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/29929 | [
"Bug",
"Needs Reproducible Code"
] | Custom estimator's fit() method throws "RuntimeWarning: invalid value encountered in cast" in Linux Python 3.11/3.12
### Describe the bug
We have a custom estimator class that inherits from `sklearn.base.BaseEstimator` and `RegressorMixin`. We run automated unit tests in Azure DevOps pipelines on both Windows Serve... | 29,929 |
https://github.com/scikit-learn/scikit-learn/issues/29927 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_Nightly.pylatest_pip_scipy_dev (last failure: Sep 25, 2024) ⚠️
**CI failed on [Linux_Nightly.pylatest_pip_scipy_dev](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=70481&view=logs&j=dfe99b15-50db-5d7b-b1e9-4105c42527cf)** (Sep 25, 2024)
Unable to find junit file. Please se... | 29,927 |
https://github.com/scikit-learn/scikit-learn/issues/29927 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_Nightly.pylatest_pip_scipy_dev (last failure: Sep 25, 2024) ⚠️
**CI failed on [Linux_Nightly.pylatest_pip_scipy_dev](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=70481&view=logs&j=dfe99b15-50db-5d7b-b1e9-4105c42527cf)** (Sep 25, 2024)
Unable to find junit file. Please se... | 29,927 |
https://github.com/scikit-learn/scikit-learn/issues/29925 | [
"API",
"module:metrics"
] | Remove sokalmichener from distance metrics
SciPy is planning to remove `sokalmichener`: https://github.com/scipy/scipy/pull/21572
We reimplement `SokalMichenerDistance` in the distance metric, and it's exactly the same as the implementation `RogersTanimotoDistance`. We can follow SciPy's lead and remove `sokalmiche... | 29,925 |
https://github.com/scikit-learn/scikit-learn/issues/29922 | [
"Enhancement"
] | Random forest regression fails when calling data: probably a numerical error
### Describe the bug
It is known that random forrest regression (as well as many decision tree-based methods) are not affected by the scale of the data and don't require any scaling in the feature matrix or response vector. This includes a... | 29,922 |
https://github.com/scikit-learn/scikit-learn/issues/29922 | [
"Enhancement"
] | Random forest regression fails when calling data: probably a numerical error
### Describe the bug
It is known that random forrest regression (as well as many decision tree-based methods) are not affected by the scale of the data and don't require any scaling in the feature matrix or response vector. This includes a... | 29,922 |
https://github.com/scikit-learn/scikit-learn/issues/29922 | [
"Enhancement"
] | Random forest regression fails when calling data: probably a numerical error
### Describe the bug
It is known that random forrest regression (as well as many decision tree-based methods) are not affected by the scale of the data and don't require any scaling in the feature matrix or response vector. This includes a... | 29,922 |
https://github.com/scikit-learn/scikit-learn/issues/29922 | [
"Enhancement"
] | Random forest regression fails when calling data: probably a numerical error
### Describe the bug
It is known that random forrest regression (as well as many decision tree-based methods) are not affected by the scale of the data and don't require any scaling in the feature matrix or response vector. This includes a... | 29,922 |
https://github.com/scikit-learn/scikit-learn/issues/29922 | [
"Enhancement"
] | Random forest regression fails when calling data: probably a numerical error
### Describe the bug
It is known that random forrest regression (as well as many decision tree-based methods) are not affected by the scale of the data and don't require any scaling in the feature matrix or response vector. This includes a... | 29,922 |
https://github.com/scikit-learn/scikit-learn/issues/29922 | [
"Enhancement"
] | Random forest regression fails when calling data: probably a numerical error
### Describe the bug
It is known that random forrest regression (as well as many decision tree-based methods) are not affected by the scale of the data and don't require any scaling in the feature matrix or response vector. This includes a... | 29,922 |
https://github.com/scikit-learn/scikit-learn/issues/29922 | [
"Enhancement"
] | Random forest regression fails when calling data: probably a numerical error
### Describe the bug
It is known that random forrest regression (as well as many decision tree-based methods) are not affected by the scale of the data and don't require any scaling in the feature matrix or response vector. This includes a... | 29,922 |
https://github.com/scikit-learn/scikit-learn/issues/29922 | [
"Enhancement"
] | Random forest regression fails when calling data: probably a numerical error
### Describe the bug
It is known that random forrest regression (as well as many decision tree-based methods) are not affected by the scale of the data and don't require any scaling in the feature matrix or response vector. This includes a... | 29,922 |
https://github.com/scikit-learn/scikit-learn/issues/29917 | [
"Easy",
"Documentation",
"help wanted"
] | `**params` documentation for `GridSearchCV.fit` is ambiguous
[`GridSearchCV.fit`](https://scikit-learn.org/dev/modules/generated/sklearn.model_selection.GridSearchCV.html#sklearn.model_selection.GridSearchCV.fit)
### Describe the issue linked to the documentation
The documentation for the `**params` parameter to... | 29,917 |
https://github.com/scikit-learn/scikit-learn/issues/29917 | [
"Easy",
"Documentation",
"help wanted"
] | `**params` documentation for `GridSearchCV.fit` is ambiguous
[`GridSearchCV.fit`](https://scikit-learn.org/dev/modules/generated/sklearn.model_selection.GridSearchCV.html#sklearn.model_selection.GridSearchCV.fit)
### Describe the issue linked to the documentation
The documentation for the `**params` parameter to... | 29,917 |
https://github.com/scikit-learn/scikit-learn/issues/29906 | [
"Bug"
] | Incorrect sample weight handling in `KBinsDiscretizer`
### Describe the bug
Sample weights are not properly passed through when specifying subsample within KBinsDiscretizer.
### Steps/Code to Reproduce
```python
from sklearn.datasets import make_blobs
from sklearn.preprocessing import KBinsDiscretizer
impo... | 29,906 |
https://github.com/scikit-learn/scikit-learn/issues/29905 | [
"New Feature",
"Needs Info"
] | Training final model with cross validation and using it to get unbiased probabilities
### Describe the workflow you want to enable
I want to use crossvalidation with let's say k=4 in order to get four models. That means that each sample in my dataset was used to train 3 of the four models. Thus, if I want to get a pr... | 29,905 |
https://github.com/scikit-learn/scikit-learn/issues/29905 | [
"New Feature",
"Needs Info"
] | Training final model with cross validation and using it to get unbiased probabilities
### Describe the workflow you want to enable
I want to use crossvalidation with let's say k=4 in order to get four models. That means that each sample in my dataset was used to train 3 of the four models. Thus, if I want to get a pr... | 29,905 |
https://github.com/scikit-learn/scikit-learn/issues/29905 | [
"New Feature",
"Needs Info"
] | Training final model with cross validation and using it to get unbiased probabilities
### Describe the workflow you want to enable
I want to use crossvalidation with let's say k=4 in order to get four models. That means that each sample in my dataset was used to train 3 of the four models. Thus, if I want to get a pr... | 29,905 |
https://github.com/scikit-learn/scikit-learn/issues/29902 | [
"Bug",
"Needs Triage"
] | ImportError: cannot import name 'InconsistentVersionWarning' in sklearn.exceptions
### Describe the bug
The error message "ImportError: cannot import name 'InconsistentVersionWarning'“ occurs when there is an attempt to import the sklearn
### Steps/Code to Reproduce
import sklearn
### Expected Results
successful ... | 29,902 |
https://github.com/scikit-learn/scikit-learn/issues/29902 | [
"Bug",
"Needs Triage"
] | ImportError: cannot import name 'InconsistentVersionWarning' in sklearn.exceptions
### Describe the bug
The error message "ImportError: cannot import name 'InconsistentVersionWarning'“ occurs when there is an attempt to import the sklearn
### Steps/Code to Reproduce
import sklearn
### Expected Results
successful ... | 29,902 |
https://github.com/scikit-learn/scikit-learn/issues/29902 | [
"Bug",
"Needs Triage"
] | ImportError: cannot import name 'InconsistentVersionWarning' in sklearn.exceptions
### Describe the bug
The error message "ImportError: cannot import name 'InconsistentVersionWarning'“ occurs when there is an attempt to import the sklearn
### Steps/Code to Reproduce
import sklearn
### Expected Results
successful ... | 29,902 |
https://github.com/scikit-learn/scikit-learn/issues/29901 | [
"New Feature",
"module:linear_model"
] | proper sparse support in glm's with newton-cholesky
### Describe the workflow you want to enable
When a user fits a glm with a sparse X, I believe the newton-cholesky solver ultimately creates a dense hessian, and the newton step is solved using scipy's dense symmetric linear solve. Instead I think SKL should create... | 29,901 |
https://github.com/scikit-learn/scikit-learn/issues/29901 | [
"New Feature",
"module:linear_model"
] | proper sparse support in glm's with newton-cholesky
### Describe the workflow you want to enable
When a user fits a glm with a sparse X, I believe the newton-cholesky solver ultimately creates a dense hessian, and the newton step is solved using scipy's dense symmetric linear solve. Instead I think SKL should create... | 29,901 |
https://github.com/scikit-learn/scikit-learn/issues/29901 | [
"New Feature",
"module:linear_model"
] | proper sparse support in glm's with newton-cholesky
### Describe the workflow you want to enable
When a user fits a glm with a sparse X, I believe the newton-cholesky solver ultimately creates a dense hessian, and the newton step is solved using scipy's dense symmetric linear solve. Instead I think SKL should create... | 29,901 |
https://github.com/scikit-learn/scikit-learn/issues/29900 | [
"Easy",
"Documentation"
] | Docs for estimator types do not list all possible estimator types
### Describe the issue linked to the documentation
The docs for 'Developing scikit-learn estimators' mention that one should specify the estimator type:
https://scikit-learn.org/stable/developers/develop.html#estimator-types
It lists the options as... | 29,900 |
https://github.com/scikit-learn/scikit-learn/issues/29900 | [
"Easy",
"Documentation"
] | Docs for estimator types do not list all possible estimator types
### Describe the issue linked to the documentation
The docs for 'Developing scikit-learn estimators' mention that one should specify the estimator type:
https://scikit-learn.org/stable/developers/develop.html#estimator-types
It lists the options as... | 29,900 |
https://github.com/scikit-learn/scikit-learn/issues/29893 | [
"API",
"RFC"
] | Implications of FrozenEstimator on our API
With https://github.com/scikit-learn/scikit-learn/pull/29705, we have a simple way to freeze estimators, which means there is no need for `cv="prefit"`. This also opens the door for https://github.com/scikit-learn/scikit-learn/pull/8350 to make `Pipeline` and `FeatureUnion` f... | 29,893 |
https://github.com/scikit-learn/scikit-learn/issues/29893 | [
"API",
"RFC"
] | Implications of FrozenEstimator on our API
With https://github.com/scikit-learn/scikit-learn/pull/29705, we have a simple way to freeze estimators, which means there is no need for `cv="prefit"`. This also opens the door for https://github.com/scikit-learn/scikit-learn/pull/8350 to make `Pipeline` and `FeatureUnion` f... | 29,893 |
https://github.com/scikit-learn/scikit-learn/issues/29893 | [
"API",
"RFC"
] | Implications of FrozenEstimator on our API
With https://github.com/scikit-learn/scikit-learn/pull/29705, we have a simple way to freeze estimators, which means there is no need for `cv="prefit"`. This also opens the door for https://github.com/scikit-learn/scikit-learn/pull/8350 to make `Pipeline` and `FeatureUnion` f... | 29,893 |
https://github.com/scikit-learn/scikit-learn/issues/29893 | [
"API",
"RFC"
] | Implications of FrozenEstimator on our API
With https://github.com/scikit-learn/scikit-learn/pull/29705, we have a simple way to freeze estimators, which means there is no need for `cv="prefit"`. This also opens the door for https://github.com/scikit-learn/scikit-learn/pull/8350 to make `Pipeline` and `FeatureUnion` f... | 29,893 |
https://github.com/scikit-learn/scikit-learn/issues/29893 | [
"API",
"RFC"
] | Implications of FrozenEstimator on our API
With https://github.com/scikit-learn/scikit-learn/pull/29705, we have a simple way to freeze estimators, which means there is no need for `cv="prefit"`. This also opens the door for https://github.com/scikit-learn/scikit-learn/pull/8350 to make `Pipeline` and `FeatureUnion` f... | 29,893 |
https://github.com/scikit-learn/scikit-learn/issues/29893 | [
"API",
"RFC"
] | Implications of FrozenEstimator on our API
With https://github.com/scikit-learn/scikit-learn/pull/29705, we have a simple way to freeze estimators, which means there is no need for `cv="prefit"`. This also opens the door for https://github.com/scikit-learn/scikit-learn/pull/8350 to make `Pipeline` and `FeatureUnion` f... | 29,893 |
https://github.com/scikit-learn/scikit-learn/issues/29893 | [
"API",
"RFC"
] | Implications of FrozenEstimator on our API
With https://github.com/scikit-learn/scikit-learn/pull/29705, we have a simple way to freeze estimators, which means there is no need for `cv="prefit"`. This also opens the door for https://github.com/scikit-learn/scikit-learn/pull/8350 to make `Pipeline` and `FeatureUnion` f... | 29,893 |
https://github.com/scikit-learn/scikit-learn/issues/29893 | [
"API",
"RFC"
] | Implications of FrozenEstimator on our API
With https://github.com/scikit-learn/scikit-learn/pull/29705, we have a simple way to freeze estimators, which means there is no need for `cv="prefit"`. This also opens the door for https://github.com/scikit-learn/scikit-learn/pull/8350 to make `Pipeline` and `FeatureUnion` f... | 29,893 |
https://github.com/scikit-learn/scikit-learn/issues/29893 | [
"API",
"RFC"
] | Implications of FrozenEstimator on our API
With https://github.com/scikit-learn/scikit-learn/pull/29705, we have a simple way to freeze estimators, which means there is no need for `cv="prefit"`. This also opens the door for https://github.com/scikit-learn/scikit-learn/pull/8350 to make `Pipeline` and `FeatureUnion` f... | 29,893 |
https://github.com/scikit-learn/scikit-learn/issues/29893 | [
"API",
"RFC"
] | Implications of FrozenEstimator on our API
With https://github.com/scikit-learn/scikit-learn/pull/29705, we have a simple way to freeze estimators, which means there is no need for `cv="prefit"`. This also opens the door for https://github.com/scikit-learn/scikit-learn/pull/8350 to make `Pipeline` and `FeatureUnion` f... | 29,893 |
https://github.com/scikit-learn/scikit-learn/issues/29893 | [
"API",
"RFC"
] | Implications of FrozenEstimator on our API
With https://github.com/scikit-learn/scikit-learn/pull/29705, we have a simple way to freeze estimators, which means there is no need for `cv="prefit"`. This also opens the door for https://github.com/scikit-learn/scikit-learn/pull/8350 to make `Pipeline` and `FeatureUnion` f... | 29,893 |
https://github.com/scikit-learn/scikit-learn/issues/29893 | [
"API",
"RFC"
] | Implications of FrozenEstimator on our API
With https://github.com/scikit-learn/scikit-learn/pull/29705, we have a simple way to freeze estimators, which means there is no need for `cv="prefit"`. This also opens the door for https://github.com/scikit-learn/scikit-learn/pull/8350 to make `Pipeline` and `FeatureUnion` f... | 29,893 |
https://github.com/scikit-learn/scikit-learn/issues/29893 | [
"API",
"RFC"
] | Implications of FrozenEstimator on our API
With https://github.com/scikit-learn/scikit-learn/pull/29705, we have a simple way to freeze estimators, which means there is no need for `cv="prefit"`. This also opens the door for https://github.com/scikit-learn/scikit-learn/pull/8350 to make `Pipeline` and `FeatureUnion` f... | 29,893 |
https://github.com/scikit-learn/scikit-learn/issues/29893 | [
"API",
"RFC"
] | Implications of FrozenEstimator on our API
With https://github.com/scikit-learn/scikit-learn/pull/29705, we have a simple way to freeze estimators, which means there is no need for `cv="prefit"`. This also opens the door for https://github.com/scikit-learn/scikit-learn/pull/8350 to make `Pipeline` and `FeatureUnion` f... | 29,893 |
https://github.com/scikit-learn/scikit-learn/issues/29893 | [
"API",
"RFC"
] | Implications of FrozenEstimator on our API
With https://github.com/scikit-learn/scikit-learn/pull/29705, we have a simple way to freeze estimators, which means there is no need for `cv="prefit"`. This also opens the door for https://github.com/scikit-learn/scikit-learn/pull/8350 to make `Pipeline` and `FeatureUnion` f... | 29,893 |
https://github.com/scikit-learn/scikit-learn/issues/29891 | [
"Needs Triage"
] | ⚠️ CI failed on Wheel builder (last failure: Sep 22, 2024) ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/10978032969)** (Sep 22, 2024)
COMMENT:
The same tests are failing here: https://github.com/scikit-learn/scikit-learn/issues/29889 | 29,891 |
https://github.com/scikit-learn/scikit-learn/issues/29891 | [
"Needs Triage"
] | ⚠️ CI failed on Wheel builder (last failure: Sep 22, 2024) ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/10978032969)** (Sep 22, 2024)
COMMENT:
The root cause is likely numpy-dev or scipy-dev https://github.com/scikit-learn/scikit-learn/issues/29864 | 29,891 |
https://github.com/scikit-learn/scikit-learn/issues/29891 | [
"Needs Triage"
] | ⚠️ CI failed on Wheel builder (last failure: Sep 22, 2024) ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/10978032969)** (Sep 22, 2024)
COMMENT:
## CI is no longer failing! ✅
[Successful run](https://github.com/scikit-learn/scikit-learn/actions/runs/10987327652)... | 29,891 |
https://github.com/scikit-learn/scikit-learn/issues/29889 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_free_threaded.pylatest_pip_free_threaded (last failure: Sep 22, 2024) ⚠️
**CI is still failing on [Linux_free_threaded.pylatest_pip_free_threaded](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=70432&view=logs&j=8bc43b48-889f-54b9-cd8b-781ee8447bf2)** (Sep 22, 2024)
- test... | 29,889 |
https://github.com/scikit-learn/scikit-learn/issues/29889 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_free_threaded.pylatest_pip_free_threaded (last failure: Sep 22, 2024) ⚠️
**CI is still failing on [Linux_free_threaded.pylatest_pip_free_threaded](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=70432&view=logs&j=8bc43b48-889f-54b9-cd8b-781ee8447bf2)** (Sep 22, 2024)
- test... | 29,889 |
https://github.com/scikit-learn/scikit-learn/issues/29889 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_free_threaded.pylatest_pip_free_threaded (last failure: Sep 22, 2024) ⚠️
**CI is still failing on [Linux_free_threaded.pylatest_pip_free_threaded](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=70432&view=logs&j=8bc43b48-889f-54b9-cd8b-781ee8447bf2)** (Sep 22, 2024)
- test... | 29,889 |
https://github.com/scikit-learn/scikit-learn/issues/29873 | [
"Bug",
"Needs Triage"
] | sklearn.neighbors.NearestNeighbors may have a bug
### Describe the bug
I found a suspected error in NearestNeighbors:
``` python
from sklearn.neighbors import NearestNeighbors
nbrs = NearestNeighbors(n_neighbors=2).fit(yields[if_predict == -1][:130])
distances, indices = nbrs.kneighbors(yields[if_predict == -1][:... | 29,873 |
https://github.com/scikit-learn/scikit-learn/issues/29873 | [
"Bug",
"Needs Triage"
] | sklearn.neighbors.NearestNeighbors may have a bug
### Describe the bug
I found a suspected error in NearestNeighbors:
``` python
from sklearn.neighbors import NearestNeighbors
nbrs = NearestNeighbors(n_neighbors=2).fit(yields[if_predict == -1][:130])
distances, indices = nbrs.kneighbors(yields[if_predict == -1][:... | 29,873 |
https://github.com/scikit-learn/scikit-learn/issues/29870 | [
"Build / CI"
] | Publish Python 3.13 wheels on PyPI for 1.5.2
### Describe the workflow you want to enable
Hello,
Could you please release CPython 3.13 manylinux wheels on PyPI?
Python 3.13.0~rc2 has already been released and there will be no ABI changes even for bug fixes at this point.
It will help projects starts using scikit-l... | 29,870 |
https://github.com/scikit-learn/scikit-learn/issues/29870 | [
"Build / CI"
] | Publish Python 3.13 wheels on PyPI for 1.5.2
### Describe the workflow you want to enable
Hello,
Could you please release CPython 3.13 manylinux wheels on PyPI?
Python 3.13.0~rc2 has already been released and there will be no ABI changes even for bug fixes at this point.
It will help projects starts using scikit-l... | 29,870 |
https://github.com/scikit-learn/scikit-learn/issues/29870 | [
"Build / CI"
] | Publish Python 3.13 wheels on PyPI for 1.5.2
### Describe the workflow you want to enable
Hello,
Could you please release CPython 3.13 manylinux wheels on PyPI?
Python 3.13.0~rc2 has already been released and there will be no ABI changes even for bug fixes at this point.
It will help projects starts using scikit-l... | 29,870 |
https://github.com/scikit-learn/scikit-learn/issues/29870 | [
"Build / CI"
] | Publish Python 3.13 wheels on PyPI for 1.5.2
### Describe the workflow you want to enable
Hello,
Could you please release CPython 3.13 manylinux wheels on PyPI?
Python 3.13.0~rc2 has already been released and there will be no ABI changes even for bug fixes at this point.
It will help projects starts using scikit-l... | 29,870 |
https://github.com/scikit-learn/scikit-learn/issues/29870 | [
"Build / CI"
] | Publish Python 3.13 wheels on PyPI for 1.5.2
### Describe the workflow you want to enable
Hello,
Could you please release CPython 3.13 manylinux wheels on PyPI?
Python 3.13.0~rc2 has already been released and there will be no ABI changes even for bug fixes at this point.
It will help projects starts using scikit-l... | 29,870 |
https://github.com/scikit-learn/scikit-learn/issues/29870 | [
"Build / CI"
] | Publish Python 3.13 wheels on PyPI for 1.5.2
### Describe the workflow you want to enable
Hello,
Could you please release CPython 3.13 manylinux wheels on PyPI?
Python 3.13.0~rc2 has already been released and there will be no ABI changes even for bug fixes at this point.
It will help projects starts using scikit-l... | 29,870 |
https://github.com/scikit-learn/scikit-learn/issues/29864 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_Nightly.pylatest_pip_scipy_dev (last failure: Sep 22, 2024) ⚠️
**CI is still failing on [Linux_Nightly.pylatest_pip_scipy_dev](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=70432&view=logs&j=dfe99b15-50db-5d7b-b1e9-4105c42527cf)** (Sep 22, 2024)
- test_lbfgs_solver_consis... | 29,864 |
https://github.com/scikit-learn/scikit-learn/issues/29864 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_Nightly.pylatest_pip_scipy_dev (last failure: Sep 22, 2024) ⚠️
**CI is still failing on [Linux_Nightly.pylatest_pip_scipy_dev](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=70432&view=logs&j=dfe99b15-50db-5d7b-b1e9-4105c42527cf)** (Sep 22, 2024)
- test_lbfgs_solver_consis... | 29,864 |
https://github.com/scikit-learn/scikit-learn/issues/29864 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_Nightly.pylatest_pip_scipy_dev (last failure: Sep 22, 2024) ⚠️
**CI is still failing on [Linux_Nightly.pylatest_pip_scipy_dev](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=70432&view=logs&j=dfe99b15-50db-5d7b-b1e9-4105c42527cf)** (Sep 22, 2024)
- test_lbfgs_solver_consis... | 29,864 |
https://github.com/scikit-learn/scikit-learn/issues/29864 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_Nightly.pylatest_pip_scipy_dev (last failure: Sep 22, 2024) ⚠️
**CI is still failing on [Linux_Nightly.pylatest_pip_scipy_dev](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=70432&view=logs&j=dfe99b15-50db-5d7b-b1e9-4105c42527cf)** (Sep 22, 2024)
- test_lbfgs_solver_consis... | 29,864 |
https://github.com/scikit-learn/scikit-learn/issues/29864 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_Nightly.pylatest_pip_scipy_dev (last failure: Sep 22, 2024) ⚠️
**CI is still failing on [Linux_Nightly.pylatest_pip_scipy_dev](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=70432&view=logs&j=dfe99b15-50db-5d7b-b1e9-4105c42527cf)** (Sep 22, 2024)
- test_lbfgs_solver_consis... | 29,864 |
https://github.com/scikit-learn/scikit-learn/issues/29864 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_Nightly.pylatest_pip_scipy_dev (last failure: Sep 22, 2024) ⚠️
**CI is still failing on [Linux_Nightly.pylatest_pip_scipy_dev](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=70432&view=logs&j=dfe99b15-50db-5d7b-b1e9-4105c42527cf)** (Sep 22, 2024)
- test_lbfgs_solver_consis... | 29,864 |
https://github.com/scikit-learn/scikit-learn/issues/29862 | [
"Needs Info"
] | "int64 indices" error in fit_predict function even with 32-bit integer
### Describe the bug
I'm trying to apply spectral clustering on a sparse adjacency matrix of a surface mesh. Although the matrix's entries are using 32-bit integer indices, the `fit_predict` function gives me the following error:
```
ValueErr... | 29,862 |
https://github.com/scikit-learn/scikit-learn/issues/29862 | [
"Needs Info"
] | "int64 indices" error in fit_predict function even with 32-bit integer
### Describe the bug
I'm trying to apply spectral clustering on a sparse adjacency matrix of a surface mesh. Although the matrix's entries are using 32-bit integer indices, the `fit_predict` function gives me the following error:
```
ValueErr... | 29,862 |
https://github.com/scikit-learn/scikit-learn/issues/29862 | [
"Needs Info"
] | "int64 indices" error in fit_predict function even with 32-bit integer
### Describe the bug
I'm trying to apply spectral clustering on a sparse adjacency matrix of a surface mesh. Although the matrix's entries are using 32-bit integer indices, the `fit_predict` function gives me the following error:
```
ValueErr... | 29,862 |
https://github.com/scikit-learn/scikit-learn/issues/29862 | [
"Needs Info"
] | "int64 indices" error in fit_predict function even with 32-bit integer
### Describe the bug
I'm trying to apply spectral clustering on a sparse adjacency matrix of a surface mesh. Although the matrix's entries are using 32-bit integer indices, the `fit_predict` function gives me the following error:
```
ValueErr... | 29,862 |
https://github.com/scikit-learn/scikit-learn/issues/29862 | [
"Needs Info"
] | "int64 indices" error in fit_predict function even with 32-bit integer
### Describe the bug
I'm trying to apply spectral clustering on a sparse adjacency matrix of a surface mesh. Although the matrix's entries are using 32-bit integer indices, the `fit_predict` function gives me the following error:
```
ValueErr... | 29,862 |
https://github.com/scikit-learn/scikit-learn/issues/29862 | [
"Needs Info"
] | "int64 indices" error in fit_predict function even with 32-bit integer
### Describe the bug
I'm trying to apply spectral clustering on a sparse adjacency matrix of a surface mesh. Although the matrix's entries are using 32-bit integer indices, the `fit_predict` function gives me the following error:
```
ValueErr... | 29,862 |
https://github.com/scikit-learn/scikit-learn/issues/29862 | [
"Needs Info"
] | "int64 indices" error in fit_predict function even with 32-bit integer
### Describe the bug
I'm trying to apply spectral clustering on a sparse adjacency matrix of a surface mesh. Although the matrix's entries are using 32-bit integer indices, the `fit_predict` function gives me the following error:
```
ValueErr... | 29,862 |
https://github.com/scikit-learn/scikit-learn/issues/29858 | [
"Bug",
"Needs Triage"
] | Sklearn train_test_split gives incorrect array outputs.
### Describe the bug
I suspect this is because I give the function more than one array to split, but according to the documentation train_test_split should be able to take any number of arrays?
Code to reproduce:
```
test_numerical = np.random.rand(2509, 9)... | 29,858 |
https://github.com/scikit-learn/scikit-learn/issues/29858 | [
"Bug",
"Needs Triage"
] | Sklearn train_test_split gives incorrect array outputs.
### Describe the bug
I suspect this is because I give the function more than one array to split, but according to the documentation train_test_split should be able to take any number of arrays?
Code to reproduce:
```
test_numerical = np.random.rand(2509, 9)... | 29,858 |
https://github.com/scikit-learn/scikit-learn/issues/29856 | [
"Bug"
] | ClassifierChain does not accept NaN values even when base estimator supports them
### Describe the bug
I am working on a multilabel classification problem using ClassifierChain with RandomForestClassifier as the base estimator.
I have encountered an issue where ClassifierChain raises a ValueError when the input da... | 29,856 |
https://github.com/scikit-learn/scikit-learn/issues/29856 | [
"Bug"
] | ClassifierChain does not accept NaN values even when base estimator supports them
### Describe the bug
I am working on a multilabel classification problem using ClassifierChain with RandomForestClassifier as the base estimator.
I have encountered an issue where ClassifierChain raises a ValueError when the input da... | 29,856 |
https://github.com/scikit-learn/scikit-learn/issues/29856 | [
"Bug"
] | ClassifierChain does not accept NaN values even when base estimator supports them
### Describe the bug
I am working on a multilabel classification problem using ClassifierChain with RandomForestClassifier as the base estimator.
I have encountered an issue where ClassifierChain raises a ValueError when the input da... | 29,856 |
https://github.com/scikit-learn/scikit-learn/issues/29856 | [
"Bug"
] | ClassifierChain does not accept NaN values even when base estimator supports them
### Describe the bug
I am working on a multilabel classification problem using ClassifierChain with RandomForestClassifier as the base estimator.
I have encountered an issue where ClassifierChain raises a ValueError when the input da... | 29,856 |
https://github.com/scikit-learn/scikit-learn/issues/29856 | [
"Bug"
] | ClassifierChain does not accept NaN values even when base estimator supports them
### Describe the bug
I am working on a multilabel classification problem using ClassifierChain with RandomForestClassifier as the base estimator.
I have encountered an issue where ClassifierChain raises a ValueError when the input da... | 29,856 |
https://github.com/scikit-learn/scikit-learn/issues/29850 | [
"Bug",
"Needs Triage"
] | `cross_validate` accepts `sample_weight` in fitted estimator, but should raise or warn
### Describe the bug
When we pass a fitted estimator into `cross_validate` it will fit this estimator again on the given train-validation splits.
However, users can pass `sample_weight` to the fitted estimator without being warn... | 29,850 |
https://github.com/scikit-learn/scikit-learn/issues/29850 | [
"Bug",
"Needs Triage"
] | `cross_validate` accepts `sample_weight` in fitted estimator, but should raise or warn
### Describe the bug
When we pass a fitted estimator into `cross_validate` it will fit this estimator again on the given train-validation splits.
However, users can pass `sample_weight` to the fitted estimator without being warn... | 29,850 |
https://github.com/scikit-learn/scikit-learn/issues/29850 | [
"Bug",
"Needs Triage"
] | `cross_validate` accepts `sample_weight` in fitted estimator, but should raise or warn
### Describe the bug
When we pass a fitted estimator into `cross_validate` it will fit this estimator again on the given train-validation splits.
However, users can pass `sample_weight` to the fitted estimator without being warn... | 29,850 |
https://github.com/scikit-learn/scikit-learn/issues/29850 | [
"Bug",
"Needs Triage"
] | `cross_validate` accepts `sample_weight` in fitted estimator, but should raise or warn
### Describe the bug
When we pass a fitted estimator into `cross_validate` it will fit this estimator again on the given train-validation splits.
However, users can pass `sample_weight` to the fitted estimator without being warn... | 29,850 |
https://github.com/scikit-learn/scikit-learn/issues/29849 | [
"Documentation",
"RFC"
] | Adding scikit-learn to the pydata-sphinx-theme gallery of sites
As described in the title, I wonder if we want to add scikit-learn to the list of pydata-sphinx-theme gallery of sites: https://pydata-sphinx-theme.readthedocs.io/en/stable/examples/gallery.html. If we do I can ask pydata-sphinx-theme about it.
COMMENT:
... | 29,849 |
https://github.com/scikit-learn/scikit-learn/issues/29849 | [
"Documentation",
"RFC"
] | Adding scikit-learn to the pydata-sphinx-theme gallery of sites
As described in the title, I wonder if we want to add scikit-learn to the list of pydata-sphinx-theme gallery of sites: https://pydata-sphinx-theme.readthedocs.io/en/stable/examples/gallery.html. If we do I can ask pydata-sphinx-theme about it.
COMMENT:
... | 29,849 |
https://github.com/scikit-learn/scikit-learn/issues/29849 | [
"Documentation",
"RFC"
] | Adding scikit-learn to the pydata-sphinx-theme gallery of sites
As described in the title, I wonder if we want to add scikit-learn to the list of pydata-sphinx-theme gallery of sites: https://pydata-sphinx-theme.readthedocs.io/en/stable/examples/gallery.html. If we do I can ask pydata-sphinx-theme about it.
COMMENT:
... | 29,849 |
https://github.com/scikit-learn/scikit-learn/issues/29837 | [
"New Feature",
"Needs Decision"
] | Add float as acceptable input for n_jobs
### Describe the workflow you want to enable
Float may be used as possible input for n_jobs. That is, allowing selection of set percentage of the machine's CPU core count.
### Describe your proposed solution
When n_jobs is a float (in the range `(0.0, 1.0]`), the numb... | 29,837 |
https://github.com/scikit-learn/scikit-learn/issues/29837 | [
"New Feature",
"Needs Decision"
] | Add float as acceptable input for n_jobs
### Describe the workflow you want to enable
Float may be used as possible input for n_jobs. That is, allowing selection of set percentage of the machine's CPU core count.
### Describe your proposed solution
When n_jobs is a float (in the range `(0.0, 1.0]`), the numb... | 29,837 |
https://github.com/scikit-learn/scikit-learn/issues/29837 | [
"New Feature",
"Needs Decision"
] | Add float as acceptable input for n_jobs
### Describe the workflow you want to enable
Float may be used as possible input for n_jobs. That is, allowing selection of set percentage of the machine's CPU core count.
### Describe your proposed solution
When n_jobs is a float (in the range `(0.0, 1.0]`), the numb... | 29,837 |
https://github.com/scikit-learn/scikit-learn/issues/29837 | [
"New Feature",
"Needs Decision"
] | Add float as acceptable input for n_jobs
### Describe the workflow you want to enable
Float may be used as possible input for n_jobs. That is, allowing selection of set percentage of the machine's CPU core count.
### Describe your proposed solution
When n_jobs is a float (in the range `(0.0, 1.0]`), the numb... | 29,837 |
https://github.com/scikit-learn/scikit-learn/issues/29837 | [
"New Feature",
"Needs Decision"
] | Add float as acceptable input for n_jobs
### Describe the workflow you want to enable
Float may be used as possible input for n_jobs. That is, allowing selection of set percentage of the machine's CPU core count.
### Describe your proposed solution
When n_jobs is a float (in the range `(0.0, 1.0]`), the numb... | 29,837 |
https://github.com/scikit-learn/scikit-learn/issues/29837 | [
"New Feature",
"Needs Decision"
] | Add float as acceptable input for n_jobs
### Describe the workflow you want to enable
Float may be used as possible input for n_jobs. That is, allowing selection of set percentage of the machine's CPU core count.
### Describe your proposed solution
When n_jobs is a float (in the range `(0.0, 1.0]`), the numb... | 29,837 |
https://github.com/scikit-learn/scikit-learn/issues/29836 | [
"Bug",
"Needs Triage"
] | Incorrect calculation of Precision and Recall score from
### Describe the bug
The values calculated for the precision and recall seems to be in opposite of each other.
### Steps/Code to Reproduce
```
from sklearn.metrics import accuracy_score # Accuracy = (TP + TN) / (TP + TN + FP + FN)
from sklearn.metrics impo... | 29,836 |
https://github.com/scikit-learn/scikit-learn/issues/29830 | [
"Build / CI"
] | ⚠️ CI failed on Wheel builder (last failure: Sep 13, 2024) ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/10842683629)** (Sep 13, 2024)
COMMENT:
## CI is no longer failing! ✅
[Successful run](https://github.com/scikit-learn/scikit-learn/actions/runs/10859271523)... | 29,830 |
https://github.com/scikit-learn/scikit-learn/issues/29829 | [
"Build / CI"
] | ⚠️ CI failed on Linux_free_threaded.pylatest_pip_free_threaded (last failure: Sep 13, 2024) ⚠️
**CI is still failing on [Linux_free_threaded.pylatest_pip_free_threaded](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=70215&view=logs&j=8bc43b48-889f-54b9-cd8b-781ee8447bf2)** (Sep 13, 2024)
Unable... | 29,829 |
https://github.com/scikit-learn/scikit-learn/issues/29829 | [
"Build / CI"
] | ⚠️ CI failed on Linux_free_threaded.pylatest_pip_free_threaded (last failure: Sep 13, 2024) ⚠️
**CI is still failing on [Linux_free_threaded.pylatest_pip_free_threaded](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=70215&view=logs&j=8bc43b48-889f-54b9-cd8b-781ee8447bf2)** (Sep 13, 2024)
Unable... | 29,829 |
https://github.com/scikit-learn/scikit-learn/issues/29829 | [
"Build / CI"
] | ⚠️ CI failed on Linux_free_threaded.pylatest_pip_free_threaded (last failure: Sep 13, 2024) ⚠️
**CI is still failing on [Linux_free_threaded.pylatest_pip_free_threaded](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=70215&view=logs&j=8bc43b48-889f-54b9-cd8b-781ee8447bf2)** (Sep 13, 2024)
Unable... | 29,829 |
https://github.com/scikit-learn/scikit-learn/issues/29829 | [
"Build / CI"
] | ⚠️ CI failed on Linux_free_threaded.pylatest_pip_free_threaded (last failure: Sep 13, 2024) ⚠️
**CI is still failing on [Linux_free_threaded.pylatest_pip_free_threaded](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=70215&view=logs&j=8bc43b48-889f-54b9-cd8b-781ee8447bf2)** (Sep 13, 2024)
Unable... | 29,829 |
https://github.com/scikit-learn/scikit-learn/issues/29827 | [
"Bug",
"API"
] | SimpleImputer does not drop a column full of `np.nan` even when `keep_empty_feature=False`
The following code snippet lead to some surprises:
```python
import numpy as np
from sklearn.datasets import load_iris
from sklearn.impute import SimpleImputer
X, y = load_iris(return_X_y=True)
X[:, 0] = np.nan
impu... | 29,827 |
https://github.com/scikit-learn/scikit-learn/issues/29827 | [
"Bug",
"API"
] | SimpleImputer does not drop a column full of `np.nan` even when `keep_empty_feature=False`
The following code snippet lead to some surprises:
```python
import numpy as np
from sklearn.datasets import load_iris
from sklearn.impute import SimpleImputer
X, y = load_iris(return_X_y=True)
X[:, 0] = np.nan
impu... | 29,827 |
https://github.com/scikit-learn/scikit-learn/issues/29827 | [
"Bug",
"API"
] | SimpleImputer does not drop a column full of `np.nan` even when `keep_empty_feature=False`
The following code snippet lead to some surprises:
```python
import numpy as np
from sklearn.datasets import load_iris
from sklearn.impute import SimpleImputer
X, y = load_iris(return_X_y=True)
X[:, 0] = np.nan
impu... | 29,827 |
https://github.com/scikit-learn/scikit-learn/issues/29827 | [
"Bug",
"API"
] | SimpleImputer does not drop a column full of `np.nan` even when `keep_empty_feature=False`
The following code snippet lead to some surprises:
```python
import numpy as np
from sklearn.datasets import load_iris
from sklearn.impute import SimpleImputer
X, y = load_iris(return_X_y=True)
X[:, 0] = np.nan
impu... | 29,827 |
https://github.com/scikit-learn/scikit-learn/issues/29827 | [
"Bug",
"API"
] | SimpleImputer does not drop a column full of `np.nan` even when `keep_empty_feature=False`
The following code snippet lead to some surprises:
```python
import numpy as np
from sklearn.datasets import load_iris
from sklearn.impute import SimpleImputer
X, y = load_iris(return_X_y=True)
X[:, 0] = np.nan
impu... | 29,827 |
https://github.com/scikit-learn/scikit-learn/issues/29823 | [
"Documentation"
] | Misleading variable name for the example of AUC calculation
### Describe the issue linked to the documentation
In the [example of AUC calculation](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.auc.html), it was given that:
```python
import numpy as np
from sklearn import metrics
y = np.arra... | 29,823 |
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