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/27186 | [
"Needs Investigation"
] | BUG (maybe) wrong node bound spread in KernelDensity
### Describe the bug
https://github.com/scikit-learn/scikit-learn/blob/a5620f45614ac3f849c430f53146a66319e4908b/sklearn/neighbors/_binary_tree.pxi.tp#L2114-L2116
https://github.com/scikit-learn/scikit-learn/blob/a5620f45614ac3f849c430f53146a66319e4908b/sklearn... | 27,186 |
https://github.com/scikit-learn/scikit-learn/issues/27183 | [
"Needs Triage"
] | AttributeError: 'NoneType' object has no attribute 'split' when running K-means Clustering
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/27182
<div type='discussions-op-text'>
<sup>Originally posted by **Somesh140** August 27, 2023</sup>
```python
`# elbow method
clustering_scor... | 27,183 |
https://github.com/scikit-learn/scikit-learn/issues/27183 | [
"Needs Triage"
] | AttributeError: 'NoneType' object has no attribute 'split' when running K-means Clustering
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/27182
<div type='discussions-op-text'>
<sup>Originally posted by **Somesh140** August 27, 2023</sup>
```python
`# elbow method
clustering_scor... | 27,183 |
https://github.com/scikit-learn/scikit-learn/issues/27183 | [
"Needs Triage"
] | AttributeError: 'NoneType' object has no attribute 'split' when running K-means Clustering
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/27182
<div type='discussions-op-text'>
<sup>Originally posted by **Somesh140** August 27, 2023</sup>
```python
`# elbow method
clustering_scor... | 27,183 |
https://github.com/scikit-learn/scikit-learn/issues/27183 | [
"Needs Triage"
] | AttributeError: 'NoneType' object has no attribute 'split' when running K-means Clustering
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/27182
<div type='discussions-op-text'>
<sup>Originally posted by **Somesh140** August 27, 2023</sup>
```python
`# elbow method
clustering_scor... | 27,183 |
https://github.com/scikit-learn/scikit-learn/issues/27183 | [
"Needs Triage"
] | AttributeError: 'NoneType' object has no attribute 'split' when running K-means Clustering
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/27182
<div type='discussions-op-text'>
<sup>Originally posted by **Somesh140** August 27, 2023</sup>
```python
`# elbow method
clustering_scor... | 27,183 |
https://github.com/scikit-learn/scikit-learn/issues/27183 | [
"Needs Triage"
] | AttributeError: 'NoneType' object has no attribute 'split' when running K-means Clustering
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/27182
<div type='discussions-op-text'>
<sup>Originally posted by **Somesh140** August 27, 2023</sup>
```python
`# elbow method
clustering_scor... | 27,183 |
https://github.com/scikit-learn/scikit-learn/issues/27183 | [
"Needs Triage"
] | AttributeError: 'NoneType' object has no attribute 'split' when running K-means Clustering
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/27182
<div type='discussions-op-text'>
<sup>Originally posted by **Somesh140** August 27, 2023</sup>
```python
`# elbow method
clustering_scor... | 27,183 |
https://github.com/scikit-learn/scikit-learn/issues/27183 | [
"Needs Triage"
] | AttributeError: 'NoneType' object has no attribute 'split' when running K-means Clustering
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/27182
<div type='discussions-op-text'>
<sup>Originally posted by **Somesh140** August 27, 2023</sup>
```python
`# elbow method
clustering_scor... | 27,183 |
https://github.com/scikit-learn/scikit-learn/issues/27183 | [
"Needs Triage"
] | AttributeError: 'NoneType' object has no attribute 'split' when running K-means Clustering
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/27182
<div type='discussions-op-text'>
<sup>Originally posted by **Somesh140** August 27, 2023</sup>
```python
`# elbow method
clustering_scor... | 27,183 |
https://github.com/scikit-learn/scikit-learn/issues/27181 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_Nightly.pylatest_pip_scipy_dev ⚠️
**CI is still failing on [Linux_Nightly.pylatest_pip_scipy_dev](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=58833&view=logs&j=dfe99b15-50db-5d7b-b1e9-4105c42527cf)** (Sep 11, 2023)
- test_multi_target_sparse_regression[dok_array]
COMME... | 27,181 |
https://github.com/scikit-learn/scikit-learn/issues/27181 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_Nightly.pylatest_pip_scipy_dev ⚠️
**CI is still failing on [Linux_Nightly.pylatest_pip_scipy_dev](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=58833&view=logs&j=dfe99b15-50db-5d7b-b1e9-4105c42527cf)** (Sep 11, 2023)
- test_multi_target_sparse_regression[dok_array]
COMME... | 27,181 |
https://github.com/scikit-learn/scikit-learn/issues/27180 | [
"Bug",
"Needs Triage"
] | AttributeError: 'Flags' object has no attribute 'c_contiguous'
### Describe the bug
This is the error I am getting when I run my knn classifier. Everything was fine until last night and I am very puzzled to see this issue this morning. I am new to ML so please help.
```pytb
AttributeError ... | 27,180 |
https://github.com/scikit-learn/scikit-learn/issues/27180 | [
"Bug",
"Needs Triage"
] | AttributeError: 'Flags' object has no attribute 'c_contiguous'
### Describe the bug
This is the error I am getting when I run my knn classifier. Everything was fine until last night and I am very puzzled to see this issue this morning. I am new to ML so please help.
```pytb
AttributeError ... | 27,180 |
https://github.com/scikit-learn/scikit-learn/issues/27180 | [
"Bug",
"Needs Triage"
] | AttributeError: 'Flags' object has no attribute 'c_contiguous'
### Describe the bug
This is the error I am getting when I run my knn classifier. Everything was fine until last night and I am very puzzled to see this issue this morning. I am new to ML so please help.
```pytb
AttributeError ... | 27,180 |
https://github.com/scikit-learn/scikit-learn/issues/27180 | [
"Bug",
"Needs Triage"
] | AttributeError: 'Flags' object has no attribute 'c_contiguous'
### Describe the bug
This is the error I am getting when I run my knn classifier. Everything was fine until last night and I am very puzzled to see this issue this morning. I am new to ML so please help.
```pytb
AttributeError ... | 27,180 |
https://github.com/scikit-learn/scikit-learn/issues/27172 | [
"Bug",
"Needs Triage"
] | incorrect intercept in LinearRegression when `copy_X=False`?
### Describe the bug
The intercept is incorrectly computed when using sample weights and `copy_X=False`.
The docs only say that `X` may be overwritten by setting this flag but the intercept also changes.
### Steps/Code to Reproduce
import numpy a... | 27,172 |
https://github.com/scikit-learn/scikit-learn/issues/27172 | [
"Bug",
"Needs Triage"
] | incorrect intercept in LinearRegression when `copy_X=False`?
### Describe the bug
The intercept is incorrectly computed when using sample weights and `copy_X=False`.
The docs only say that `X` may be overwritten by setting this flag but the intercept also changes.
### Steps/Code to Reproduce
import numpy a... | 27,172 |
https://github.com/scikit-learn/scikit-learn/issues/27159 | [
"Documentation",
"help wanted"
] | RandomForest{Classifier,Regressor} split criterion documentation
### Describe the issue linked to the documentation
There's no where in the documentation that explains what method is used to identify which values to consider as candidate splits. For example, for regression, an exhaustive method would be to sort each ... | 27,159 |
https://github.com/scikit-learn/scikit-learn/issues/27159 | [
"Documentation",
"help wanted"
] | RandomForest{Classifier,Regressor} split criterion documentation
### Describe the issue linked to the documentation
There's no where in the documentation that explains what method is used to identify which values to consider as candidate splits. For example, for regression, an exhaustive method would be to sort each ... | 27,159 |
https://github.com/scikit-learn/scikit-learn/issues/27159 | [
"Documentation",
"help wanted"
] | RandomForest{Classifier,Regressor} split criterion documentation
### Describe the issue linked to the documentation
There's no where in the documentation that explains what method is used to identify which values to consider as candidate splits. For example, for regression, an exhaustive method would be to sort each ... | 27,159 |
https://github.com/scikit-learn/scikit-learn/issues/27159 | [
"Documentation",
"help wanted"
] | RandomForest{Classifier,Regressor} split criterion documentation
### Describe the issue linked to the documentation
There's no where in the documentation that explains what method is used to identify which values to consider as candidate splits. For example, for regression, an exhaustive method would be to sort each ... | 27,159 |
https://github.com/scikit-learn/scikit-learn/issues/27159 | [
"Documentation",
"help wanted"
] | RandomForest{Classifier,Regressor} split criterion documentation
### Describe the issue linked to the documentation
There's no where in the documentation that explains what method is used to identify which values to consider as candidate splits. For example, for regression, an exhaustive method would be to sort each ... | 27,159 |
https://github.com/scikit-learn/scikit-learn/issues/27159 | [
"Documentation",
"help wanted"
] | RandomForest{Classifier,Regressor} split criterion documentation
### Describe the issue linked to the documentation
There's no where in the documentation that explains what method is used to identify which values to consider as candidate splits. For example, for regression, an exhaustive method would be to sort each ... | 27,159 |
https://github.com/scikit-learn/scikit-learn/issues/27159 | [
"Documentation",
"help wanted"
] | RandomForest{Classifier,Regressor} split criterion documentation
### Describe the issue linked to the documentation
There's no where in the documentation that explains what method is used to identify which values to consider as candidate splits. For example, for regression, an exhaustive method would be to sort each ... | 27,159 |
https://github.com/scikit-learn/scikit-learn/issues/27159 | [
"Documentation",
"help wanted"
] | RandomForest{Classifier,Regressor} split criterion documentation
### Describe the issue linked to the documentation
There's no where in the documentation that explains what method is used to identify which values to consider as candidate splits. For example, for regression, an exhaustive method would be to sort each ... | 27,159 |
https://github.com/scikit-learn/scikit-learn/issues/27159 | [
"Documentation",
"help wanted"
] | RandomForest{Classifier,Regressor} split criterion documentation
### Describe the issue linked to the documentation
There's no where in the documentation that explains what method is used to identify which values to consider as candidate splits. For example, for regression, an exhaustive method would be to sort each ... | 27,159 |
https://github.com/scikit-learn/scikit-learn/issues/27159 | [
"Documentation",
"help wanted"
] | RandomForest{Classifier,Regressor} split criterion documentation
### Describe the issue linked to the documentation
There's no where in the documentation that explains what method is used to identify which values to consider as candidate splits. For example, for regression, an exhaustive method would be to sort each ... | 27,159 |
https://github.com/scikit-learn/scikit-learn/issues/27159 | [
"Documentation",
"help wanted"
] | RandomForest{Classifier,Regressor} split criterion documentation
### Describe the issue linked to the documentation
There's no where in the documentation that explains what method is used to identify which values to consider as candidate splits. For example, for regression, an exhaustive method would be to sort each ... | 27,159 |
https://github.com/scikit-learn/scikit-learn/issues/27159 | [
"Documentation",
"help wanted"
] | RandomForest{Classifier,Regressor} split criterion documentation
### Describe the issue linked to the documentation
There's no where in the documentation that explains what method is used to identify which values to consider as candidate splits. For example, for regression, an exhaustive method would be to sort each ... | 27,159 |
https://github.com/scikit-learn/scikit-learn/issues/27159 | [
"Documentation",
"help wanted"
] | RandomForest{Classifier,Regressor} split criterion documentation
### Describe the issue linked to the documentation
There's no where in the documentation that explains what method is used to identify which values to consider as candidate splits. For example, for regression, an exhaustive method would be to sort each ... | 27,159 |
https://github.com/scikit-learn/scikit-learn/issues/27159 | [
"Documentation",
"help wanted"
] | RandomForest{Classifier,Regressor} split criterion documentation
### Describe the issue linked to the documentation
There's no where in the documentation that explains what method is used to identify which values to consider as candidate splits. For example, for regression, an exhaustive method would be to sort each ... | 27,159 |
https://github.com/scikit-learn/scikit-learn/issues/27159 | [
"Documentation",
"help wanted"
] | RandomForest{Classifier,Regressor} split criterion documentation
### Describe the issue linked to the documentation
There's no where in the documentation that explains what method is used to identify which values to consider as candidate splits. For example, for regression, an exhaustive method would be to sort each ... | 27,159 |
https://github.com/scikit-learn/scikit-learn/issues/27159 | [
"Documentation",
"help wanted"
] | RandomForest{Classifier,Regressor} split criterion documentation
### Describe the issue linked to the documentation
There's no where in the documentation that explains what method is used to identify which values to consider as candidate splits. For example, for regression, an exhaustive method would be to sort each ... | 27,159 |
https://github.com/scikit-learn/scikit-learn/issues/27159 | [
"Documentation",
"help wanted"
] | RandomForest{Classifier,Regressor} split criterion documentation
### Describe the issue linked to the documentation
There's no where in the documentation that explains what method is used to identify which values to consider as candidate splits. For example, for regression, an exhaustive method would be to sort each ... | 27,159 |
https://github.com/scikit-learn/scikit-learn/issues/27159 | [
"Documentation",
"help wanted"
] | RandomForest{Classifier,Regressor} split criterion documentation
### Describe the issue linked to the documentation
There's no where in the documentation that explains what method is used to identify which values to consider as candidate splits. For example, for regression, an exhaustive method would be to sort each ... | 27,159 |
https://github.com/scikit-learn/scikit-learn/issues/27159 | [
"Documentation",
"help wanted"
] | RandomForest{Classifier,Regressor} split criterion documentation
### Describe the issue linked to the documentation
There's no where in the documentation that explains what method is used to identify which values to consider as candidate splits. For example, for regression, an exhaustive method would be to sort each ... | 27,159 |
https://github.com/scikit-learn/scikit-learn/issues/27159 | [
"Documentation",
"help wanted"
] | RandomForest{Classifier,Regressor} split criterion documentation
### Describe the issue linked to the documentation
There's no where in the documentation that explains what method is used to identify which values to consider as candidate splits. For example, for regression, an exhaustive method would be to sort each ... | 27,159 |
https://github.com/scikit-learn/scikit-learn/issues/27159 | [
"Documentation",
"help wanted"
] | RandomForest{Classifier,Regressor} split criterion documentation
### Describe the issue linked to the documentation
There's no where in the documentation that explains what method is used to identify which values to consider as candidate splits. For example, for regression, an exhaustive method would be to sort each ... | 27,159 |
https://github.com/scikit-learn/scikit-learn/issues/27159 | [
"Documentation",
"help wanted"
] | RandomForest{Classifier,Regressor} split criterion documentation
### Describe the issue linked to the documentation
There's no where in the documentation that explains what method is used to identify which values to consider as candidate splits. For example, for regression, an exhaustive method would be to sort each ... | 27,159 |
https://github.com/scikit-learn/scikit-learn/issues/27159 | [
"Documentation",
"help wanted"
] | RandomForest{Classifier,Regressor} split criterion documentation
### Describe the issue linked to the documentation
There's no where in the documentation that explains what method is used to identify which values to consider as candidate splits. For example, for regression, an exhaustive method would be to sort each ... | 27,159 |
https://github.com/scikit-learn/scikit-learn/issues/27159 | [
"Documentation",
"help wanted"
] | RandomForest{Classifier,Regressor} split criterion documentation
### Describe the issue linked to the documentation
There's no where in the documentation that explains what method is used to identify which values to consider as candidate splits. For example, for regression, an exhaustive method would be to sort each ... | 27,159 |
https://github.com/scikit-learn/scikit-learn/issues/27159 | [
"Documentation",
"help wanted"
] | RandomForest{Classifier,Regressor} split criterion documentation
### Describe the issue linked to the documentation
There's no where in the documentation that explains what method is used to identify which values to consider as candidate splits. For example, for regression, an exhaustive method would be to sort each ... | 27,159 |
https://github.com/scikit-learn/scikit-learn/issues/27159 | [
"Documentation",
"help wanted"
] | RandomForest{Classifier,Regressor} split criterion documentation
### Describe the issue linked to the documentation
There's no where in the documentation that explains what method is used to identify which values to consider as candidate splits. For example, for regression, an exhaustive method would be to sort each ... | 27,159 |
https://github.com/scikit-learn/scikit-learn/issues/27159 | [
"Documentation",
"help wanted"
] | RandomForest{Classifier,Regressor} split criterion documentation
### Describe the issue linked to the documentation
There's no where in the documentation that explains what method is used to identify which values to consider as candidate splits. For example, for regression, an exhaustive method would be to sort each ... | 27,159 |
https://github.com/scikit-learn/scikit-learn/issues/27159 | [
"Documentation",
"help wanted"
] | RandomForest{Classifier,Regressor} split criterion documentation
### Describe the issue linked to the documentation
There's no where in the documentation that explains what method is used to identify which values to consider as candidate splits. For example, for regression, an exhaustive method would be to sort each ... | 27,159 |
https://github.com/scikit-learn/scikit-learn/issues/27159 | [
"Documentation",
"help wanted"
] | RandomForest{Classifier,Regressor} split criterion documentation
### Describe the issue linked to the documentation
There's no where in the documentation that explains what method is used to identify which values to consider as candidate splits. For example, for regression, an exhaustive method would be to sort each ... | 27,159 |
https://github.com/scikit-learn/scikit-learn/issues/27152 | [
"Documentation",
"Needs Triage"
] | DOC "Copy to clipboard" doesn't copy multiline instructions
### Describe the issue linked to the documentation
For instance in [Getting Started](https://scikit-learn.org/stable/getting_started.html):
The paste... | 27,152 |
https://github.com/scikit-learn/scikit-learn/issues/27152 | [
"Documentation",
"Needs Triage"
] | DOC "Copy to clipboard" doesn't copy multiline instructions
### Describe the issue linked to the documentation
For instance in [Getting Started](https://scikit-learn.org/stable/getting_started.html):
The paste... | 27,152 |
https://github.com/scikit-learn/scikit-learn/issues/27152 | [
"Documentation",
"Needs Triage"
] | DOC "Copy to clipboard" doesn't copy multiline instructions
### Describe the issue linked to the documentation
For instance in [Getting Started](https://scikit-learn.org/stable/getting_started.html):
The paste... | 27,152 |
https://github.com/scikit-learn/scikit-learn/issues/27151 | [
"Documentation",
"RFC"
] | RFC remove some of our examples
TLDR: I think we have too many examples, in particular in
- [clustering](https://scikit-learn.org/stable/auto_examples/index.html#clustering)
- [ensemble](https://scikit-learn.org/stable/auto_examples/index.html#ensemble-methods)
- [generalized-linear-models](https://scikit-learn.org/st... | 27,151 |
https://github.com/scikit-learn/scikit-learn/issues/27151 | [
"Documentation",
"RFC"
] | RFC remove some of our examples
TLDR: I think we have too many examples, in particular in
- [clustering](https://scikit-learn.org/stable/auto_examples/index.html#clustering)
- [ensemble](https://scikit-learn.org/stable/auto_examples/index.html#ensemble-methods)
- [generalized-linear-models](https://scikit-learn.org/st... | 27,151 |
https://github.com/scikit-learn/scikit-learn/issues/27151 | [
"Documentation",
"RFC"
] | RFC remove some of our examples
TLDR: I think we have too many examples, in particular in
- [clustering](https://scikit-learn.org/stable/auto_examples/index.html#clustering)
- [ensemble](https://scikit-learn.org/stable/auto_examples/index.html#ensemble-methods)
- [generalized-linear-models](https://scikit-learn.org/st... | 27,151 |
https://github.com/scikit-learn/scikit-learn/issues/27151 | [
"Documentation",
"RFC"
] | RFC remove some of our examples
TLDR: I think we have too many examples, in particular in
- [clustering](https://scikit-learn.org/stable/auto_examples/index.html#clustering)
- [ensemble](https://scikit-learn.org/stable/auto_examples/index.html#ensemble-methods)
- [generalized-linear-models](https://scikit-learn.org/st... | 27,151 |
https://github.com/scikit-learn/scikit-learn/issues/27151 | [
"Documentation",
"RFC"
] | RFC remove some of our examples
TLDR: I think we have too many examples, in particular in
- [clustering](https://scikit-learn.org/stable/auto_examples/index.html#clustering)
- [ensemble](https://scikit-learn.org/stable/auto_examples/index.html#ensemble-methods)
- [generalized-linear-models](https://scikit-learn.org/st... | 27,151 |
https://github.com/scikit-learn/scikit-learn/issues/27151 | [
"Documentation",
"RFC"
] | RFC remove some of our examples
TLDR: I think we have too many examples, in particular in
- [clustering](https://scikit-learn.org/stable/auto_examples/index.html#clustering)
- [ensemble](https://scikit-learn.org/stable/auto_examples/index.html#ensemble-methods)
- [generalized-linear-models](https://scikit-learn.org/st... | 27,151 |
https://github.com/scikit-learn/scikit-learn/issues/27151 | [
"Documentation",
"RFC"
] | RFC remove some of our examples
TLDR: I think we have too many examples, in particular in
- [clustering](https://scikit-learn.org/stable/auto_examples/index.html#clustering)
- [ensemble](https://scikit-learn.org/stable/auto_examples/index.html#ensemble-methods)
- [generalized-linear-models](https://scikit-learn.org/st... | 27,151 |
https://github.com/scikit-learn/scikit-learn/issues/27151 | [
"Documentation",
"RFC"
] | RFC remove some of our examples
TLDR: I think we have too many examples, in particular in
- [clustering](https://scikit-learn.org/stable/auto_examples/index.html#clustering)
- [ensemble](https://scikit-learn.org/stable/auto_examples/index.html#ensemble-methods)
- [generalized-linear-models](https://scikit-learn.org/st... | 27,151 |
https://github.com/scikit-learn/scikit-learn/issues/27151 | [
"Documentation",
"RFC"
] | RFC remove some of our examples
TLDR: I think we have too many examples, in particular in
- [clustering](https://scikit-learn.org/stable/auto_examples/index.html#clustering)
- [ensemble](https://scikit-learn.org/stable/auto_examples/index.html#ensemble-methods)
- [generalized-linear-models](https://scikit-learn.org/st... | 27,151 |
https://github.com/scikit-learn/scikit-learn/issues/27151 | [
"Documentation",
"RFC"
] | RFC remove some of our examples
TLDR: I think we have too many examples, in particular in
- [clustering](https://scikit-learn.org/stable/auto_examples/index.html#clustering)
- [ensemble](https://scikit-learn.org/stable/auto_examples/index.html#ensemble-methods)
- [generalized-linear-models](https://scikit-learn.org/st... | 27,151 |
https://github.com/scikit-learn/scikit-learn/issues/27151 | [
"Documentation",
"RFC"
] | RFC remove some of our examples
TLDR: I think we have too many examples, in particular in
- [clustering](https://scikit-learn.org/stable/auto_examples/index.html#clustering)
- [ensemble](https://scikit-learn.org/stable/auto_examples/index.html#ensemble-methods)
- [generalized-linear-models](https://scikit-learn.org/st... | 27,151 |
https://github.com/scikit-learn/scikit-learn/issues/27151 | [
"Documentation",
"RFC"
] | RFC remove some of our examples
TLDR: I think we have too many examples, in particular in
- [clustering](https://scikit-learn.org/stable/auto_examples/index.html#clustering)
- [ensemble](https://scikit-learn.org/stable/auto_examples/index.html#ensemble-methods)
- [generalized-linear-models](https://scikit-learn.org/st... | 27,151 |
https://github.com/scikit-learn/scikit-learn/issues/27151 | [
"Documentation",
"RFC"
] | RFC remove some of our examples
TLDR: I think we have too many examples, in particular in
- [clustering](https://scikit-learn.org/stable/auto_examples/index.html#clustering)
- [ensemble](https://scikit-learn.org/stable/auto_examples/index.html#ensemble-methods)
- [generalized-linear-models](https://scikit-learn.org/st... | 27,151 |
https://github.com/scikit-learn/scikit-learn/issues/27151 | [
"Documentation",
"RFC"
] | RFC remove some of our examples
TLDR: I think we have too many examples, in particular in
- [clustering](https://scikit-learn.org/stable/auto_examples/index.html#clustering)
- [ensemble](https://scikit-learn.org/stable/auto_examples/index.html#ensemble-methods)
- [generalized-linear-models](https://scikit-learn.org/st... | 27,151 |
https://github.com/scikit-learn/scikit-learn/issues/27147 | [
"Needs Triage"
] | ⚠️ CI failed on Wheel builder ⚠️
**CI failed on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/5959205563)** (Aug 24, 2023)
COMMENT:
## CI is no longer failing! ✅
[Successful run](https://github.com/scikit-learn/scikit-learn/actions/runs/5971617389) on Aug 25, 2023 | 27,147 |
https://github.com/scikit-learn/scikit-learn/issues/27146 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_nogil.pylatest_pip_nogil ⚠️
**CI failed on [Linux_nogil.pylatest_pip_nogil](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=58261&view=logs&j=67fbb25f-e417-50be-be55-3b1e9637fce5)** (Aug 24, 2023)
- test_pairwise_distances_argkmin[45-float32-parallel_on_X-cityblock-0-500]
-... | 27,146 |
https://github.com/scikit-learn/scikit-learn/issues/27141 | [
"Needs Triage"
] | Make automatic validation for sklearn.utils.extmath._randomized_eigsh
https://github.com/scikit-learn/scikit-learn/blob/7f9bad99d6e0a3e8ddf92a7e5561245224dab102/sklearn/utils/extmath.py#L482
COMMENT:
As explained in the linked PR, we don't want to add validation for this function. | 27,141 |
https://github.com/scikit-learn/scikit-learn/issues/27138 | [
"Needs Triage"
] | ⚠️ CI failed on Linux.pylatest_pip_openblas_pandas ⚠️
**CI failed on [Linux.pylatest_pip_openblas_pandas](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=58207&view=logs&j=78a0bf4f-79e5-5387-94ec-13e67d216d6e)** (Aug 23, 2023)
- test_pairwise_distances_argkmin[45-float32-parallel_on_X-cityblock-... | 27,138 |
https://github.com/scikit-learn/scikit-learn/issues/27127 | [
"New Feature",
"Documentation"
] | DOC Add permalinks to dropdown headers
### Describe the workflow you want to enable
With addition of dropdowns, you can no longer click on them to get a permalink to the header (and manually adding the `#<header>` to the end of the URL will not take you to the header.
Related: https://github.com/scikit-learn/sciki... | 27,127 |
https://github.com/scikit-learn/scikit-learn/issues/27127 | [
"New Feature",
"Documentation"
] | DOC Add permalinks to dropdown headers
### Describe the workflow you want to enable
With addition of dropdowns, you can no longer click on them to get a permalink to the header (and manually adding the `#<header>` to the end of the URL will not take you to the header.
Related: https://github.com/scikit-learn/sciki... | 27,127 |
https://github.com/scikit-learn/scikit-learn/issues/27122 | [
"Needs Triage"
] | ⚠️ CI failed on Linux.py38_conda_defaults_openblas ⚠️
**CI failed on [Linux.py38_conda_defaults_openblas](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=58128&view=logs&j=c8afde5f-ef70-5983-62e8-c6b665ad6161)** (Aug 21, 2023)
- test_pairwise_distances_argkmin[49-float32-parallel_on_X-braycurtis... | 27,122 |
https://github.com/scikit-learn/scikit-learn/issues/27122 | [
"Needs Triage"
] | ⚠️ CI failed on Linux.py38_conda_defaults_openblas ⚠️
**CI failed on [Linux.py38_conda_defaults_openblas](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=58128&view=logs&j=c8afde5f-ef70-5983-62e8-c6b665ad6161)** (Aug 21, 2023)
- test_pairwise_distances_argkmin[49-float32-parallel_on_X-braycurtis... | 27,122 |
https://github.com/scikit-learn/scikit-learn/issues/27122 | [
"Needs Triage"
] | ⚠️ CI failed on Linux.py38_conda_defaults_openblas ⚠️
**CI failed on [Linux.py38_conda_defaults_openblas](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=58128&view=logs&j=c8afde5f-ef70-5983-62e8-c6b665ad6161)** (Aug 21, 2023)
- test_pairwise_distances_argkmin[49-float32-parallel_on_X-braycurtis... | 27,122 |
https://github.com/scikit-learn/scikit-learn/issues/27117 | [
"New Feature",
"Needs Decision",
"module:ensemble"
] | Add sample_weight support to binning in HGBT
Use `sample_weight` in the binning of `HistGradientBoostingClassifier` and `HistGradientBoostingRegressor`, or allow it via an option.
Currently, sample weights are ignored in the `_BinMapper`.
Some more context and history summarized by @NicolasHug [here](https://git... | 27,117 |
https://github.com/scikit-learn/scikit-learn/issues/27117 | [
"New Feature",
"Needs Decision",
"module:ensemble"
] | Add sample_weight support to binning in HGBT
Use `sample_weight` in the binning of `HistGradientBoostingClassifier` and `HistGradientBoostingRegressor`, or allow it via an option.
Currently, sample weights are ignored in the `_BinMapper`.
Some more context and history summarized by @NicolasHug [here](https://git... | 27,117 |
https://github.com/scikit-learn/scikit-learn/issues/27117 | [
"New Feature",
"Needs Decision",
"module:ensemble"
] | Add sample_weight support to binning in HGBT
Use `sample_weight` in the binning of `HistGradientBoostingClassifier` and `HistGradientBoostingRegressor`, or allow it via an option.
Currently, sample weights are ignored in the `_BinMapper`.
Some more context and history summarized by @NicolasHug [here](https://git... | 27,117 |
https://github.com/scikit-learn/scikit-learn/issues/27117 | [
"New Feature",
"Needs Decision",
"module:ensemble"
] | Add sample_weight support to binning in HGBT
Use `sample_weight` in the binning of `HistGradientBoostingClassifier` and `HistGradientBoostingRegressor`, or allow it via an option.
Currently, sample weights are ignored in the `_BinMapper`.
Some more context and history summarized by @NicolasHug [here](https://git... | 27,117 |
https://github.com/scikit-learn/scikit-learn/issues/27117 | [
"New Feature",
"Needs Decision",
"module:ensemble"
] | Add sample_weight support to binning in HGBT
Use `sample_weight` in the binning of `HistGradientBoostingClassifier` and `HistGradientBoostingRegressor`, or allow it via an option.
Currently, sample weights are ignored in the `_BinMapper`.
Some more context and history summarized by @NicolasHug [here](https://git... | 27,117 |
https://github.com/scikit-learn/scikit-learn/issues/27117 | [
"New Feature",
"Needs Decision",
"module:ensemble"
] | Add sample_weight support to binning in HGBT
Use `sample_weight` in the binning of `HistGradientBoostingClassifier` and `HistGradientBoostingRegressor`, or allow it via an option.
Currently, sample weights are ignored in the `_BinMapper`.
Some more context and history summarized by @NicolasHug [here](https://git... | 27,117 |
https://github.com/scikit-learn/scikit-learn/issues/27117 | [
"New Feature",
"Needs Decision",
"module:ensemble"
] | Add sample_weight support to binning in HGBT
Use `sample_weight` in the binning of `HistGradientBoostingClassifier` and `HistGradientBoostingRegressor`, or allow it via an option.
Currently, sample weights are ignored in the `_BinMapper`.
Some more context and history summarized by @NicolasHug [here](https://git... | 27,117 |
https://github.com/scikit-learn/scikit-learn/issues/27109 | [
"New Feature",
"module:ensemble",
"Needs Decision - Include Feature"
] | Add baseline estimator to HGBT
### Describe the workflow you want to enable
I would like to specify a baseline estimator like in `GradientBoostingRegressor(init=MyCoolBaselineEstimator_Maybe_a_linear_model)`.
### Describe your proposed solution
Add a parameter `baseline` (or if has to be the same, then `init`) to `... | 27,109 |
https://github.com/scikit-learn/scikit-learn/issues/27109 | [
"New Feature",
"module:ensemble",
"Needs Decision - Include Feature"
] | Add baseline estimator to HGBT
### Describe the workflow you want to enable
I would like to specify a baseline estimator like in `GradientBoostingRegressor(init=MyCoolBaselineEstimator_Maybe_a_linear_model)`.
### Describe your proposed solution
Add a parameter `baseline` (or if has to be the same, then `init`) to `... | 27,109 |
https://github.com/scikit-learn/scikit-learn/issues/27109 | [
"New Feature",
"module:ensemble",
"Needs Decision - Include Feature"
] | Add baseline estimator to HGBT
### Describe the workflow you want to enable
I would like to specify a baseline estimator like in `GradientBoostingRegressor(init=MyCoolBaselineEstimator_Maybe_a_linear_model)`.
### Describe your proposed solution
Add a parameter `baseline` (or if has to be the same, then `init`) to `... | 27,109 |
https://github.com/scikit-learn/scikit-learn/issues/27109 | [
"New Feature",
"module:ensemble",
"Needs Decision - Include Feature"
] | Add baseline estimator to HGBT
### Describe the workflow you want to enable
I would like to specify a baseline estimator like in `GradientBoostingRegressor(init=MyCoolBaselineEstimator_Maybe_a_linear_model)`.
### Describe your proposed solution
Add a parameter `baseline` (or if has to be the same, then `init`) to `... | 27,109 |
https://github.com/scikit-learn/scikit-learn/issues/27109 | [
"New Feature",
"module:ensemble",
"Needs Decision - Include Feature"
] | Add baseline estimator to HGBT
### Describe the workflow you want to enable
I would like to specify a baseline estimator like in `GradientBoostingRegressor(init=MyCoolBaselineEstimator_Maybe_a_linear_model)`.
### Describe your proposed solution
Add a parameter `baseline` (or if has to be the same, then `init`) to `... | 27,109 |
https://github.com/scikit-learn/scikit-learn/issues/27109 | [
"New Feature",
"module:ensemble",
"Needs Decision - Include Feature"
] | Add baseline estimator to HGBT
### Describe the workflow you want to enable
I would like to specify a baseline estimator like in `GradientBoostingRegressor(init=MyCoolBaselineEstimator_Maybe_a_linear_model)`.
### Describe your proposed solution
Add a parameter `baseline` (or if has to be the same, then `init`) to `... | 27,109 |
https://github.com/scikit-learn/scikit-learn/issues/27105 | [
"Bug",
"Needs Triage"
] | Feature selection estimator class params does not update with pipeline class params for Gridsearch
### Describe the bug
In a pipeline which has a step of feature selection (SelectFromModel with XGB estimator) and a step of XGB class, when Grid Search is used for hyperparameter tuning of a param in XGB, only one ste... | 27,105 |
https://github.com/scikit-learn/scikit-learn/issues/27105 | [
"Bug",
"Needs Triage"
] | Feature selection estimator class params does not update with pipeline class params for Gridsearch
### Describe the bug
In a pipeline which has a step of feature selection (SelectFromModel with XGB estimator) and a step of XGB class, when Grid Search is used for hyperparameter tuning of a param in XGB, only one ste... | 27,105 |
https://github.com/scikit-learn/scikit-learn/issues/27105 | [
"Bug",
"Needs Triage"
] | Feature selection estimator class params does not update with pipeline class params for Gridsearch
### Describe the bug
In a pipeline which has a step of feature selection (SelectFromModel with XGB estimator) and a step of XGB class, when Grid Search is used for hyperparameter tuning of a param in XGB, only one ste... | 27,105 |
https://github.com/scikit-learn/scikit-learn/issues/27105 | [
"Bug",
"Needs Triage"
] | Feature selection estimator class params does not update with pipeline class params for Gridsearch
### Describe the bug
In a pipeline which has a step of feature selection (SelectFromModel with XGB estimator) and a step of XGB class, when Grid Search is used for hyperparameter tuning of a param in XGB, only one ste... | 27,105 |
https://github.com/scikit-learn/scikit-learn/issues/27105 | [
"Bug",
"Needs Triage"
] | Feature selection estimator class params does not update with pipeline class params for Gridsearch
### Describe the bug
In a pipeline which has a step of feature selection (SelectFromModel with XGB estimator) and a step of XGB class, when Grid Search is used for hyperparameter tuning of a param in XGB, only one ste... | 27,105 |
https://github.com/scikit-learn/scikit-learn/issues/27105 | [
"Bug",
"Needs Triage"
] | Feature selection estimator class params does not update with pipeline class params for Gridsearch
### Describe the bug
In a pipeline which has a step of feature selection (SelectFromModel with XGB estimator) and a step of XGB class, when Grid Search is used for hyperparameter tuning of a param in XGB, only one ste... | 27,105 |
https://github.com/scikit-learn/scikit-learn/issues/27092 | [
"Bug",
"Needs Reproducible Code"
] | AttributeError: 'LogisticRegression' object has no attribute 'feature_names_in_'
### Describe the bug
I created two model successfully (one being Decision Tree, and the other Logistic Regression). Those were exported as pickle `.pkl` files. Because I used one-hot encoding in both models and I have a lot of categori... | 27,092 |
https://github.com/scikit-learn/scikit-learn/issues/27092 | [
"Bug",
"Needs Reproducible Code"
] | AttributeError: 'LogisticRegression' object has no attribute 'feature_names_in_'
### Describe the bug
I created two model successfully (one being Decision Tree, and the other Logistic Regression). Those were exported as pickle `.pkl` files. Because I used one-hot encoding in both models and I have a lot of categori... | 27,092 |
https://github.com/scikit-learn/scikit-learn/issues/27092 | [
"Bug",
"Needs Reproducible Code"
] | AttributeError: 'LogisticRegression' object has no attribute 'feature_names_in_'
### Describe the bug
I created two model successfully (one being Decision Tree, and the other Logistic Regression). Those were exported as pickle `.pkl` files. Because I used one-hot encoding in both models and I have a lot of categori... | 27,092 |
https://github.com/scikit-learn/scikit-learn/issues/27092 | [
"Bug",
"Needs Reproducible Code"
] | AttributeError: 'LogisticRegression' object has no attribute 'feature_names_in_'
### Describe the bug
I created two model successfully (one being Decision Tree, and the other Logistic Regression). Those were exported as pickle `.pkl` files. Because I used one-hot encoding in both models and I have a lot of categori... | 27,092 |
https://github.com/scikit-learn/scikit-learn/issues/27090 | [
"Sprint",
"module:test-suite",
"Meta-issue",
"good first PR to review"
] | TST Extend tests for `scipy.sparse.*array`
SciPy sparse matrices (i.e. `scipy.sparse.*matrix`) are tested but their sparse arrays counterpart (i.e. `scipy.sparse.*array`) aren't yet will become ubiquitous (see #26418).
Tests and their parameterizations (when they exist) must be adapted to include `scipy.sparse.*arr... | 27,090 |
https://github.com/scikit-learn/scikit-learn/issues/27090 | [
"Sprint",
"module:test-suite",
"Meta-issue",
"good first PR to review"
] | TST Extend tests for `scipy.sparse.*array`
SciPy sparse matrices (i.e. `scipy.sparse.*matrix`) are tested but their sparse arrays counterpart (i.e. `scipy.sparse.*array`) aren't yet will become ubiquitous (see #26418).
Tests and their parameterizations (when they exist) must be adapted to include `scipy.sparse.*arr... | 27,090 |
https://github.com/scikit-learn/scikit-learn/issues/27090 | [
"Sprint",
"module:test-suite",
"Meta-issue",
"good first PR to review"
] | TST Extend tests for `scipy.sparse.*array`
SciPy sparse matrices (i.e. `scipy.sparse.*matrix`) are tested but their sparse arrays counterpart (i.e. `scipy.sparse.*array`) aren't yet will become ubiquitous (see #26418).
Tests and their parameterizations (when they exist) must be adapted to include `scipy.sparse.*arr... | 27,090 |
https://github.com/scikit-learn/scikit-learn/issues/27090 | [
"Sprint",
"module:test-suite",
"Meta-issue",
"good first PR to review"
] | TST Extend tests for `scipy.sparse.*array`
SciPy sparse matrices (i.e. `scipy.sparse.*matrix`) are tested but their sparse arrays counterpart (i.e. `scipy.sparse.*array`) aren't yet will become ubiquitous (see #26418).
Tests and their parameterizations (when they exist) must be adapted to include `scipy.sparse.*arr... | 27,090 |
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