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/31566 | [
"Needs Triage"
] | ⚠️ CI failed on Wheel builder (last failure: Jun 17, 2025) ⚠️
**CI failed on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/15697733135)** (Jun 17, 2025)
COMMENT:
From the logs, looks like a timeout, closing to see if it happens again. | 31,566 |
https://github.com/scikit-learn/scikit-learn/issues/31555 | [
"Bug",
"Needs Triage"
] | is_classifier returns False for custom classifier wrappers in scikit-learn 1.6.1, even with ClassifierMixin and _estimator_type
### Describe the bug
#### Describe the bug
Since upgrading to scikit-learn 1.6.1, the utility function `is_classifier` always returns `False` for custom classifier wrappers, even if they in... | 31,555 |
https://github.com/scikit-learn/scikit-learn/issues/31554 | [
"Performance",
"help wanted",
"module:metrics",
"Needs Investigation"
] | Allow batch based metrics calculation of sklearn.metrics
### Describe the workflow you want to enable
I have a lot of data and need to calculate metrics such as accuracy_score, jaccard_score, f1_score, recall, precision etc.
### Describe your proposed solution
When I try to calculate these it can literally take da... | 31,554 |
https://github.com/scikit-learn/scikit-learn/issues/31554 | [
"Performance",
"help wanted",
"module:metrics",
"Needs Investigation"
] | Allow batch based metrics calculation of sklearn.metrics
### Describe the workflow you want to enable
I have a lot of data and need to calculate metrics such as accuracy_score, jaccard_score, f1_score, recall, precision etc.
### Describe your proposed solution
When I try to calculate these it can literally take da... | 31,554 |
https://github.com/scikit-learn/scikit-learn/issues/31554 | [
"Performance",
"help wanted",
"module:metrics",
"Needs Investigation"
] | Allow batch based metrics calculation of sklearn.metrics
### Describe the workflow you want to enable
I have a lot of data and need to calculate metrics such as accuracy_score, jaccard_score, f1_score, recall, precision etc.
### Describe your proposed solution
When I try to calculate these it can literally take da... | 31,554 |
https://github.com/scikit-learn/scikit-learn/issues/31554 | [
"Performance",
"help wanted",
"module:metrics",
"Needs Investigation"
] | Allow batch based metrics calculation of sklearn.metrics
### Describe the workflow you want to enable
I have a lot of data and need to calculate metrics such as accuracy_score, jaccard_score, f1_score, recall, precision etc.
### Describe your proposed solution
When I try to calculate these it can literally take da... | 31,554 |
https://github.com/scikit-learn/scikit-learn/issues/31554 | [
"Performance",
"help wanted",
"module:metrics",
"Needs Investigation"
] | Allow batch based metrics calculation of sklearn.metrics
### Describe the workflow you want to enable
I have a lot of data and need to calculate metrics such as accuracy_score, jaccard_score, f1_score, recall, precision etc.
### Describe your proposed solution
When I try to calculate these it can literally take da... | 31,554 |
https://github.com/scikit-learn/scikit-learn/issues/31554 | [
"Performance",
"help wanted",
"module:metrics",
"Needs Investigation"
] | Allow batch based metrics calculation of sklearn.metrics
### Describe the workflow you want to enable
I have a lot of data and need to calculate metrics such as accuracy_score, jaccard_score, f1_score, recall, precision etc.
### Describe your proposed solution
When I try to calculate these it can literally take da... | 31,554 |
https://github.com/scikit-learn/scikit-learn/issues/31554 | [
"Performance",
"help wanted",
"module:metrics",
"Needs Investigation"
] | Allow batch based metrics calculation of sklearn.metrics
### Describe the workflow you want to enable
I have a lot of data and need to calculate metrics such as accuracy_score, jaccard_score, f1_score, recall, precision etc.
### Describe your proposed solution
When I try to calculate these it can literally take da... | 31,554 |
https://github.com/scikit-learn/scikit-learn/issues/31554 | [
"Performance",
"help wanted",
"module:metrics",
"Needs Investigation"
] | Allow batch based metrics calculation of sklearn.metrics
### Describe the workflow you want to enable
I have a lot of data and need to calculate metrics such as accuracy_score, jaccard_score, f1_score, recall, precision etc.
### Describe your proposed solution
When I try to calculate these it can literally take da... | 31,554 |
https://github.com/scikit-learn/scikit-learn/issues/31554 | [
"Performance",
"help wanted",
"module:metrics",
"Needs Investigation"
] | Allow batch based metrics calculation of sklearn.metrics
### Describe the workflow you want to enable
I have a lot of data and need to calculate metrics such as accuracy_score, jaccard_score, f1_score, recall, precision etc.
### Describe your proposed solution
When I try to calculate these it can literally take da... | 31,554 |
https://github.com/scikit-learn/scikit-learn/issues/31554 | [
"Performance",
"help wanted",
"module:metrics",
"Needs Investigation"
] | Allow batch based metrics calculation of sklearn.metrics
### Describe the workflow you want to enable
I have a lot of data and need to calculate metrics such as accuracy_score, jaccard_score, f1_score, recall, precision etc.
### Describe your proposed solution
When I try to calculate these it can literally take da... | 31,554 |
https://github.com/scikit-learn/scikit-learn/issues/31554 | [
"Performance",
"help wanted",
"module:metrics",
"Needs Investigation"
] | Allow batch based metrics calculation of sklearn.metrics
### Describe the workflow you want to enable
I have a lot of data and need to calculate metrics such as accuracy_score, jaccard_score, f1_score, recall, precision etc.
### Describe your proposed solution
When I try to calculate these it can literally take da... | 31,554 |
https://github.com/scikit-learn/scikit-learn/issues/31554 | [
"Performance",
"help wanted",
"module:metrics",
"Needs Investigation"
] | Allow batch based metrics calculation of sklearn.metrics
### Describe the workflow you want to enable
I have a lot of data and need to calculate metrics such as accuracy_score, jaccard_score, f1_score, recall, precision etc.
### Describe your proposed solution
When I try to calculate these it can literally take da... | 31,554 |
https://github.com/scikit-learn/scikit-learn/issues/31554 | [
"Performance",
"help wanted",
"module:metrics",
"Needs Investigation"
] | Allow batch based metrics calculation of sklearn.metrics
### Describe the workflow you want to enable
I have a lot of data and need to calculate metrics such as accuracy_score, jaccard_score, f1_score, recall, precision etc.
### Describe your proposed solution
When I try to calculate these it can literally take da... | 31,554 |
https://github.com/scikit-learn/scikit-learn/issues/31554 | [
"Performance",
"help wanted",
"module:metrics",
"Needs Investigation"
] | Allow batch based metrics calculation of sklearn.metrics
### Describe the workflow you want to enable
I have a lot of data and need to calculate metrics such as accuracy_score, jaccard_score, f1_score, recall, precision etc.
### Describe your proposed solution
When I try to calculate these it can literally take da... | 31,554 |
https://github.com/scikit-learn/scikit-learn/issues/31554 | [
"Performance",
"help wanted",
"module:metrics",
"Needs Investigation"
] | Allow batch based metrics calculation of sklearn.metrics
### Describe the workflow you want to enable
I have a lot of data and need to calculate metrics such as accuracy_score, jaccard_score, f1_score, recall, precision etc.
### Describe your proposed solution
When I try to calculate these it can literally take da... | 31,554 |
https://github.com/scikit-learn/scikit-learn/issues/31546 | [
"Bug",
"Regression"
] | Regression in `DecisionBoundaryDisplay.from_estimator` with `colors` and `plot_method='contour'` after upgrading to v1.7.0
### Describe the bug
Hello. Recently, after upgrading to scikit-learn v1.7.0, I encountered an issue when using `DecisionBoundaryDisplay.from_estimator` with the `colors` keyword argument. Specif... | 31,546 |
https://github.com/scikit-learn/scikit-learn/issues/31546 | [
"Bug",
"Regression"
] | Regression in `DecisionBoundaryDisplay.from_estimator` with `colors` and `plot_method='contour'` after upgrading to v1.7.0
### Describe the bug
Hello. Recently, after upgrading to scikit-learn v1.7.0, I encountered an issue when using `DecisionBoundaryDisplay.from_estimator` with the `colors` keyword argument. Specif... | 31,546 |
https://github.com/scikit-learn/scikit-learn/issues/31546 | [
"Bug",
"Regression"
] | Regression in `DecisionBoundaryDisplay.from_estimator` with `colors` and `plot_method='contour'` after upgrading to v1.7.0
### Describe the bug
Hello. Recently, after upgrading to scikit-learn v1.7.0, I encountered an issue when using `DecisionBoundaryDisplay.from_estimator` with the `colors` keyword argument. Specif... | 31,546 |
https://github.com/scikit-learn/scikit-learn/issues/31542 | [
"New Feature",
"help wanted",
"Hard"
] | Huber Loss for HistGradientBoostingRegressor
### Describe the workflow you want to enable
Huber loss is available as an option for `GradientBoostingRegressor` and works great when training on data with frequent outliers (thank you!). `HistGradientBoostingRegressor` however does not support Huber loss, which may be re... | 31,542 |
https://github.com/scikit-learn/scikit-learn/issues/31542 | [
"New Feature",
"help wanted",
"Hard"
] | Huber Loss for HistGradientBoostingRegressor
### Describe the workflow you want to enable
Huber loss is available as an option for `GradientBoostingRegressor` and works great when training on data with frequent outliers (thank you!). `HistGradientBoostingRegressor` however does not support Huber loss, which may be re... | 31,542 |
https://github.com/scikit-learn/scikit-learn/issues/31542 | [
"New Feature",
"help wanted",
"Hard"
] | Huber Loss for HistGradientBoostingRegressor
### Describe the workflow you want to enable
Huber loss is available as an option for `GradientBoostingRegressor` and works great when training on data with frequent outliers (thank you!). `HistGradientBoostingRegressor` however does not support Huber loss, which may be re... | 31,542 |
https://github.com/scikit-learn/scikit-learn/issues/31542 | [
"New Feature",
"help wanted",
"Hard"
] | Huber Loss for HistGradientBoostingRegressor
### Describe the workflow you want to enable
Huber loss is available as an option for `GradientBoostingRegressor` and works great when training on data with frequent outliers (thank you!). `HistGradientBoostingRegressor` however does not support Huber loss, which may be re... | 31,542 |
https://github.com/scikit-learn/scikit-learn/issues/31542 | [
"New Feature",
"help wanted",
"Hard"
] | Huber Loss for HistGradientBoostingRegressor
### Describe the workflow you want to enable
Huber loss is available as an option for `GradientBoostingRegressor` and works great when training on data with frequent outliers (thank you!). `HistGradientBoostingRegressor` however does not support Huber loss, which may be re... | 31,542 |
https://github.com/scikit-learn/scikit-learn/issues/31542 | [
"New Feature",
"help wanted",
"Hard"
] | Huber Loss for HistGradientBoostingRegressor
### Describe the workflow you want to enable
Huber loss is available as an option for `GradientBoostingRegressor` and works great when training on data with frequent outliers (thank you!). `HistGradientBoostingRegressor` however does not support Huber loss, which may be re... | 31,542 |
https://github.com/scikit-learn/scikit-learn/issues/31542 | [
"New Feature",
"help wanted",
"Hard"
] | Huber Loss for HistGradientBoostingRegressor
### Describe the workflow you want to enable
Huber loss is available as an option for `GradientBoostingRegressor` and works great when training on data with frequent outliers (thank you!). `HistGradientBoostingRegressor` however does not support Huber loss, which may be re... | 31,542 |
https://github.com/scikit-learn/scikit-learn/issues/31542 | [
"New Feature",
"help wanted",
"Hard"
] | Huber Loss for HistGradientBoostingRegressor
### Describe the workflow you want to enable
Huber loss is available as an option for `GradientBoostingRegressor` and works great when training on data with frequent outliers (thank you!). `HistGradientBoostingRegressor` however does not support Huber loss, which may be re... | 31,542 |
https://github.com/scikit-learn/scikit-learn/issues/31542 | [
"New Feature",
"help wanted",
"Hard"
] | Huber Loss for HistGradientBoostingRegressor
### Describe the workflow you want to enable
Huber loss is available as an option for `GradientBoostingRegressor` and works great when training on data with frequent outliers (thank you!). `HistGradientBoostingRegressor` however does not support Huber loss, which may be re... | 31,542 |
https://github.com/scikit-learn/scikit-learn/issues/31542 | [
"New Feature",
"help wanted",
"Hard"
] | Huber Loss for HistGradientBoostingRegressor
### Describe the workflow you want to enable
Huber loss is available as an option for `GradientBoostingRegressor` and works great when training on data with frequent outliers (thank you!). `HistGradientBoostingRegressor` however does not support Huber loss, which may be re... | 31,542 |
https://github.com/scikit-learn/scikit-learn/issues/31542 | [
"New Feature",
"help wanted",
"Hard"
] | Huber Loss for HistGradientBoostingRegressor
### Describe the workflow you want to enable
Huber loss is available as an option for `GradientBoostingRegressor` and works great when training on data with frequent outliers (thank you!). `HistGradientBoostingRegressor` however does not support Huber loss, which may be re... | 31,542 |
https://github.com/scikit-learn/scikit-learn/issues/31542 | [
"New Feature",
"help wanted",
"Hard"
] | Huber Loss for HistGradientBoostingRegressor
### Describe the workflow you want to enable
Huber loss is available as an option for `GradientBoostingRegressor` and works great when training on data with frequent outliers (thank you!). `HistGradientBoostingRegressor` however does not support Huber loss, which may be re... | 31,542 |
https://github.com/scikit-learn/scikit-learn/issues/31542 | [
"New Feature",
"help wanted",
"Hard"
] | Huber Loss for HistGradientBoostingRegressor
### Describe the workflow you want to enable
Huber loss is available as an option for `GradientBoostingRegressor` and works great when training on data with frequent outliers (thank you!). `HistGradientBoostingRegressor` however does not support Huber loss, which may be re... | 31,542 |
https://github.com/scikit-learn/scikit-learn/issues/31542 | [
"New Feature",
"help wanted",
"Hard"
] | Huber Loss for HistGradientBoostingRegressor
### Describe the workflow you want to enable
Huber loss is available as an option for `GradientBoostingRegressor` and works great when training on data with frequent outliers (thank you!). `HistGradientBoostingRegressor` however does not support Huber loss, which may be re... | 31,542 |
https://github.com/scikit-learn/scikit-learn/issues/31542 | [
"New Feature",
"help wanted",
"Hard"
] | Huber Loss for HistGradientBoostingRegressor
### Describe the workflow you want to enable
Huber loss is available as an option for `GradientBoostingRegressor` and works great when training on data with frequent outliers (thank you!). `HistGradientBoostingRegressor` however does not support Huber loss, which may be re... | 31,542 |
https://github.com/scikit-learn/scikit-learn/issues/31542 | [
"New Feature",
"help wanted",
"Hard"
] | Huber Loss for HistGradientBoostingRegressor
### Describe the workflow you want to enable
Huber loss is available as an option for `GradientBoostingRegressor` and works great when training on data with frequent outliers (thank you!). `HistGradientBoostingRegressor` however does not support Huber loss, which may be re... | 31,542 |
https://github.com/scikit-learn/scikit-learn/issues/31542 | [
"New Feature",
"help wanted",
"Hard"
] | Huber Loss for HistGradientBoostingRegressor
### Describe the workflow you want to enable
Huber loss is available as an option for `GradientBoostingRegressor` and works great when training on data with frequent outliers (thank you!). `HistGradientBoostingRegressor` however does not support Huber loss, which may be re... | 31,542 |
https://github.com/scikit-learn/scikit-learn/issues/31542 | [
"New Feature",
"help wanted",
"Hard"
] | Huber Loss for HistGradientBoostingRegressor
### Describe the workflow you want to enable
Huber loss is available as an option for `GradientBoostingRegressor` and works great when training on data with frequent outliers (thank you!). `HistGradientBoostingRegressor` however does not support Huber loss, which may be re... | 31,542 |
https://github.com/scikit-learn/scikit-learn/issues/31542 | [
"New Feature",
"help wanted",
"Hard"
] | Huber Loss for HistGradientBoostingRegressor
### Describe the workflow you want to enable
Huber loss is available as an option for `GradientBoostingRegressor` and works great when training on data with frequent outliers (thank you!). `HistGradientBoostingRegressor` however does not support Huber loss, which may be re... | 31,542 |
https://github.com/scikit-learn/scikit-learn/issues/31542 | [
"New Feature",
"help wanted",
"Hard"
] | Huber Loss for HistGradientBoostingRegressor
### Describe the workflow you want to enable
Huber loss is available as an option for `GradientBoostingRegressor` and works great when training on data with frequent outliers (thank you!). `HistGradientBoostingRegressor` however does not support Huber loss, which may be re... | 31,542 |
https://github.com/scikit-learn/scikit-learn/issues/31542 | [
"New Feature",
"help wanted",
"Hard"
] | Huber Loss for HistGradientBoostingRegressor
### Describe the workflow you want to enable
Huber loss is available as an option for `GradientBoostingRegressor` and works great when training on data with frequent outliers (thank you!). `HistGradientBoostingRegressor` however does not support Huber loss, which may be re... | 31,542 |
https://github.com/scikit-learn/scikit-learn/issues/31542 | [
"New Feature",
"help wanted",
"Hard"
] | Huber Loss for HistGradientBoostingRegressor
### Describe the workflow you want to enable
Huber loss is available as an option for `GradientBoostingRegressor` and works great when training on data with frequent outliers (thank you!). `HistGradientBoostingRegressor` however does not support Huber loss, which may be re... | 31,542 |
https://github.com/scikit-learn/scikit-learn/issues/31542 | [
"New Feature",
"help wanted",
"Hard"
] | Huber Loss for HistGradientBoostingRegressor
### Describe the workflow you want to enable
Huber loss is available as an option for `GradientBoostingRegressor` and works great when training on data with frequent outliers (thank you!). `HistGradientBoostingRegressor` however does not support Huber loss, which may be re... | 31,542 |
https://github.com/scikit-learn/scikit-learn/issues/31540 | [
"Enhancement",
"API",
"Needs Decision"
] | Make `sklearn.metrics._scorer._MultimetricScorer` part of the public API
### Describe the workflow you want to enable
This tool is great to run multiple scorers on a single estimator thanks to the caching mechanism. It is a bummer that it is not part of the public API.
### Describe your proposed solution
Make it pa... | 31,540 |
https://github.com/scikit-learn/scikit-learn/issues/31540 | [
"Enhancement",
"API",
"Needs Decision"
] | Make `sklearn.metrics._scorer._MultimetricScorer` part of the public API
### Describe the workflow you want to enable
This tool is great to run multiple scorers on a single estimator thanks to the caching mechanism. It is a bummer that it is not part of the public API.
### Describe your proposed solution
Make it pa... | 31,540 |
https://github.com/scikit-learn/scikit-learn/issues/31538 | [
"Bug",
"Needs Triage"
] | 当selector = VarianceThreshold(threshold=0.1)和selector = VarianceThreshold()输出的结果不一样
### Describe the bug
import numpy as np
X = np.arange(30,dtype=float).reshape((10, 3))
X[:,1] = 1
from sklearn.feature_selection import VarianceThreshold
vt = VarianceThreshold(threshold=0.01)
xt = vt.fit_transform(X)
# 未设置阈值时，可能未实际计算... | 31,538 |
https://github.com/scikit-learn/scikit-learn/issues/31538 | [
"Bug",
"Needs Triage"
] | 当selector = VarianceThreshold(threshold=0.1)和selector = VarianceThreshold()输出的结果不一样
### Describe the bug
import numpy as np
X = np.arange(30,dtype=float).reshape((10, 3))
X[:,1] = 1
from sklearn.feature_selection import VarianceThreshold
vt = VarianceThreshold(threshold=0.01)
xt = vt.fit_transform(X)
# 未设置阈值时，可能未实际计算... | 31,538 |
https://github.com/scikit-learn/scikit-learn/issues/31538 | [
"Bug",
"Needs Triage"
] | 当selector = VarianceThreshold(threshold=0.1)和selector = VarianceThreshold()输出的结果不一样
### Describe the bug
import numpy as np
X = np.arange(30,dtype=float).reshape((10, 3))
X[:,1] = 1
from sklearn.feature_selection import VarianceThreshold
vt = VarianceThreshold(threshold=0.01)
xt = vt.fit_transform(X)
# 未设置阈值时，可能未实际计算... | 31,538 |
https://github.com/scikit-learn/scikit-learn/issues/31536 | [
"Enhancement"
] | Improve sample_weight handling in sag(a)
### Describe the bug
This may be more of a discussion, but overall I am not sure what treatment of weighting would preserve the convergence guarantees for the SAG(A) solver. So far as I see it, at each update step we uniformly select some index $i_j$ such that the update steps... | 31,536 |
https://github.com/scikit-learn/scikit-learn/issues/31536 | [
"Enhancement"
] | Improve sample_weight handling in sag(a)
### Describe the bug
This may be more of a discussion, but overall I am not sure what treatment of weighting would preserve the convergence guarantees for the SAG(A) solver. So far as I see it, at each update step we uniformly select some index $i_j$ such that the update steps... | 31,536 |
https://github.com/scikit-learn/scikit-learn/issues/31536 | [
"Enhancement"
] | Improve sample_weight handling in sag(a)
### Describe the bug
This may be more of a discussion, but overall I am not sure what treatment of weighting would preserve the convergence guarantees for the SAG(A) solver. So far as I see it, at each update step we uniformly select some index $i_j$ such that the update steps... | 31,536 |
https://github.com/scikit-learn/scikit-learn/issues/31536 | [
"Enhancement"
] | Improve sample_weight handling in sag(a)
### Describe the bug
This may be more of a discussion, but overall I am not sure what treatment of weighting would preserve the convergence guarantees for the SAG(A) solver. So far as I see it, at each update step we uniformly select some index $i_j$ such that the update steps... | 31,536 |
https://github.com/scikit-learn/scikit-learn/issues/31536 | [
"Enhancement"
] | Improve sample_weight handling in sag(a)
### Describe the bug
This may be more of a discussion, but overall I am not sure what treatment of weighting would preserve the convergence guarantees for the SAG(A) solver. So far as I see it, at each update step we uniformly select some index $i_j$ such that the update steps... | 31,536 |
https://github.com/scikit-learn/scikit-learn/issues/31536 | [
"Enhancement"
] | Improve sample_weight handling in sag(a)
### Describe the bug
This may be more of a discussion, but overall I am not sure what treatment of weighting would preserve the convergence guarantees for the SAG(A) solver. So far as I see it, at each update step we uniformly select some index $i_j$ such that the update steps... | 31,536 |
https://github.com/scikit-learn/scikit-learn/issues/31536 | [
"Enhancement"
] | Improve sample_weight handling in sag(a)
### Describe the bug
This may be more of a discussion, but overall I am not sure what treatment of weighting would preserve the convergence guarantees for the SAG(A) solver. So far as I see it, at each update step we uniformly select some index $i_j$ such that the update steps... | 31,536 |
https://github.com/scikit-learn/scikit-learn/issues/31533 | [
"RFC",
"Array API"
] | RFC: stop using scikit-learn `stable_cumsum` and instead use `np.cumsum/xp.cumulative_sum` directly
As discussed in https://github.com/scikit-learn/scikit-learn/pull/30878/files#r2142562746, our current `stable_cumsum` function brings very little value to the user: it does extra computation to check that `np.allclose(... | 31,533 |
https://github.com/scikit-learn/scikit-learn/issues/31533 | [
"RFC",
"Array API"
] | RFC: stop using scikit-learn `stable_cumsum` and instead use `np.cumsum/xp.cumulative_sum` directly
As discussed in https://github.com/scikit-learn/scikit-learn/pull/30878/files#r2142562746, our current `stable_cumsum` function brings very little value to the user: it does extra computation to check that `np.allclose(... | 31,533 |
https://github.com/scikit-learn/scikit-learn/issues/31533 | [
"RFC",
"Array API"
] | RFC: stop using scikit-learn `stable_cumsum` and instead use `np.cumsum/xp.cumulative_sum` directly
As discussed in https://github.com/scikit-learn/scikit-learn/pull/30878/files#r2142562746, our current `stable_cumsum` function brings very little value to the user: it does extra computation to check that `np.allclose(... | 31,533 |
https://github.com/scikit-learn/scikit-learn/issues/31533 | [
"RFC",
"Array API"
] | RFC: stop using scikit-learn `stable_cumsum` and instead use `np.cumsum/xp.cumulative_sum` directly
As discussed in https://github.com/scikit-learn/scikit-learn/pull/30878/files#r2142562746, our current `stable_cumsum` function brings very little value to the user: it does extra computation to check that `np.allclose(... | 31,533 |
https://github.com/scikit-learn/scikit-learn/issues/31533 | [
"RFC",
"Array API"
] | RFC: stop using scikit-learn `stable_cumsum` and instead use `np.cumsum/xp.cumulative_sum` directly
As discussed in https://github.com/scikit-learn/scikit-learn/pull/30878/files#r2142562746, our current `stable_cumsum` function brings very little value to the user: it does extra computation to check that `np.allclose(... | 31,533 |
https://github.com/scikit-learn/scikit-learn/issues/31533 | [
"RFC",
"Array API"
] | RFC: stop using scikit-learn `stable_cumsum` and instead use `np.cumsum/xp.cumulative_sum` directly
As discussed in https://github.com/scikit-learn/scikit-learn/pull/30878/files#r2142562746, our current `stable_cumsum` function brings very little value to the user: it does extra computation to check that `np.allclose(... | 31,533 |
https://github.com/scikit-learn/scikit-learn/issues/31533 | [
"RFC",
"Array API"
] | RFC: stop using scikit-learn `stable_cumsum` and instead use `np.cumsum/xp.cumulative_sum` directly
As discussed in https://github.com/scikit-learn/scikit-learn/pull/30878/files#r2142562746, our current `stable_cumsum` function brings very little value to the user: it does extra computation to check that `np.allclose(... | 31,533 |
https://github.com/scikit-learn/scikit-learn/issues/31533 | [
"RFC",
"Array API"
] | RFC: stop using scikit-learn `stable_cumsum` and instead use `np.cumsum/xp.cumulative_sum` directly
As discussed in https://github.com/scikit-learn/scikit-learn/pull/30878/files#r2142562746, our current `stable_cumsum` function brings very little value to the user: it does extra computation to check that `np.allclose(... | 31,533 |
https://github.com/scikit-learn/scikit-learn/issues/31527 | [
"Needs Triage"
] | ⚠️ CI failed on Wheel builder (last failure: Jun 12, 2025) ⚠️
**CI failed on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/15601223966)** (Jun 12, 2025)
COMMENT:
The free-threaded failures are likely due to cibuildwheel 3.0.0 release, from [changelog](https://cibuildwheel.pypa.io/en/stable... | 31,527 |
https://github.com/scikit-learn/scikit-learn/issues/31525 | [
"Bug"
] | Issue with the `RidgeCV` diagram representation with non-default alphas
It seems that we introduced a regression in the HTML representation. The following code is failing:
```python
import numpy as np
from sklearn.linear_model import RidgeCV
RidgeCV(np.logspace(-3, 3, num=10)
```
leads to the following error:
```p... | 31,525 |
https://github.com/scikit-learn/scikit-learn/issues/31521 | [
"Bug",
"Regression"
] | TarFile.extractall() got an unexpected keyword argument 'filter'
### Describe the bug
For the latest version `1.7.0`, it can be installed with Python 3.10, but the parameter `filter` is available starting from Python 3.12 (See: https://docs.python.org/3/library/tarfile.html#tarfile.TarFile.extractall ).
https://gith... | 31,521 |
https://github.com/scikit-learn/scikit-learn/issues/31520 | [
"Bug",
"Needs Investigation"
] | 32-Bit Raspberry Pi OS Installation Issues with UV
### Describe the bug
When attempting to install scikit-learn==1.4.2 - 1.6.1 on Raspberry Pi OS Lite 32-Bit (Bookworm) or Raspberry Pi OS Lit 32-Bit (Bullseye) with UV, the following error is given:
```
× Failed to download and build `scikit-learn==1.4.2`
├─▶ Fail... | 31,520 |
https://github.com/scikit-learn/scikit-learn/issues/31520 | [
"Bug",
"Needs Investigation"
] | 32-Bit Raspberry Pi OS Installation Issues with UV
### Describe the bug
When attempting to install scikit-learn==1.4.2 - 1.6.1 on Raspberry Pi OS Lite 32-Bit (Bookworm) or Raspberry Pi OS Lit 32-Bit (Bullseye) with UV, the following error is given:
```
× Failed to download and build `scikit-learn==1.4.2`
├─▶ Fail... | 31,520 |
https://github.com/scikit-learn/scikit-learn/issues/31520 | [
"Bug",
"Needs Investigation"
] | 32-Bit Raspberry Pi OS Installation Issues with UV
### Describe the bug
When attempting to install scikit-learn==1.4.2 - 1.6.1 on Raspberry Pi OS Lite 32-Bit (Bookworm) or Raspberry Pi OS Lit 32-Bit (Bullseye) with UV, the following error is given:
```
× Failed to download and build `scikit-learn==1.4.2`
├─▶ Fail... | 31,520 |
https://github.com/scikit-learn/scikit-learn/issues/31520 | [
"Bug",
"Needs Investigation"
] | 32-Bit Raspberry Pi OS Installation Issues with UV
### Describe the bug
When attempting to install scikit-learn==1.4.2 - 1.6.1 on Raspberry Pi OS Lite 32-Bit (Bookworm) or Raspberry Pi OS Lit 32-Bit (Bullseye) with UV, the following error is given:
```
× Failed to download and build `scikit-learn==1.4.2`
├─▶ Fail... | 31,520 |
https://github.com/scikit-learn/scikit-learn/issues/31520 | [
"Bug",
"Needs Investigation"
] | 32-Bit Raspberry Pi OS Installation Issues with UV
### Describe the bug
When attempting to install scikit-learn==1.4.2 - 1.6.1 on Raspberry Pi OS Lite 32-Bit (Bookworm) or Raspberry Pi OS Lit 32-Bit (Bullseye) with UV, the following error is given:
```
× Failed to download and build `scikit-learn==1.4.2`
├─▶ Fail... | 31,520 |
https://github.com/scikit-learn/scikit-learn/issues/31512 | [
"New Feature"
] | Add free-threading wheel for Linux arm64 (aarch64)
### Describe the workflow you want to enable
I am a maintainer for the third-party package [fastcan](https://github.com/scikit-learn-contrib/fastcan). I tested the package on the free-threading Python (cp313t), and found scikit-learn missing a wheel for Linux arm64 (... | 31,512 |
https://github.com/scikit-learn/scikit-learn/issues/31503 | [
"New Feature",
"help wanted",
"Hard"
] | HDBSCAN performance issues compared to original hdbscan implementation (likely because Boruvka algorithm is not implemented)
### Describe the bug
When switching from Sklearn HDBSCAN implementation to original one from `hdbscan` library, I've notice that Sklearn's implementation has much worse implementation. I've tri... | 31,503 |
https://github.com/scikit-learn/scikit-learn/issues/31503 | [
"New Feature",
"help wanted",
"Hard"
] | HDBSCAN performance issues compared to original hdbscan implementation (likely because Boruvka algorithm is not implemented)
### Describe the bug
When switching from Sklearn HDBSCAN implementation to original one from `hdbscan` library, I've notice that Sklearn's implementation has much worse implementation. I've tri... | 31,503 |
https://github.com/scikit-learn/scikit-learn/issues/31498 | [
"Bug",
"Needs Triage"
] | Doc website incorrectly flags stable as unstable
### Describe the bug
Current website gives:
I tried having a look on how to fix this, but went in a rabbit hole that the version switcher is generated by "list_versions.py" in th... | 31,498 |
https://github.com/scikit-learn/scikit-learn/issues/31475 | [
"Needs Investigation"
] | MultiOutputRegressor can't process estimators with synchronization primitives
### Describe the bug
[MultiOutputRegressor ](https://scikit-learn.org/stable/modules/generated/sklearn.multioutput.MultiOutputRegressor.html) can't process estimators with threading/multiprocessing synchronization primitives
I want to prop... | 31,475 |
https://github.com/scikit-learn/scikit-learn/issues/31475 | [
"Needs Investigation"
] | MultiOutputRegressor can't process estimators with synchronization primitives
### Describe the bug
[MultiOutputRegressor ](https://scikit-learn.org/stable/modules/generated/sklearn.multioutput.MultiOutputRegressor.html) can't process estimators with threading/multiprocessing synchronization primitives
I want to prop... | 31,475 |
https://github.com/scikit-learn/scikit-learn/issues/31475 | [
"Needs Investigation"
] | MultiOutputRegressor can't process estimators with synchronization primitives
### Describe the bug
[MultiOutputRegressor ](https://scikit-learn.org/stable/modules/generated/sklearn.multioutput.MultiOutputRegressor.html) can't process estimators with threading/multiprocessing synchronization primitives
I want to prop... | 31,475 |
https://github.com/scikit-learn/scikit-learn/issues/31473 | [
"New Feature"
] | Add option to return final cross-validation score in SequentialFeatureSelector
### Describe the workflow you want to enable
Currently, when using `SequentialFeatureSelector`, it internally performs cross-validation to decide which features to select, based on the scoring function. However, the final cross-validation ... | 31,473 |
https://github.com/scikit-learn/scikit-learn/issues/31473 | [
"New Feature"
] | Add option to return final cross-validation score in SequentialFeatureSelector
### Describe the workflow you want to enable
Currently, when using `SequentialFeatureSelector`, it internally performs cross-validation to decide which features to select, based on the scoring function. However, the final cross-validation ... | 31,473 |
https://github.com/scikit-learn/scikit-learn/issues/31462 | [
"New Feature",
"Needs Decision - Include Feature"
] | Feat: DummyClassifier strategy that produces randomized probabilities
### Describe the workflow you want to enable
# Motivation
The `dummy` module is fantastic for testing pipelines all the way up through enterprise scales. The [strategies](https://github.com/scikit-learn/scikit-learn/blob/98ed9dc73/sklearn/dummy.py... | 31,462 |
https://github.com/scikit-learn/scikit-learn/issues/31462 | [
"New Feature",
"Needs Decision - Include Feature"
] | Feat: DummyClassifier strategy that produces randomized probabilities
### Describe the workflow you want to enable
# Motivation
The `dummy` module is fantastic for testing pipelines all the way up through enterprise scales. The [strategies](https://github.com/scikit-learn/scikit-learn/blob/98ed9dc73/sklearn/dummy.py... | 31,462 |
https://github.com/scikit-learn/scikit-learn/issues/31462 | [
"New Feature",
"Needs Decision - Include Feature"
] | Feat: DummyClassifier strategy that produces randomized probabilities
### Describe the workflow you want to enable
# Motivation
The `dummy` module is fantastic for testing pipelines all the way up through enterprise scales. The [strategies](https://github.com/scikit-learn/scikit-learn/blob/98ed9dc73/sklearn/dummy.py... | 31,462 |
https://github.com/scikit-learn/scikit-learn/issues/31462 | [
"New Feature",
"Needs Decision - Include Feature"
] | Feat: DummyClassifier strategy that produces randomized probabilities
### Describe the workflow you want to enable
# Motivation
The `dummy` module is fantastic for testing pipelines all the way up through enterprise scales. The [strategies](https://github.com/scikit-learn/scikit-learn/blob/98ed9dc73/sklearn/dummy.py... | 31,462 |
https://github.com/scikit-learn/scikit-learn/issues/31462 | [
"New Feature",
"Needs Decision - Include Feature"
] | Feat: DummyClassifier strategy that produces randomized probabilities
### Describe the workflow you want to enable
# Motivation
The `dummy` module is fantastic for testing pipelines all the way up through enterprise scales. The [strategies](https://github.com/scikit-learn/scikit-learn/blob/98ed9dc73/sklearn/dummy.py... | 31,462 |
https://github.com/scikit-learn/scikit-learn/issues/31462 | [
"New Feature",
"Needs Decision - Include Feature"
] | Feat: DummyClassifier strategy that produces randomized probabilities
### Describe the workflow you want to enable
# Motivation
The `dummy` module is fantastic for testing pipelines all the way up through enterprise scales. The [strategies](https://github.com/scikit-learn/scikit-learn/blob/98ed9dc73/sklearn/dummy.py... | 31,462 |
https://github.com/scikit-learn/scikit-learn/issues/31462 | [
"New Feature",
"Needs Decision - Include Feature"
] | Feat: DummyClassifier strategy that produces randomized probabilities
### Describe the workflow you want to enable
# Motivation
The `dummy` module is fantastic for testing pipelines all the way up through enterprise scales. The [strategies](https://github.com/scikit-learn/scikit-learn/blob/98ed9dc73/sklearn/dummy.py... | 31,462 |
https://github.com/scikit-learn/scikit-learn/issues/31462 | [
"New Feature",
"Needs Decision - Include Feature"
] | Feat: DummyClassifier strategy that produces randomized probabilities
### Describe the workflow you want to enable
# Motivation
The `dummy` module is fantastic for testing pipelines all the way up through enterprise scales. The [strategies](https://github.com/scikit-learn/scikit-learn/blob/98ed9dc73/sklearn/dummy.py... | 31,462 |
https://github.com/scikit-learn/scikit-learn/issues/31462 | [
"New Feature",
"Needs Decision - Include Feature"
] | Feat: DummyClassifier strategy that produces randomized probabilities
### Describe the workflow you want to enable
# Motivation
The `dummy` module is fantastic for testing pipelines all the way up through enterprise scales. The [strategies](https://github.com/scikit-learn/scikit-learn/blob/98ed9dc73/sklearn/dummy.py... | 31,462 |
https://github.com/scikit-learn/scikit-learn/issues/31462 | [
"New Feature",
"Needs Decision - Include Feature"
] | Feat: DummyClassifier strategy that produces randomized probabilities
### Describe the workflow you want to enable
# Motivation
The `dummy` module is fantastic for testing pipelines all the way up through enterprise scales. The [strategies](https://github.com/scikit-learn/scikit-learn/blob/98ed9dc73/sklearn/dummy.py... | 31,462 |
https://github.com/scikit-learn/scikit-learn/issues/31462 | [
"New Feature",
"Needs Decision - Include Feature"
] | Feat: DummyClassifier strategy that produces randomized probabilities
### Describe the workflow you want to enable
# Motivation
The `dummy` module is fantastic for testing pipelines all the way up through enterprise scales. The [strategies](https://github.com/scikit-learn/scikit-learn/blob/98ed9dc73/sklearn/dummy.py... | 31,462 |
https://github.com/scikit-learn/scikit-learn/issues/31462 | [
"New Feature",
"Needs Decision - Include Feature"
] | Feat: DummyClassifier strategy that produces randomized probabilities
### Describe the workflow you want to enable
# Motivation
The `dummy` module is fantastic for testing pipelines all the way up through enterprise scales. The [strategies](https://github.com/scikit-learn/scikit-learn/blob/98ed9dc73/sklearn/dummy.py... | 31,462 |
https://github.com/scikit-learn/scikit-learn/issues/31462 | [
"New Feature",
"Needs Decision - Include Feature"
] | Feat: DummyClassifier strategy that produces randomized probabilities
### Describe the workflow you want to enable
# Motivation
The `dummy` module is fantastic for testing pipelines all the way up through enterprise scales. The [strategies](https://github.com/scikit-learn/scikit-learn/blob/98ed9dc73/sklearn/dummy.py... | 31,462 |
https://github.com/scikit-learn/scikit-learn/issues/31462 | [
"New Feature",
"Needs Decision - Include Feature"
] | Feat: DummyClassifier strategy that produces randomized probabilities
### Describe the workflow you want to enable
# Motivation
The `dummy` module is fantastic for testing pipelines all the way up through enterprise scales. The [strategies](https://github.com/scikit-learn/scikit-learn/blob/98ed9dc73/sklearn/dummy.py... | 31,462 |
https://github.com/scikit-learn/scikit-learn/issues/31462 | [
"New Feature",
"Needs Decision - Include Feature"
] | Feat: DummyClassifier strategy that produces randomized probabilities
### Describe the workflow you want to enable
# Motivation
The `dummy` module is fantastic for testing pipelines all the way up through enterprise scales. The [strategies](https://github.com/scikit-learn/scikit-learn/blob/98ed9dc73/sklearn/dummy.py... | 31,462 |
https://github.com/scikit-learn/scikit-learn/issues/31462 | [
"New Feature",
"Needs Decision - Include Feature"
] | Feat: DummyClassifier strategy that produces randomized probabilities
### Describe the workflow you want to enable
# Motivation
The `dummy` module is fantastic for testing pipelines all the way up through enterprise scales. The [strategies](https://github.com/scikit-learn/scikit-learn/blob/98ed9dc73/sklearn/dummy.py... | 31,462 |
https://github.com/scikit-learn/scikit-learn/issues/31462 | [
"New Feature",
"Needs Decision - Include Feature"
] | Feat: DummyClassifier strategy that produces randomized probabilities
### Describe the workflow you want to enable
# Motivation
The `dummy` module is fantastic for testing pipelines all the way up through enterprise scales. The [strategies](https://github.com/scikit-learn/scikit-learn/blob/98ed9dc73/sklearn/dummy.py... | 31,462 |
https://github.com/scikit-learn/scikit-learn/issues/31462 | [
"New Feature",
"Needs Decision - Include Feature"
] | Feat: DummyClassifier strategy that produces randomized probabilities
### Describe the workflow you want to enable
# Motivation
The `dummy` module is fantastic for testing pipelines all the way up through enterprise scales. The [strategies](https://github.com/scikit-learn/scikit-learn/blob/98ed9dc73/sklearn/dummy.py... | 31,462 |
https://github.com/scikit-learn/scikit-learn/issues/31450 | [
"New Feature",
"Needs Decision - Include Feature"
] | Spherical K-means support (unit norm centroids and input)
### Describe the workflow you want to enable
Hi,
I was wondering if there is—or has been—any initiative to support cosine similarity in the KMeans implementation (i.e., spherical KMeans). I find the algorithm quite useful and would be happy to propose an imple... | 31,450 |
https://github.com/scikit-learn/scikit-learn/issues/31450 | [
"New Feature",
"Needs Decision - Include Feature"
] | Spherical K-means support (unit norm centroids and input)
### Describe the workflow you want to enable
Hi,
I was wondering if there is—or has been—any initiative to support cosine similarity in the KMeans implementation (i.e., spherical KMeans). I find the algorithm quite useful and would be happy to propose an imple... | 31,450 |
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