mostly affecting the rendering of the documentation of downstream libraries.
For example in Nilearn we use the TransformerMixin in quite a few of our estimators.
But when viewing the doc ... | 32,045 | [
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https://github.com/scikit-learn/scikit-learn/issues/32045 | [
"Bug",
"Documentation"
] | make sphinx directive about version more sklearn specific
### Describe the issue linked to the documentation
This is minor issue mostly affecting the rendering of the documentation of downstream libraries.
For example in Nilearn we use the TransformerMixin in quite a few of our estimators.
But when viewing the doc ... | 32,045 | [
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https://github.com/scikit-learn/scikit-learn/issues/32045 | [
"Bug",
"Documentation"
] | make sphinx directive about version more sklearn specific
### Describe the issue linked to the documentation
This is minor issue mostly affecting the rendering of the documentation of downstream libraries.
For example in Nilearn we use the TransformerMixin in quite a few of our estimators.
But when viewing the doc ... | 32,045 | [
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https://github.com/scikit-learn/scikit-learn/issues/32045 | [
"Bug",
"Documentation"
] | make sphinx directive about version more sklearn specific
### Describe the issue linked to the documentation
This is minor issue mostly affecting the rendering of the documentation of downstream libraries.
For example in Nilearn we use the TransformerMixin in quite a few of our estimators.
But when viewing the doc ... | 32,045 | [
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https://github.com/scikit-learn/scikit-learn/issues/32044 | [
"module:svm",
"Array API"
] | PyTorch tensor failed with SVM
### Describe the bug
PyTorch tensor failed with SVM: `TypeError: asarray(): argument 'dtype' must be torch.dtype, not type`
### Steps/Code to Reproduce
```python
import torch
from sklearn import config_context
from sklearn.svm import SVC
from sklearn.datasets import make_classificatio... | 32,044 | [
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https://github.com/scikit-learn/scikit-learn/issues/32043 | [
"Bug",
"Needs Triage"
] | Failed to build scikit learn with cython.
### Describe the bug
I run the command in https://scikit-learn.org/stable/developers/advanced_installation.html , but it built failed:
```
root@dsw-1307236-5f5f447cdf-xs4m5:/mnt/workspace/scikit-learn# pip install --editable . --verbose --no-build-isolation --config-s... | 32,043 | [
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0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32036 | [
"Bug",
"Documentation"
] | Classification metrics don't seem to support sparse?
While working on #31829, I noticed that although most metrics in `_classification.py` say they support sparse in the docstring (and include "sparse matrix" in `validate_params`), when you actually try, you get an error.
Essentially in `_check_targets`, we do:
http... | 32,036 | [
0.015210146084427834,
-0.011679407209157944,
0.05314693972468376,
-0.028382619842886925,
0.09347009658813477,
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0.027317587286233902,
-0.011... |
https://github.com/scikit-learn/scikit-learn/issues/32036 | [
"Bug",
"Documentation"
] | Classification metrics don't seem to support sparse?
While working on #31829, I noticed that although most metrics in `_classification.py` say they support sparse in the docstring (and include "sparse matrix" in `validate_params`), when you actually try, you get an error.
Essentially in `_check_targets`, we do:
http... | 32,036 | [
0.015210146084427834,
-0.011679407209157944,
0.05314693972468376,
-0.028382619842886925,
0.09347009658813477,
0.009288699366152287,
0.0479743592441082,
0.04797021672129631,
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-0.02071020007133484,
0.016785161569714546,
-0.02991580404341221,
0.027317587286233902,
-0.011... |
https://github.com/scikit-learn/scikit-learn/issues/32036 | [
"Bug",
"Documentation"
] | Classification metrics don't seem to support sparse?
While working on #31829, I noticed that although most metrics in `_classification.py` say they support sparse in the docstring (and include "sparse matrix" in `validate_params`), when you actually try, you get an error.
Essentially in `_check_targets`, we do:
http... | 32,036 | [
0.015210146084427834,
-0.011679407209157944,
0.05314693972468376,
-0.028382619842886925,
0.09347009658813477,
0.009288699366152287,
0.0479743592441082,
0.04797021672129631,
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-0.02071020007133484,
0.016785161569714546,
-0.02991580404341221,
0.027317587286233902,
-0.011... |
https://github.com/scikit-learn/scikit-learn/issues/32036 | [
"Bug",
"Documentation"
] | Classification metrics don't seem to support sparse?
While working on #31829, I noticed that although most metrics in `_classification.py` say they support sparse in the docstring (and include "sparse matrix" in `validate_params`), when you actually try, you get an error.
Essentially in `_check_targets`, we do:
http... | 32,036 | [
0.015210146084427834,
-0.011679407209157944,
0.05314693972468376,
-0.028382619842886925,
0.09347009658813477,
0.009288699366152287,
0.0479743592441082,
0.04797021672129631,
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-0.02071020007133484,
0.016785161569714546,
-0.02991580404341221,
0.027317587286233902,
-0.011... |
https://github.com/scikit-learn/scikit-learn/issues/32036 | [
"Bug",
"Documentation"
] | Classification metrics don't seem to support sparse?
While working on #31829, I noticed that although most metrics in `_classification.py` say they support sparse in the docstring (and include "sparse matrix" in `validate_params`), when you actually try, you get an error.
Essentially in `_check_targets`, we do:
http... | 32,036 | [
0.015210146084427834,
-0.011679407209157944,
0.05314693972468376,
-0.028382619842886925,
0.09347009658813477,
0.009288699366152287,
0.0479743592441082,
0.04797021672129631,
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-0.02071020007133484,
0.016785161569714546,
-0.02991580404341221,
0.027317587286233902,
-0.011... |
https://github.com/scikit-learn/scikit-learn/issues/32036 | [
"Bug",
"Documentation"
] | Classification metrics don't seem to support sparse?
While working on #31829, I noticed that although most metrics in `_classification.py` say they support sparse in the docstring (and include "sparse matrix" in `validate_params`), when you actually try, you get an error.
Essentially in `_check_targets`, we do:
http... | 32,036 | [
0.015210146084427834,
-0.011679407209157944,
0.05314693972468376,
-0.028382619842886925,
0.09347009658813477,
0.009288699366152287,
0.0479743592441082,
0.04797021672129631,
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-0.02071020007133484,
0.016785161569714546,
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0.027317587286233902,
-0.011... |
https://github.com/scikit-learn/scikit-learn/issues/32032 | [
"New Feature",
"Needs Decision - Include Feature"
] | Setting weights on items when passing list of dicts to RandomizedSearchCV
### Describe the workflow you want to enable
We can pass a list of dictionaries to `RandomizedSearchCV`, for example
```python
[
{"dim_reduction": "passthrough"},
{
"dim_reduction": PCA(),
"dim_reduction__n_components":... | 32,032 | [
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-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32032 | [
"New Feature",
"Needs Decision - Include Feature"
] | Setting weights on items when passing list of dicts to RandomizedSearchCV
### Describe the workflow you want to enable
We can pass a list of dictionaries to `RandomizedSearchCV`, for example
```python
[
{"dim_reduction": "passthrough"},
{
"dim_reduction": PCA(),
"dim_reduction__n_components":... | 32,032 | [
0.006612506229430437,
0.04089715704321861,
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-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32022 | [
"Bug"
] | ⚠️ CI failed on Linux_Nightly.pylatest_pip_scipy_dev (last failure: Aug 28, 2025) ⚠️
**CI is still failing on [Linux_Nightly.pylatest_pip_scipy_dev](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=79396&view=logs&j=dfe99b15-50db-5d7b-b1e9-4105c42527cf)** (Aug 28, 2025)
Unable to find junit file.... | 32,022 | [
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0.03206790... |
https://github.com/scikit-learn/scikit-learn/issues/32022 | [
"Bug"
] | ⚠️ CI failed on Linux_Nightly.pylatest_pip_scipy_dev (last failure: Aug 28, 2025) ⚠️
**CI is still failing on [Linux_Nightly.pylatest_pip_scipy_dev](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=79396&view=logs&j=dfe99b15-50db-5d7b-b1e9-4105c42527cf)** (Aug 28, 2025)
Unable to find junit file.... | 32,022 | [
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0.03... |
https://github.com/scikit-learn/scikit-learn/issues/32022 | [
"Bug"
] | ⚠️ CI failed on Linux_Nightly.pylatest_pip_scipy_dev (last failure: Aug 28, 2025) ⚠️
**CI is still failing on [Linux_Nightly.pylatest_pip_scipy_dev](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=79396&view=logs&j=dfe99b15-50db-5d7b-b1e9-4105c42527cf)** (Aug 28, 2025)
Unable to find junit file.... | 32,022 | [
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0.059... |
https://github.com/scikit-learn/scikit-learn/issues/32022 | [
"Bug"
] | ⚠️ CI failed on Linux_Nightly.pylatest_pip_scipy_dev (last failure: Aug 28, 2025) ⚠️
**CI is still failing on [Linux_Nightly.pylatest_pip_scipy_dev](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=79396&view=logs&j=dfe99b15-50db-5d7b-b1e9-4105c42527cf)** (Aug 28, 2025)
Unable to find junit file.... | 32,022 | [
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https://github.com/scikit-learn/scikit-learn/issues/31989 | [
"New Feature",
"Hard",
"module:cluster",
"Needs Decision - Include Feature"
] | Implementing Divisive Analysis
### Describe the workflow you want to enable
I want to add Divisive Analysis Clustering to base scikit-learn in order to provide more options to developers.
"Divisive methods start when all objects are together (that is, at step 0 there is one cluster) and in each following step a clust... | 31,989 | [
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0.0... |
https://github.com/scikit-learn/scikit-learn/issues/31989 | [
"New Feature",
"Hard",
"module:cluster",
"Needs Decision - Include Feature"
] | Implementing Divisive Analysis
### Describe the workflow you want to enable
I want to add Divisive Analysis Clustering to base scikit-learn in order to provide more options to developers.
"Divisive methods start when all objects are together (that is, at step 0 there is one cluster) and in each following step a clust... | 31,989 | [
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https://github.com/scikit-learn/scikit-learn/issues/31989 | [
"New Feature",
"Hard",
"module:cluster",
"Needs Decision - Include Feature"
] | Implementing Divisive Analysis
### Describe the workflow you want to enable
I want to add Divisive Analysis Clustering to base scikit-learn in order to provide more options to developers.
"Divisive methods start when all objects are together (that is, at step 0 there is one cluster) and in each following step a clust... | 31,989 | [
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https://github.com/scikit-learn/scikit-learn/issues/31989 | [
"New Feature",
"Hard",
"module:cluster",
"Needs Decision - Include Feature"
] | Implementing Divisive Analysis
### Describe the workflow you want to enable
I want to add Divisive Analysis Clustering to base scikit-learn in order to provide more options to developers.
"Divisive methods start when all objects are together (that is, at step 0 there is one cluster) and in each following step a clust... | 31,989 | [
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https://github.com/scikit-learn/scikit-learn/issues/31988 | [
"Bug",
"Needs Investigation"
] | Different Results on ARM and x86 when using `RFECV(RandomForestClassifier())`
### Describe the bug
When using `RFECV(RandomForestClassifier())` with `sklearn=1.7.1` with `numpy>=2.0.0`, I am seeing significant discrepancies in floating point results between ARM Macs and x86 Macs/Linux machines. This discrepancy goes... | 31,988 | [
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0.020383836701512337,
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0.02679622545838356,
0.04919494688510895,
-0.01... |
https://github.com/scikit-learn/scikit-learn/issues/31988 | [
"Bug",
"Needs Investigation"
] | Different Results on ARM and x86 when using `RFECV(RandomForestClassifier())`
### Describe the bug
When using `RFECV(RandomForestClassifier())` with `sklearn=1.7.1` with `numpy>=2.0.0`, I am seeing significant discrepancies in floating point results between ARM Macs and x86 Macs/Linux machines. This discrepancy goes... | 31,988 | [
-0.004818593617528677,
-0.03781924024224281,
-0.0036513833329081535,
0.020383836701512337,
0.03207544982433319,
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-0.010117234662175179,
0.023339003324508667,
0.0041705840267241,
0.018191764131188393,
0.008026855066418648,
0.02679622545838356,
0.04919494688510895,
-0.01... |
https://github.com/scikit-learn/scikit-learn/issues/31988 | [
"Bug",
"Needs Investigation"
] | Different Results on ARM and x86 when using `RFECV(RandomForestClassifier())`
### Describe the bug
When using `RFECV(RandomForestClassifier())` with `sklearn=1.7.1` with `numpy>=2.0.0`, I am seeing significant discrepancies in floating point results between ARM Macs and x86 Macs/Linux machines. This discrepancy goes... | 31,988 | [
-0.004818593617528677,
-0.03781924024224281,
-0.0036513833329081535,
0.020383836701512337,
0.03207544982433319,
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0.023339003324508667,
0.0041705840267241,
0.018191764131188393,
0.008026855066418648,
0.02679622545838356,
0.04919494688510895,
-0.01... |
https://github.com/scikit-learn/scikit-learn/issues/31988 | [
"Bug",
"Needs Investigation"
] | Different Results on ARM and x86 when using `RFECV(RandomForestClassifier())`
### Describe the bug
When using `RFECV(RandomForestClassifier())` with `sklearn=1.7.1` with `numpy>=2.0.0`, I am seeing significant discrepancies in floating point results between ARM Macs and x86 Macs/Linux machines. This discrepancy goes... | 31,988 | [
-0.004818593617528677,
-0.03781924024224281,
-0.0036513833329081535,
0.020383836701512337,
0.03207544982433319,
-0.01960388943552971,
-0.010117234662175179,
0.023339003324508667,
0.0041705840267241,
0.018191764131188393,
0.008026855066418648,
0.02679622545838356,
0.04919494688510895,
-0.01... |
https://github.com/scikit-learn/scikit-learn/issues/31988 | [
"Bug",
"Needs Investigation"
] | Different Results on ARM and x86 when using `RFECV(RandomForestClassifier())`
### Describe the bug
When using `RFECV(RandomForestClassifier())` with `sklearn=1.7.1` with `numpy>=2.0.0`, I am seeing significant discrepancies in floating point results between ARM Macs and x86 Macs/Linux machines. This discrepancy goes... | 31,988 | [
-0.004818593617528677,
-0.03781924024224281,
-0.0036513833329081535,
0.020383836701512337,
0.03207544982433319,
-0.01960388943552971,
-0.010117234662175179,
0.023339003324508667,
0.0041705840267241,
0.018191764131188393,
0.008026855066418648,
0.02679622545838356,
0.04919494688510895,
-0.01... |
https://github.com/scikit-learn/scikit-learn/issues/31988 | [
"Bug",
"Needs Investigation"
] | Different Results on ARM and x86 when using `RFECV(RandomForestClassifier())`
### Describe the bug
When using `RFECV(RandomForestClassifier())` with `sklearn=1.7.1` with `numpy>=2.0.0`, I am seeing significant discrepancies in floating point results between ARM Macs and x86 Macs/Linux machines. This discrepancy goes... | 31,988 | [
-0.004818593617528677,
-0.03781924024224281,
-0.0036513833329081535,
0.020383836701512337,
0.03207544982433319,
-0.01960388943552971,
-0.010117234662175179,
0.023339003324508667,
0.0041705840267241,
0.018191764131188393,
0.008026855066418648,
0.02679622545838356,
0.04919494688510895,
-0.01... |
https://github.com/scikit-learn/scikit-learn/issues/31978 | [
"spam"
] | Create troubleshooting guide
## 🔧 Troubleshooting Guide
### Description
A troubleshooting guide would help users solve common problems.
### Suggested content:
- Common error messages and solutions
- Installation troubleshooting
- Configuration issues
- Performance problems
### Benefits:
- Reduces support burden
- ... | 31,978 | [
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0.061975866... |
https://github.com/scikit-learn/scikit-learn/issues/31976 | [
"spam"
] | Add beginner-friendly examples
## 🎯 Beginner Examples Request
### Description
It would be great to have more beginner-friendly examples in the project.
### Suggested additions:
- Simple "Hello World" examples
- Step-by-step tutorials
- Common use case demonstrations
- Code comments for clarity
### Why this matters... | 31,976 | [
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0.0... |
https://github.com/scikit-learn/scikit-learn/issues/31974 | [
"Bug"
] | ⚠️ CI failed on Wheel builder (last failure: Aug 22, 2025) ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/17145548838)** (Aug 22, 2025)
COMMENT:
Needs to be looked at in more details. Seems like a variation of https://github.com/scikit-learn/scikit-learn/issues/3... | 31,974 | [
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0.... |
https://github.com/scikit-learn/scikit-learn/issues/31971 | [
"Bug"
] | ValueError in PLSRegression.fit() with zero-variance predictor
### Describe the bug
Related: https://github.com/scipy/scipy/commit/5bc3d8814d566ef328f41cfa69ccd797c68b0d02
When fitting a PLSRegression model, if the input array X contains a feature with zero variance (i.e., a constant column), the fit method raises a... | 31,971 | [
-0.028920726850628853,
-0.03567645326256752,
0.03720388561487198,
0.02555125765502453,
0.12422328442335129,
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0.02220010943710804,
0.018494579941034317,
0.029480893164873123,
0.007614751812070608,
0.05266968905925751,
0.04598011448979378,
0.03330438956618309,
0.0334563... |
https://github.com/scikit-learn/scikit-learn/issues/31971 | [
"Bug"
] | ValueError in PLSRegression.fit() with zero-variance predictor
### Describe the bug
Related: https://github.com/scipy/scipy/commit/5bc3d8814d566ef328f41cfa69ccd797c68b0d02
When fitting a PLSRegression model, if the input array X contains a feature with zero variance (i.e., a constant column), the fit method raises a... | 31,971 | [
-0.028920726850628853,
-0.03567645326256752,
0.03720388561487198,
0.02555125765502453,
0.12422328442335129,
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0.02220010943710804,
0.018494579941034317,
0.029480893164873123,
0.007614751812070608,
0.05266968905925751,
0.04598011448979378,
0.03330438956618309,
0.0334563... |
https://github.com/scikit-learn/scikit-learn/issues/31971 | [
"Bug"
] | ValueError in PLSRegression.fit() with zero-variance predictor
### Describe the bug
Related: https://github.com/scipy/scipy/commit/5bc3d8814d566ef328f41cfa69ccd797c68b0d02
When fitting a PLSRegression model, if the input array X contains a feature with zero variance (i.e., a constant column), the fit method raises a... | 31,971 | [
-0.028920726850628853,
-0.03567645326256752,
0.03720388561487198,
0.02555125765502453,
0.12422328442335129,
-0.006123135797679424,
0.02220010943710804,
0.018494579941034317,
0.029480893164873123,
0.007614751812070608,
0.05266968905925751,
0.04598011448979378,
0.03330438956618309,
0.0334563... |
https://github.com/scikit-learn/scikit-learn/issues/31971 | [
"Bug"
] | ValueError in PLSRegression.fit() with zero-variance predictor
### Describe the bug
Related: https://github.com/scipy/scipy/commit/5bc3d8814d566ef328f41cfa69ccd797c68b0d02
When fitting a PLSRegression model, if the input array X contains a feature with zero variance (i.e., a constant column), the fit method raises a... | 31,971 | [
-0.028920726850628853,
-0.03567645326256752,
0.03720388561487198,
0.02555125765502453,
0.12422328442335129,
-0.006123135797679424,
0.02220010943710804,
0.018494579941034317,
0.029480893164873123,
0.007614751812070608,
0.05266968905925751,
0.04598011448979378,
0.03330438956618309,
0.0334563... |
https://github.com/scikit-learn/scikit-learn/issues/31971 | [
"Bug"
] | ValueError in PLSRegression.fit() with zero-variance predictor
### Describe the bug
Related: https://github.com/scipy/scipy/commit/5bc3d8814d566ef328f41cfa69ccd797c68b0d02
When fitting a PLSRegression model, if the input array X contains a feature with zero variance (i.e., a constant column), the fit method raises a... | 31,971 | [
-0.028920726850628853,
-0.03567645326256752,
0.03720388561487198,
0.02555125765502453,
0.12422328442335129,
-0.006123135797679424,
0.02220010943710804,
0.018494579941034317,
0.029480893164873123,
0.007614751812070608,
0.05266968905925751,
0.04598011448979378,
0.03330438956618309,
0.0334563... |
https://github.com/scikit-learn/scikit-learn/issues/31971 | [
"Bug"
] | ValueError in PLSRegression.fit() with zero-variance predictor
### Describe the bug
Related: https://github.com/scipy/scipy/commit/5bc3d8814d566ef328f41cfa69ccd797c68b0d02
When fitting a PLSRegression model, if the input array X contains a feature with zero variance (i.e., a constant column), the fit method raises a... | 31,971 | [
-0.028920726850628853,
-0.03567645326256752,
0.03720388561487198,
0.02555125765502453,
0.12422328442335129,
-0.006123135797679424,
0.02220010943710804,
0.018494579941034317,
0.029480893164873123,
0.007614751812070608,
0.05266968905925751,
0.04598011448979378,
0.03330438956618309,
0.0334563... |
https://github.com/scikit-learn/scikit-learn/issues/31970 | [
"spam"
] | Create troubleshooting guide
## 🔧 Troubleshooting Guide
### Description
A troubleshooting guide would help users solve common problems.
### Suggested content:
- Common error messages and solutions
- Installation troubleshooting
- Configuration issues
- Performance problems
### Benefits:
- Reduces support burden
- ... | 31,970 | [
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0.0043035331182181835,
... |
https://github.com/scikit-learn/scikit-learn/issues/31968 | [
"Needs Triage"
] | ⚠️ CI failed on Linux.pylatest_pip_openblas_pandas (last failure: Aug 19, 2025) ⚠️
**CI failed on [Linux.pylatest_pip_openblas_pandas](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=79175&view=logs&j=78a0bf4f-79e5-5387-94ec-13e67d216d6e)** (Aug 19, 2025)
- test_sparse_matmul_to_dense[23-float32... | 31,968 | [
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0.0036189784295856953,
0.066... |
https://github.com/scikit-learn/scikit-learn/issues/31968 | [
"Needs Triage"
] | ⚠️ CI failed on Linux.pylatest_pip_openblas_pandas (last failure: Aug 19, 2025) ⚠️
**CI failed on [Linux.pylatest_pip_openblas_pandas](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=79175&view=logs&j=78a0bf4f-79e5-5387-94ec-13e67d216d6e)** (Aug 19, 2025)
- test_sparse_matmul_to_dense[23-float32... | 31,968 | [
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0.066... |
https://github.com/scikit-learn/scikit-learn/issues/31965 | [
"Documentation"
] | a11y - scikit-learn docs accessibility audit and remediation
### Description
**Note:** This is scoped as part of an ongoing NASA ROSES grant in collaboration with Quansight; as such, a couple of us at Quansight will take on the work outlined in this issue.
Per the NASA ROSES grant, we will conduct an accessibility r... | 31,965 | [
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https://github.com/scikit-learn/scikit-learn/issues/31965 | [
"Documentation"
] | a11y - scikit-learn docs accessibility audit and remediation
### Description
**Note:** This is scoped as part of an ongoing NASA ROSES grant in collaboration with Quansight; as such, a couple of us at Quansight will take on the work outlined in this issue.
Per the NASA ROSES grant, we will conduct an accessibility r... | 31,965 | [
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https://github.com/scikit-learn/scikit-learn/issues/31965 | [
"Documentation"
] | a11y - scikit-learn docs accessibility audit and remediation
### Description
**Note:** This is scoped as part of an ongoing NASA ROSES grant in collaboration with Quansight; as such, a couple of us at Quansight will take on the work outlined in this issue.
Per the NASA ROSES grant, we will conduct an accessibility r... | 31,965 | [
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https://github.com/scikit-learn/scikit-learn/issues/31965 | [
"Documentation"
] | a11y - scikit-learn docs accessibility audit and remediation
### Description
**Note:** This is scoped as part of an ongoing NASA ROSES grant in collaboration with Quansight; as such, a couple of us at Quansight will take on the work outlined in this issue.
Per the NASA ROSES grant, we will conduct an accessibility r... | 31,965 | [
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https://github.com/scikit-learn/scikit-learn/issues/31955 | [
"Needs Triage"
] | ⚠️ CI failed on Wheel builder (last failure: Aug 19, 2025) ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/17059042784)** (Aug 19, 2025)
COMMENT:
This seems to have been noticed in https://github.com/probabl-ai/skore/pull/1982. For some reason that needs to be deb... | 31,955 | [
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https://github.com/scikit-learn/scikit-learn/issues/31955 | [
"Needs Triage"
] | ⚠️ CI failed on Wheel builder (last failure: Aug 19, 2025) ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/17059042784)** (Aug 19, 2025)
COMMENT:
I opened https://github.com/scikit-learn/scikit-learn/pull/31964 as a work-around in scikit-learn.
I opened https://g... | 31,955 | [
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0.03395288810133934,
0.06975626200437546,
0.05849447473883629,
-0.012805583886802197,
0.066... |
https://github.com/scikit-learn/scikit-learn/issues/31947 | [
"Bug"
] | UserWarning: X has feature names, but PowerTransformer was fitted without feature names
### Describe the bug
When using pandas dataframes and a `TransformedTargetRegressor` with `PowerTransformer` with `set_output(transform="pandas")`, I get this warning:
> UserWarning: X has feature names, but PowerTransformer was ... | 31,947 | [
0.00538224633783102,
0.01592894271016121,
0.02485724724829197,
-0.030433256179094315,
0.07637123763561249,
0.015852851793169975,
0.08001965284347534,
0.02407625876367092,
-0.005970519967377186,
0.04605073481798172,
0.041961126029491425,
-0.015075234696269035,
0.047443509101867676,
0.054348... |
https://github.com/scikit-learn/scikit-learn/issues/31947 | [
"Bug"
] | UserWarning: X has feature names, but PowerTransformer was fitted without feature names
### Describe the bug
When using pandas dataframes and a `TransformedTargetRegressor` with `PowerTransformer` with `set_output(transform="pandas")`, I get this warning:
> UserWarning: X has feature names, but PowerTransformer was ... | 31,947 | [
0.00538224633783102,
0.01592894271016121,
0.02485724724829197,
-0.030433256179094315,
0.07637123763561249,
0.015852851793169975,
0.08001965284347534,
0.02407625876367092,
-0.005970519967377186,
0.04605073481798172,
0.041961126029491425,
-0.015075234696269035,
0.047443509101867676,
0.054348... |
https://github.com/scikit-learn/scikit-learn/issues/31947 | [
"Bug"
] | UserWarning: X has feature names, but PowerTransformer was fitted without feature names
### Describe the bug
When using pandas dataframes and a `TransformedTargetRegressor` with `PowerTransformer` with `set_output(transform="pandas")`, I get this warning:
> UserWarning: X has feature names, but PowerTransformer was ... | 31,947 | [
0.00538224633783102,
0.01592894271016121,
0.02485724724829197,
-0.030433256179094315,
0.07637123763561249,
0.015852851793169975,
0.08001965284347534,
0.02407625876367092,
-0.005970519967377186,
0.04605073481798172,
0.041961126029491425,
-0.015075234696269035,
0.047443509101867676,
0.054348... |
https://github.com/scikit-learn/scikit-learn/issues/31947 | [
"Bug"
] | UserWarning: X has feature names, but PowerTransformer was fitted without feature names
### Describe the bug
When using pandas dataframes and a `TransformedTargetRegressor` with `PowerTransformer` with `set_output(transform="pandas")`, I get this warning:
> UserWarning: X has feature names, but PowerTransformer was ... | 31,947 | [
0.00538224633783102,
0.01592894271016121,
0.02485724724829197,
-0.030433256179094315,
0.07637123763561249,
0.015852851793169975,
0.08001965284347534,
0.02407625876367092,
-0.005970519967377186,
0.04605073481798172,
0.041961126029491425,
-0.015075234696269035,
0.047443509101867676,
0.054348... |
https://github.com/scikit-learn/scikit-learn/issues/31947 | [
"Bug"
] | UserWarning: X has feature names, but PowerTransformer was fitted without feature names
### Describe the bug
When using pandas dataframes and a `TransformedTargetRegressor` with `PowerTransformer` with `set_output(transform="pandas")`, I get this warning:
> UserWarning: X has feature names, but PowerTransformer was ... | 31,947 | [
0.00538224633783102,
0.01592894271016121,
0.02485724724829197,
-0.030433256179094315,
0.07637123763561249,
0.015852851793169975,
0.08001965284347534,
0.02407625876367092,
-0.005970519967377186,
0.04605073481798172,
0.041961126029491425,
-0.015075234696269035,
0.047443509101867676,
0.054348... |
https://github.com/scikit-learn/scikit-learn/issues/31947 | [
"Bug"
] | UserWarning: X has feature names, but PowerTransformer was fitted without feature names
### Describe the bug
When using pandas dataframes and a `TransformedTargetRegressor` with `PowerTransformer` with `set_output(transform="pandas")`, I get this warning:
> UserWarning: X has feature names, but PowerTransformer was ... | 31,947 | [
0.00538224633783102,
0.01592894271016121,
0.02485724724829197,
-0.030433256179094315,
0.07637123763561249,
0.015852851793169975,
0.08001965284347534,
0.02407625876367092,
-0.005970519967377186,
0.04605073481798172,
0.041961126029491425,
-0.015075234696269035,
0.047443509101867676,
0.054348... |
https://github.com/scikit-learn/scikit-learn/issues/31947 | [
"Bug"
] | UserWarning: X has feature names, but PowerTransformer was fitted without feature names
### Describe the bug
When using pandas dataframes and a `TransformedTargetRegressor` with `PowerTransformer` with `set_output(transform="pandas")`, I get this warning:
> UserWarning: X has feature names, but PowerTransformer was ... | 31,947 | [
0.00538224633783102,
0.01592894271016121,
0.02485724724829197,
-0.030433256179094315,
0.07637123763561249,
0.015852851793169975,
0.08001965284347534,
0.02407625876367092,
-0.005970519967377186,
0.04605073481798172,
0.041961126029491425,
-0.015075234696269035,
0.047443509101867676,
0.054348... |
https://github.com/scikit-learn/scikit-learn/issues/31947 | [
"Bug"
] | UserWarning: X has feature names, but PowerTransformer was fitted without feature names
### Describe the bug
When using pandas dataframes and a `TransformedTargetRegressor` with `PowerTransformer` with `set_output(transform="pandas")`, I get this warning:
> UserWarning: X has feature names, but PowerTransformer was ... | 31,947 | [
0.00538224633783102,
0.01592894271016121,
0.02485724724829197,
-0.030433256179094315,
0.07637123763561249,
0.015852851793169975,
0.08001965284347534,
0.02407625876367092,
-0.005970519967377186,
0.04605073481798172,
0.041961126029491425,
-0.015075234696269035,
0.047443509101867676,
0.054348... |
https://github.com/scikit-learn/scikit-learn/issues/31940 | [
"module:datasets"
] | Diabetes data should match the original source
### Describe the bug
When `load_diabetes` is called with `scaled=False`, the `s5` attribute has some values with insufficient precision:
All values should stay equal when rounded to 4 decimals, but 11 of them don't.
This is caused by the fact that the unpacked `sklearn/... | 31,940 | [
0.03249890357255936,
-0.023578867316246033,
0.016733257099986076,
0.009702309966087341,
0.07942492514848709,
0.0072695291601121426,
0.015027813613414764,
0.007978282868862152,
0.018542267382144928,
0.005539547652006149,
0.007403386756777763,
-0.003402884816750884,
0.04887545481324196,
0.04... |
https://github.com/scikit-learn/scikit-learn/issues/31940 | [
"module:datasets"
] | Diabetes data should match the original source
### Describe the bug
When `load_diabetes` is called with `scaled=False`, the `s5` attribute has some values with insufficient precision:
All values should stay equal when rounded to 4 decimals, but 11 of them don't.
This is caused by the fact that the unpacked `sklearn/... | 31,940 | [
0.03249890357255936,
-0.023578867316246033,
0.016733257099986076,
0.009702309966087341,
0.07942492514848709,
0.0072695291601121426,
0.015027813613414764,
0.007978282868862152,
0.018542267382144928,
0.005539547652006149,
0.007403386756777763,
-0.003402884816750884,
0.04887545481324196,
0.04... |
https://github.com/scikit-learn/scikit-learn/issues/31940 | [
"module:datasets"
] | Diabetes data should match the original source
### Describe the bug
When `load_diabetes` is called with `scaled=False`, the `s5` attribute has some values with insufficient precision:
All values should stay equal when rounded to 4 decimals, but 11 of them don't.
This is caused by the fact that the unpacked `sklearn/... | 31,940 | [
0.03249890357255936,
-0.023578867316246033,
0.016733257099986076,
0.009702309966087341,
0.07942492514848709,
0.0072695291601121426,
0.015027813613414764,
0.007978282868862152,
0.018542267382144928,
0.005539547652006149,
0.007403386756777763,
-0.003402884816750884,
0.04887545481324196,
0.04... |
https://github.com/scikit-learn/scikit-learn/issues/31940 | [
"module:datasets"
] | Diabetes data should match the original source
### Describe the bug
When `load_diabetes` is called with `scaled=False`, the `s5` attribute has some values with insufficient precision:
All values should stay equal when rounded to 4 decimals, but 11 of them don't.
This is caused by the fact that the unpacked `sklearn/... | 31,940 | [
0.03249890357255936,
-0.023578867316246033,
0.016733257099986076,
0.009702309966087341,
0.07942492514848709,
0.0072695291601121426,
0.015027813613414764,
0.007978282868862152,
0.018542267382144928,
0.005539547652006149,
0.007403386756777763,
-0.003402884816750884,
0.04887545481324196,
0.04... |
https://github.com/scikit-learn/scikit-learn/issues/31940 | [
"module:datasets"
] | Diabetes data should match the original source
### Describe the bug
When `load_diabetes` is called with `scaled=False`, the `s5` attribute has some values with insufficient precision:
All values should stay equal when rounded to 4 decimals, but 11 of them don't.
This is caused by the fact that the unpacked `sklearn/... | 31,940 | [
0.03249890357255936,
-0.023578867316246033,
0.016733257099986076,
0.009702309966087341,
0.07942492514848709,
0.0072695291601121426,
0.015027813613414764,
0.007978282868862152,
0.018542267382144928,
0.005539547652006149,
0.007403386756777763,
-0.003402884816750884,
0.04887545481324196,
0.04... |
https://github.com/scikit-learn/scikit-learn/issues/31940 | [
"module:datasets"
] | Diabetes data should match the original source
### Describe the bug
When `load_diabetes` is called with `scaled=False`, the `s5` attribute has some values with insufficient precision:
All values should stay equal when rounded to 4 decimals, but 11 of them don't.
This is caused by the fact that the unpacked `sklearn/... | 31,940 | [
0.03249890357255936,
-0.023578867316246033,
0.016733257099986076,
0.009702309966087341,
0.07942492514848709,
0.0072695291601121426,
0.015027813613414764,
0.007978282868862152,
0.018542267382144928,
0.005539547652006149,
0.007403386756777763,
-0.003402884816750884,
0.04887545481324196,
0.04... |
https://github.com/scikit-learn/scikit-learn/issues/31940 | [
"module:datasets"
] | Diabetes data should match the original source
### Describe the bug
When `load_diabetes` is called with `scaled=False`, the `s5` attribute has some values with insufficient precision:
All values should stay equal when rounded to 4 decimals, but 11 of them don't.
This is caused by the fact that the unpacked `sklearn/... | 31,940 | [
0.03249890357255936,
-0.023578867316246033,
0.016733257099986076,
0.009702309966087341,
0.07942492514848709,
0.0072695291601121426,
0.015027813613414764,
0.007978282868862152,
0.018542267382144928,
0.005539547652006149,
0.007403386756777763,
-0.003402884816750884,
0.04887545481324196,
0.04... |
https://github.com/scikit-learn/scikit-learn/issues/31940 | [
"module:datasets"
] | Diabetes data should match the original source
### Describe the bug
When `load_diabetes` is called with `scaled=False`, the `s5` attribute has some values with insufficient precision:
All values should stay equal when rounded to 4 decimals, but 11 of them don't.
This is caused by the fact that the unpacked `sklearn/... | 31,940 | [
0.03249890357255936,
-0.023578867316246033,
0.016733257099986076,
0.009702309966087341,
0.07942492514848709,
0.0072695291601121426,
0.015027813613414764,
0.007978282868862152,
0.018542267382144928,
0.005539547652006149,
0.007403386756777763,
-0.003402884816750884,
0.04887545481324196,
0.04... |
https://github.com/scikit-learn/scikit-learn/issues/31931 | [
"Enhancement"
] | Allow common estimator checks to use `xfail_strict=True`
### Describe the workflow you want to enable
I'd like to be able to use [`parametrize_with_checks`](https://scikit-learn.org/stable/modules/generated/sklearn.utils.estimator_checks.parametrize_with_checks.html) and use "strict mode" to notice when checks that a... | 31,931 | [
-0.06284613162279129,
-0.001682046102359891,
0.03837497904896736,
-0.02543640322983265,
0.06419343501329422,
-0.012942320667207241,
0.01456819660961628,
0.03456561267375946,
0.05624949932098389,
0.025895696133375168,
0.04056618735194206,
0.05530284717679024,
-0.03918440267443657,
0.0092171... |
https://github.com/scikit-learn/scikit-learn/issues/31931 | [
"Enhancement"
] | Allow common estimator checks to use `xfail_strict=True`
### Describe the workflow you want to enable
I'd like to be able to use [`parametrize_with_checks`](https://scikit-learn.org/stable/modules/generated/sklearn.utils.estimator_checks.parametrize_with_checks.html) and use "strict mode" to notice when checks that a... | 31,931 | [
-0.06284613162279129,
-0.001682046102359891,
0.03837497904896736,
-0.02543640322983265,
0.06419343501329422,
-0.012942320667207241,
0.01456819660961628,
0.03456561267375946,
0.05624949932098389,
0.025895696133375168,
0.04056618735194206,
0.05530284717679024,
-0.03918440267443657,
0.0092171... |
https://github.com/scikit-learn/scikit-learn/issues/31930 | [
"Documentation"
] | Docs instructions for installing LLVM OpenMP with Homebrew may need updating
### Describe the issue linked to the documentation
Environment variables CFLAGS, CXXFLAGS, CXXFLAGS mentioned here:
https://scikit-learn.org/dev/developers/advanced_installation.html#compiler-macos:~:text=Set%20the%20following%20environment... | 31,930 | [
0.003496210090816021,
-0.035078518092632294,
-0.04128392040729523,
-0.05763404071331024,
0.004872528370469809,
0.03560750186443329,
-0.009403432719409466,
0.010223781690001488,
0.020669804885983467,
0.00496665807440877,
-0.04285553842782974,
0.07395973056554794,
-0.010943413712084293,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/31930 | [
"Documentation"
] | Docs instructions for installing LLVM OpenMP with Homebrew may need updating
### Describe the issue linked to the documentation
Environment variables CFLAGS, CXXFLAGS, CXXFLAGS mentioned here:
https://scikit-learn.org/dev/developers/advanced_installation.html#compiler-macos:~:text=Set%20the%20following%20environment... | 31,930 | [
0.002894103527069092,
-0.033600933849811554,
-0.041729532182216644,
-0.06395253539085388,
0.002000176813453436,
0.031158410012722015,
-0.009817548096179962,
0.010220257565379143,
0.01117529533803463,
0.002670230809599161,
-0.04599728807806969,
0.07887987047433853,
-0.007874705828726292,
-0... |
https://github.com/scikit-learn/scikit-learn/issues/31930 | [
"Documentation"
] | Docs instructions for installing LLVM OpenMP with Homebrew may need updating
### Describe the issue linked to the documentation
Environment variables CFLAGS, CXXFLAGS, CXXFLAGS mentioned here:
https://scikit-learn.org/dev/developers/advanced_installation.html#compiler-macos:~:text=Set%20the%20following%20environment... | 31,930 | [
0.0038629393093287945,
-0.03597579896450043,
-0.03706832975149155,
-0.06177286431193352,
0.0026972368359565735,
0.032141849398612976,
-0.013751961290836334,
0.01235809177160263,
0.017608223482966423,
0.00379249663092196,
-0.047464270144701004,
0.07774992287158966,
-0.009882785379886627,
-0... |
https://github.com/scikit-learn/scikit-learn/issues/31930 | [
"Documentation"
] | Docs instructions for installing LLVM OpenMP with Homebrew may need updating
### Describe the issue linked to the documentation
Environment variables CFLAGS, CXXFLAGS, CXXFLAGS mentioned here:
https://scikit-learn.org/dev/developers/advanced_installation.html#compiler-macos:~:text=Set%20the%20following%20environment... | 31,930 | [
0.0032375124283134937,
-0.030972018837928772,
-0.03774323686957359,
-0.06304793804883957,
0.0020051123574376106,
0.031445130705833435,
-0.012465660460293293,
0.013605189509689808,
0.012017603032290936,
-0.00007353497494477779,
-0.043863262981176376,
0.07852033525705338,
-0.006289837881922722... |
https://github.com/scikit-learn/scikit-learn/issues/31930 | [
"Documentation"
] | Docs instructions for installing LLVM OpenMP with Homebrew may need updating
### Describe the issue linked to the documentation
Environment variables CFLAGS, CXXFLAGS, CXXFLAGS mentioned here:
https://scikit-learn.org/dev/developers/advanced_installation.html#compiler-macos:~:text=Set%20the%20following%20environment... | 31,930 | [
0.011602147482335567,
-0.03982389345765114,
-0.033422742038965225,
-0.07034222036600113,
0.00810610968619585,
0.034967079758644104,
-0.009698244743049145,
0.01471845805644989,
0.01703655906021595,
-0.0019411464454606175,
-0.044216565787792206,
0.07725314050912857,
-0.015357691794633865,
-0... |
https://github.com/scikit-learn/scikit-learn/issues/31930 | [
"Documentation"
] | Docs instructions for installing LLVM OpenMP with Homebrew may need updating
### Describe the issue linked to the documentation
Environment variables CFLAGS, CXXFLAGS, CXXFLAGS mentioned here:
https://scikit-learn.org/dev/developers/advanced_installation.html#compiler-macos:~:text=Set%20the%20following%20environment... | 31,930 | [
0.017691371962428093,
-0.04408711567521095,
-0.02239089645445347,
-0.04882775619626045,
0.01782126910984516,
0.03202187642455101,
0.002458263887092471,
0.010981501080095768,
0.04714711010456085,
0.000871460244525224,
-0.03763342648744583,
0.10195409506559372,
-0.014132129959762096,
-0.0146... |
https://github.com/scikit-learn/scikit-learn/issues/31930 | [
"Documentation"
] | Docs instructions for installing LLVM OpenMP with Homebrew may need updating
### Describe the issue linked to the documentation
Environment variables CFLAGS, CXXFLAGS, CXXFLAGS mentioned here:
https://scikit-learn.org/dev/developers/advanced_installation.html#compiler-macos:~:text=Set%20the%20following%20environment... | 31,930 | [
0.012952121905982494,
-0.040260639041662216,
-0.02810782939195633,
-0.05899742990732193,
0.018912356346845627,
0.034354068338871,
0.005499215796589851,
0.008638609200716019,
0.031510788947343826,
0.0032087191939353943,
-0.03740210831165314,
0.10522925853729248,
-0.013436062261462212,
-0.01... |
https://github.com/scikit-learn/scikit-learn/issues/31930 | [
"Documentation"
] | Docs instructions for installing LLVM OpenMP with Homebrew may need updating
### Describe the issue linked to the documentation
Environment variables CFLAGS, CXXFLAGS, CXXFLAGS mentioned here:
https://scikit-learn.org/dev/developers/advanced_installation.html#compiler-macos:~:text=Set%20the%20following%20environment... | 31,930 | [
-0.0020184593740850687,
-0.030519019812345505,
-0.03878749534487724,
-0.05556400492787361,
0.00947926752269268,
0.037030141800642014,
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0.007203013636171818,
0.021854229271411896,
0.00893819984048605,
-0.0425403006374836,
0.08826372027397156,
-0.013045321218669415,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/31930 | [
"Documentation"
] | Docs instructions for installing LLVM OpenMP with Homebrew may need updating
### Describe the issue linked to the documentation
Environment variables CFLAGS, CXXFLAGS, CXXFLAGS mentioned here:
https://scikit-learn.org/dev/developers/advanced_installation.html#compiler-macos:~:text=Set%20the%20following%20environment... | 31,930 | [
0.008401264436542988,
-0.042899325489997864,
-0.04253755137324333,
-0.07690023630857468,
0.009426473639905453,
0.028920413926243782,
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0.023152263835072517,
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-0.05541207268834114,
0.08348645269870758,
-0.025333238765597343,
... |
https://github.com/scikit-learn/scikit-learn/issues/31930 | [
"Documentation"
] | Docs instructions for installing LLVM OpenMP with Homebrew may need updating
### Describe the issue linked to the documentation
Environment variables CFLAGS, CXXFLAGS, CXXFLAGS mentioned here:
https://scikit-learn.org/dev/developers/advanced_installation.html#compiler-macos:~:text=Set%20the%20following%20environment... | 31,930 | [
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https://github.com/scikit-learn/scikit-learn/issues/31930 | [
"Documentation"
] | Docs instructions for installing LLVM OpenMP with Homebrew may need updating
### Describe the issue linked to the documentation
Environment variables CFLAGS, CXXFLAGS, CXXFLAGS mentioned here:
https://scikit-learn.org/dev/developers/advanced_installation.html#compiler-macos:~:text=Set%20the%20following%20environment... | 31,930 | [
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... |
https://github.com/scikit-learn/scikit-learn/issues/31930 | [
"Documentation"
] | Docs instructions for installing LLVM OpenMP with Homebrew may need updating
### Describe the issue linked to the documentation
Environment variables CFLAGS, CXXFLAGS, CXXFLAGS mentioned here:
https://scikit-learn.org/dev/developers/advanced_installation.html#compiler-macos:~:text=Set%20the%20following%20environment... | 31,930 | [
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https://github.com/scikit-learn/scikit-learn/issues/31925 | [
"New Feature",
"Needs Decision - Include Feature"
] | Add a better implementation of Latent Dirichlet Allocation
### Describe the workflow you want to enable
While this remains to be rigorously tested, the scikit-learn implementation of Latent Dirichlet Allocation is, in the [unanimous experience of topic modelling scholars](https://maria-antoniak.github.io/2022/07/27/t... | 31,925 | [
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0... |
https://github.com/scikit-learn/scikit-learn/issues/31925 | [
"New Feature",
"Needs Decision - Include Feature"
] | Add a better implementation of Latent Dirichlet Allocation
### Describe the workflow you want to enable
While this remains to be rigorously tested, the scikit-learn implementation of Latent Dirichlet Allocation is, in the [unanimous experience of topic modelling scholars](https://maria-antoniak.github.io/2022/07/27/t... | 31,925 | [
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https://github.com/scikit-learn/scikit-learn/issues/31925 | [
"New Feature",
"Needs Decision - Include Feature"
] | Add a better implementation of Latent Dirichlet Allocation
### Describe the workflow you want to enable
While this remains to be rigorously tested, the scikit-learn implementation of Latent Dirichlet Allocation is, in the [unanimous experience of topic modelling scholars](https://maria-antoniak.github.io/2022/07/27/t... | 31,925 | [
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... |
https://github.com/scikit-learn/scikit-learn/issues/31925 | [
"New Feature",
"Needs Decision - Include Feature"
] | Add a better implementation of Latent Dirichlet Allocation
### Describe the workflow you want to enable
While this remains to be rigorously tested, the scikit-learn implementation of Latent Dirichlet Allocation is, in the [unanimous experience of topic modelling scholars](https://maria-antoniak.github.io/2022/07/27/t... | 31,925 | [
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0... |
https://github.com/scikit-learn/scikit-learn/issues/31925 | [
"New Feature",
"Needs Decision - Include Feature"
] | Add a better implementation of Latent Dirichlet Allocation
### Describe the workflow you want to enable
While this remains to be rigorously tested, the scikit-learn implementation of Latent Dirichlet Allocation is, in the [unanimous experience of topic modelling scholars](https://maria-antoniak.github.io/2022/07/27/t... | 31,925 | [
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... |
https://github.com/scikit-learn/scikit-learn/issues/31925 | [
"New Feature",
"Needs Decision - Include Feature"
] | Add a better implementation of Latent Dirichlet Allocation
### Describe the workflow you want to enable
While this remains to be rigorously tested, the scikit-learn implementation of Latent Dirichlet Allocation is, in the [unanimous experience of topic modelling scholars](https://maria-antoniak.github.io/2022/07/27/t... | 31,925 | [
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https://github.com/scikit-learn/scikit-learn/issues/31925 | [
"New Feature",
"Needs Decision - Include Feature"
] | Add a better implementation of Latent Dirichlet Allocation
### Describe the workflow you want to enable
While this remains to be rigorously tested, the scikit-learn implementation of Latent Dirichlet Allocation is, in the [unanimous experience of topic modelling scholars](https://maria-antoniak.github.io/2022/07/27/t... | 31,925 | [
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... |
https://github.com/scikit-learn/scikit-learn/issues/31925 | [
"New Feature",
"Needs Decision - Include Feature"
] | Add a better implementation of Latent Dirichlet Allocation
### Describe the workflow you want to enable
While this remains to be rigorously tested, the scikit-learn implementation of Latent Dirichlet Allocation is, in the [unanimous experience of topic modelling scholars](https://maria-antoniak.github.io/2022/07/27/t... | 31,925 | [
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https://github.com/scikit-learn/scikit-learn/issues/31925 | [
"New Feature",
"Needs Decision - Include Feature"
] | Add a better implementation of Latent Dirichlet Allocation
### Describe the workflow you want to enable
While this remains to be rigorously tested, the scikit-learn implementation of Latent Dirichlet Allocation is, in the [unanimous experience of topic modelling scholars](https://maria-antoniak.github.io/2022/07/27/t... | 31,925 | [
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https://github.com/scikit-learn/scikit-learn/issues/31925 | [
"New Feature",
"Needs Decision - Include Feature"
] | Add a better implementation of Latent Dirichlet Allocation
### Describe the workflow you want to enable
While this remains to be rigorously tested, the scikit-learn implementation of Latent Dirichlet Allocation is, in the [unanimous experience of topic modelling scholars](https://maria-antoniak.github.io/2022/07/27/t... | 31,925 | [
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https://github.com/scikit-learn/scikit-learn/issues/31925 | [
"New Feature",
"Needs Decision - Include Feature"
] | Add a better implementation of Latent Dirichlet Allocation
### Describe the workflow you want to enable
While this remains to be rigorously tested, the scikit-learn implementation of Latent Dirichlet Allocation is, in the [unanimous experience of topic modelling scholars](https://maria-antoniak.github.io/2022/07/27/t... | 31,925 | [
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0.... |
https://github.com/scikit-learn/scikit-learn/issues/31925 | [
"New Feature",
"Needs Decision - Include Feature"
] | Add a better implementation of Latent Dirichlet Allocation
### Describe the workflow you want to enable
While this remains to be rigorously tested, the scikit-learn implementation of Latent Dirichlet Allocation is, in the [unanimous experience of topic modelling scholars](https://maria-antoniak.github.io/2022/07/27/t... | 31,925 | [
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0.04973277449607849,
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0.04... |
https://github.com/scikit-learn/scikit-learn/issues/31925 | [
"New Feature",
"Needs Decision - Include Feature"
] | Add a better implementation of Latent Dirichlet Allocation
### Describe the workflow you want to enable
While this remains to be rigorously tested, the scikit-learn implementation of Latent Dirichlet Allocation is, in the [unanimous experience of topic modelling scholars](https://maria-antoniak.github.io/2022/07/27/t... | 31,925 | [
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0.... |
https://github.com/scikit-learn/scikit-learn/issues/31925 | [
"New Feature",
"Needs Decision - Include Feature"
] | Add a better implementation of Latent Dirichlet Allocation
### Describe the workflow you want to enable
While this remains to be rigorously tested, the scikit-learn implementation of Latent Dirichlet Allocation is, in the [unanimous experience of topic modelling scholars](https://maria-antoniak.github.io/2022/07/27/t... | 31,925 | [
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0.... |
https://github.com/scikit-learn/scikit-learn/issues/31925 | [
"New Feature",
"Needs Decision - Include Feature"
] | Add a better implementation of Latent Dirichlet Allocation
### Describe the workflow you want to enable
While this remains to be rigorously tested, the scikit-learn implementation of Latent Dirichlet Allocation is, in the [unanimous experience of topic modelling scholars](https://maria-antoniak.github.io/2022/07/27/t... | 31,925 | [
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0.... |
https://github.com/scikit-learn/scikit-learn/issues/31925 | [
"New Feature",
"Needs Decision - Include Feature"
] | Add a better implementation of Latent Dirichlet Allocation
### Describe the workflow you want to enable
While this remains to be rigorously tested, the scikit-learn implementation of Latent Dirichlet Allocation is, in the [unanimous experience of topic modelling scholars](https://maria-antoniak.github.io/2022/07/27/t... | 31,925 | [
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0... |
https://github.com/scikit-learn/scikit-learn/issues/31923 | [
"Bug",
"Needs Triage"
] | 404 when fetching datasets with sklearn.datasets.fetch_openml
### Describe the bug
My Azure DevOps pipeline started failing to fetch data from OpenML with 404 as of 9 August. My original line in a Jupyter notebook uses `fetch_openml(name='SPECT', version=1, parser='auto')`; but I've not been able to download any othe... | 31,923 | [
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0.0016608356963843107,
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0.044287342578172684,
0.013037833385169506,
... |
https://github.com/scikit-learn/scikit-learn/issues/31923 | [
"Bug",
"Needs Triage"
] | 404 when fetching datasets with sklearn.datasets.fetch_openml
### Describe the bug
My Azure DevOps pipeline started failing to fetch data from OpenML with 404 as of 9 August. My original line in a Jupyter notebook uses `fetch_openml(name='SPECT', version=1, parser='auto')`; but I've not been able to download any othe... | 31,923 | [
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0.0002806775737553835,
0.0016608356963843107,
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0.0027426271699368954,
0.02558932639658451,
-0.014262725599110126,
0.044287342578172684,
0.013037833385169506,
... |
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