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/27306 | [
"Bug"
] | ConfusionMatrixDisplay does not correctly change text color when confusion matrix contains NaN
### Describe the bug
In our specific usecase we generate a Confusion Matrix using our own software to be passed on to ConfusionMatrixDisplay. Due to the nature of our needs this confusion matrix could contain one or more ... | 27,306 |
https://github.com/scikit-learn/scikit-learn/issues/27306 | [
"Bug"
] | ConfusionMatrixDisplay does not correctly change text color when confusion matrix contains NaN
### Describe the bug
In our specific usecase we generate a Confusion Matrix using our own software to be passed on to ConfusionMatrixDisplay. Due to the nature of our needs this confusion matrix could contain one or more ... | 27,306 |
https://github.com/scikit-learn/scikit-learn/issues/27305 | [
"New Feature",
"Moderate",
"module:ensemble"
] | Monotonicity constraints for GradientBoostingClassifier and GradientBoostingRegressor
### Describe the workflow you want to enable
As a follow-up of #13649, I'd like to use
```python
GradientBoostingClassifier(monotonic_cst=...)
```
same as in `HistGradientBoostingClassifier` and int `RandomForestClassifier`.
##... | 27,305 |
https://github.com/scikit-learn/scikit-learn/issues/27302 | [
"Needs Triage"
] | ⚠️ CI failed on macOS.pylatest_conda_mkl_no_openmp ⚠️
**CI failed on [macOS.pylatest_conda_mkl_no_openmp](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=58670&view=logs&j=e6d5b7c0-0dfd-5ddf-13d5-c71bebf56ce2)** (Sep 06, 2023)
- test_pickle_version_warning_is_issued_when_no_version_info_in_pickl... | 27,302 |
https://github.com/scikit-learn/scikit-learn/issues/27302 | [
"Needs Triage"
] | ⚠️ CI failed on macOS.pylatest_conda_mkl_no_openmp ⚠️
**CI failed on [macOS.pylatest_conda_mkl_no_openmp](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=58670&view=logs&j=e6d5b7c0-0dfd-5ddf-13d5-c71bebf56ce2)** (Sep 06, 2023)
- test_pickle_version_warning_is_issued_when_no_version_info_in_pickl... | 27,302 |
https://github.com/scikit-learn/scikit-learn/issues/27294 | [
"New Feature",
"Needs Triage"
] | Incremental F-regression
### Describe the workflow you want to enable
For situations with many variables and low memory, for example lags taken from a high frequency time series and corresponding exogenous variables, it's possible to go though each column one by one or in batches, in an ordered manner, select the m... | 27,294 |
https://github.com/scikit-learn/scikit-learn/issues/27294 | [
"New Feature",
"Needs Triage"
] | Incremental F-regression
### Describe the workflow you want to enable
For situations with many variables and low memory, for example lags taken from a high frequency time series and corresponding exogenous variables, it's possible to go though each column one by one or in batches, in an ordered manner, select the m... | 27,294 |
https://github.com/scikit-learn/scikit-learn/issues/27285 | [
"Documentation"
] | Weighted ridge regression regularization variable is dependent on sample weight magnitude
### Describe the issue linked to the documentation
When doing weighted ridge regression, the value of the regularization parameter for a particular solution is dependent on the sample weight vector due to scaling in the implemen... | 27,285 |
https://github.com/scikit-learn/scikit-learn/issues/27285 | [
"Documentation"
] | Weighted ridge regression regularization variable is dependent on sample weight magnitude
### Describe the issue linked to the documentation
When doing weighted ridge regression, the value of the regularization parameter for a particular solution is dependent on the sample weight vector due to scaling in the implemen... | 27,285 |
https://github.com/scikit-learn/scikit-learn/issues/27272 | [
"Bug",
"Needs Triage"
] | MultiOutputRegressor _ BUG
### Describe the bug
```pytb
from sklearn.multioutput import MultiOutputRegressor
File "../lib/python3.10/site-packages/sklearn/multioutput.py", line 45, in <module>
from .utils.validation import _check_fit_params, check_is_fitted, has_fit_parameter
ImportError: cannot import n... | 27,272 |
https://github.com/scikit-learn/scikit-learn/issues/27272 | [
"Bug",
"Needs Triage"
] | MultiOutputRegressor _ BUG
### Describe the bug
```pytb
from sklearn.multioutput import MultiOutputRegressor
File "../lib/python3.10/site-packages/sklearn/multioutput.py", line 45, in <module>
from .utils.validation import _check_fit_params, check_is_fitted, has_fit_parameter
ImportError: cannot import n... | 27,272 |
https://github.com/scikit-learn/scikit-learn/issues/27272 | [
"Bug",
"Needs Triage"
] | MultiOutputRegressor _ BUG
### Describe the bug
```pytb
from sklearn.multioutput import MultiOutputRegressor
File "../lib/python3.10/site-packages/sklearn/multioutput.py", line 45, in <module>
from .utils.validation import _check_fit_params, check_is_fitted, has_fit_parameter
ImportError: cannot import n... | 27,272 |
https://github.com/scikit-learn/scikit-learn/issues/27272 | [
"Bug",
"Needs Triage"
] | MultiOutputRegressor _ BUG
### Describe the bug
```pytb
from sklearn.multioutput import MultiOutputRegressor
File "../lib/python3.10/site-packages/sklearn/multioutput.py", line 45, in <module>
from .utils.validation import _check_fit_params, check_is_fitted, has_fit_parameter
ImportError: cannot import n... | 27,272 |
https://github.com/scikit-learn/scikit-learn/issues/27271 | [
"Bug",
"Needs Triage"
] | feature_names returned by load_breast_cancer() is np.array, not list.
### Describe the bug
According to the online documentation(https://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_breast_cancer.html), `feature_names` and `target_names` should be a list, but the value returned by the `load_breast_... | 27,271 |
https://github.com/scikit-learn/scikit-learn/issues/27271 | [
"Bug",
"Needs Triage"
] | feature_names returned by load_breast_cancer() is np.array, not list.
### Describe the bug
According to the online documentation(https://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_breast_cancer.html), `feature_names` and `target_names` should be a list, but the value returned by the `load_breast_... | 27,271 |
https://github.com/scikit-learn/scikit-learn/issues/27271 | [
"Bug",
"Needs Triage"
] | feature_names returned by load_breast_cancer() is np.array, not list.
### Describe the bug
According to the online documentation(https://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_breast_cancer.html), `feature_names` and `target_names` should be a list, but the value returned by the `load_breast_... | 27,271 |
https://github.com/scikit-learn/scikit-learn/issues/27268 | [
"Build / CI"
] | macOS.pylatest_conda_forge_mkl sometimes fails pickling test
This test has failed in https://github.com/scikit-learn/scikit-learn/pull/27266 with [those logs](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=58609&view=logs&j=97641769-79fb-5590-9088-a30ce9b850b9&t=4745baa1-36b5-56c8-9a8e-6480742d... | 27,268 |
https://github.com/scikit-learn/scikit-learn/issues/27268 | [
"Build / CI"
] | macOS.pylatest_conda_forge_mkl sometimes fails pickling test
This test has failed in https://github.com/scikit-learn/scikit-learn/pull/27266 with [those logs](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=58609&view=logs&j=97641769-79fb-5590-9088-a30ce9b850b9&t=4745baa1-36b5-56c8-9a8e-6480742d... | 27,268 |
https://github.com/scikit-learn/scikit-learn/issues/27268 | [
"Build / CI"
] | macOS.pylatest_conda_forge_mkl sometimes fails pickling test
This test has failed in https://github.com/scikit-learn/scikit-learn/pull/27266 with [those logs](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=58609&view=logs&j=97641769-79fb-5590-9088-a30ce9b850b9&t=4745baa1-36b5-56c8-9a8e-6480742d... | 27,268 |
https://github.com/scikit-learn/scikit-learn/issues/27268 | [
"Build / CI"
] | macOS.pylatest_conda_forge_mkl sometimes fails pickling test
This test has failed in https://github.com/scikit-learn/scikit-learn/pull/27266 with [those logs](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=58609&view=logs&j=97641769-79fb-5590-9088-a30ce9b850b9&t=4745baa1-36b5-56c8-9a8e-6480742d... | 27,268 |
https://github.com/scikit-learn/scikit-learn/issues/27260 | [
"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=58565&view=logs&j=c8afde5f-ef70-5983-62e8-c6b665ad6161)** (Sep 01, 2023)
- test_pairwise_distances_argkmin[45-float32-parallel_on_X-cityblock-... | 27,260 |
https://github.com/scikit-learn/scikit-learn/issues/27260 | [
"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=58565&view=logs&j=c8afde5f-ef70-5983-62e8-c6b665ad6161)** (Sep 01, 2023)
- test_pairwise_distances_argkmin[45-float32-parallel_on_X-cityblock-... | 27,260 |
https://github.com/scikit-learn/scikit-learn/issues/27259 | [
"New Feature",
"Needs Decision - Include Feature"
] | New clustering metrics
### Describe the workflow you want to enable
Scikit-learn defines three popular metrics for evaluating clustering performance when there are no ground-truth cluster labels: [sklearn.metrics.silhouette_score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html... | 27,259 |
https://github.com/scikit-learn/scikit-learn/issues/27259 | [
"New Feature",
"Needs Decision - Include Feature"
] | New clustering metrics
### Describe the workflow you want to enable
Scikit-learn defines three popular metrics for evaluating clustering performance when there are no ground-truth cluster labels: [sklearn.metrics.silhouette_score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html... | 27,259 |
https://github.com/scikit-learn/scikit-learn/issues/27259 | [
"New Feature",
"Needs Decision - Include Feature"
] | New clustering metrics
### Describe the workflow you want to enable
Scikit-learn defines three popular metrics for evaluating clustering performance when there are no ground-truth cluster labels: [sklearn.metrics.silhouette_score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html... | 27,259 |
https://github.com/scikit-learn/scikit-learn/issues/27259 | [
"New Feature",
"Needs Decision - Include Feature"
] | New clustering metrics
### Describe the workflow you want to enable
Scikit-learn defines three popular metrics for evaluating clustering performance when there are no ground-truth cluster labels: [sklearn.metrics.silhouette_score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html... | 27,259 |
https://github.com/scikit-learn/scikit-learn/issues/27259 | [
"New Feature",
"Needs Decision - Include Feature"
] | New clustering metrics
### Describe the workflow you want to enable
Scikit-learn defines three popular metrics for evaluating clustering performance when there are no ground-truth cluster labels: [sklearn.metrics.silhouette_score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html... | 27,259 |
https://github.com/scikit-learn/scikit-learn/issues/27259 | [
"New Feature",
"Needs Decision - Include Feature"
] | New clustering metrics
### Describe the workflow you want to enable
Scikit-learn defines three popular metrics for evaluating clustering performance when there are no ground-truth cluster labels: [sklearn.metrics.silhouette_score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html... | 27,259 |
https://github.com/scikit-learn/scikit-learn/issues/27259 | [
"New Feature",
"Needs Decision - Include Feature"
] | New clustering metrics
### Describe the workflow you want to enable
Scikit-learn defines three popular metrics for evaluating clustering performance when there are no ground-truth cluster labels: [sklearn.metrics.silhouette_score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html... | 27,259 |
https://github.com/scikit-learn/scikit-learn/issues/27259 | [
"New Feature",
"Needs Decision - Include Feature"
] | New clustering metrics
### Describe the workflow you want to enable
Scikit-learn defines three popular metrics for evaluating clustering performance when there are no ground-truth cluster labels: [sklearn.metrics.silhouette_score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html... | 27,259 |
https://github.com/scikit-learn/scikit-learn/issues/27259 | [
"New Feature",
"Needs Decision - Include Feature"
] | New clustering metrics
### Describe the workflow you want to enable
Scikit-learn defines three popular metrics for evaluating clustering performance when there are no ground-truth cluster labels: [sklearn.metrics.silhouette_score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html... | 27,259 |
https://github.com/scikit-learn/scikit-learn/issues/27259 | [
"New Feature",
"Needs Decision - Include Feature"
] | New clustering metrics
### Describe the workflow you want to enable
Scikit-learn defines three popular metrics for evaluating clustering performance when there are no ground-truth cluster labels: [sklearn.metrics.silhouette_score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html... | 27,259 |
https://github.com/scikit-learn/scikit-learn/issues/27259 | [
"New Feature",
"Needs Decision - Include Feature"
] | New clustering metrics
### Describe the workflow you want to enable
Scikit-learn defines three popular metrics for evaluating clustering performance when there are no ground-truth cluster labels: [sklearn.metrics.silhouette_score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html... | 27,259 |
https://github.com/scikit-learn/scikit-learn/issues/27259 | [
"New Feature",
"Needs Decision - Include Feature"
] | New clustering metrics
### Describe the workflow you want to enable
Scikit-learn defines three popular metrics for evaluating clustering performance when there are no ground-truth cluster labels: [sklearn.metrics.silhouette_score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html... | 27,259 |
https://github.com/scikit-learn/scikit-learn/issues/27259 | [
"New Feature",
"Needs Decision - Include Feature"
] | New clustering metrics
### Describe the workflow you want to enable
Scikit-learn defines three popular metrics for evaluating clustering performance when there are no ground-truth cluster labels: [sklearn.metrics.silhouette_score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html... | 27,259 |
https://github.com/scikit-learn/scikit-learn/issues/27259 | [
"New Feature",
"Needs Decision - Include Feature"
] | New clustering metrics
### Describe the workflow you want to enable
Scikit-learn defines three popular metrics for evaluating clustering performance when there are no ground-truth cluster labels: [sklearn.metrics.silhouette_score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html... | 27,259 |
https://github.com/scikit-learn/scikit-learn/issues/27259 | [
"New Feature",
"Needs Decision - Include Feature"
] | New clustering metrics
### Describe the workflow you want to enable
Scikit-learn defines three popular metrics for evaluating clustering performance when there are no ground-truth cluster labels: [sklearn.metrics.silhouette_score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html... | 27,259 |
https://github.com/scikit-learn/scikit-learn/issues/27259 | [
"New Feature",
"Needs Decision - Include Feature"
] | New clustering metrics
### Describe the workflow you want to enable
Scikit-learn defines three popular metrics for evaluating clustering performance when there are no ground-truth cluster labels: [sklearn.metrics.silhouette_score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html... | 27,259 |
https://github.com/scikit-learn/scikit-learn/issues/27259 | [
"New Feature",
"Needs Decision - Include Feature"
] | New clustering metrics
### Describe the workflow you want to enable
Scikit-learn defines three popular metrics for evaluating clustering performance when there are no ground-truth cluster labels: [sklearn.metrics.silhouette_score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html... | 27,259 |
https://github.com/scikit-learn/scikit-learn/issues/27259 | [
"New Feature",
"Needs Decision - Include Feature"
] | New clustering metrics
### Describe the workflow you want to enable
Scikit-learn defines three popular metrics for evaluating clustering performance when there are no ground-truth cluster labels: [sklearn.metrics.silhouette_score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html... | 27,259 |
https://github.com/scikit-learn/scikit-learn/issues/27259 | [
"New Feature",
"Needs Decision - Include Feature"
] | New clustering metrics
### Describe the workflow you want to enable
Scikit-learn defines three popular metrics for evaluating clustering performance when there are no ground-truth cluster labels: [sklearn.metrics.silhouette_score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html... | 27,259 |
https://github.com/scikit-learn/scikit-learn/issues/27259 | [
"New Feature",
"Needs Decision - Include Feature"
] | New clustering metrics
### Describe the workflow you want to enable
Scikit-learn defines three popular metrics for evaluating clustering performance when there are no ground-truth cluster labels: [sklearn.metrics.silhouette_score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html... | 27,259 |
https://github.com/scikit-learn/scikit-learn/issues/27259 | [
"New Feature",
"Needs Decision - Include Feature"
] | New clustering metrics
### Describe the workflow you want to enable
Scikit-learn defines three popular metrics for evaluating clustering performance when there are no ground-truth cluster labels: [sklearn.metrics.silhouette_score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html... | 27,259 |
https://github.com/scikit-learn/scikit-learn/issues/27259 | [
"New Feature",
"Needs Decision - Include Feature"
] | New clustering metrics
### Describe the workflow you want to enable
Scikit-learn defines three popular metrics for evaluating clustering performance when there are no ground-truth cluster labels: [sklearn.metrics.silhouette_score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html... | 27,259 |
https://github.com/scikit-learn/scikit-learn/issues/27259 | [
"New Feature",
"Needs Decision - Include Feature"
] | New clustering metrics
### Describe the workflow you want to enable
Scikit-learn defines three popular metrics for evaluating clustering performance when there are no ground-truth cluster labels: [sklearn.metrics.silhouette_score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html... | 27,259 |
https://github.com/scikit-learn/scikit-learn/issues/27259 | [
"New Feature",
"Needs Decision - Include Feature"
] | New clustering metrics
### Describe the workflow you want to enable
Scikit-learn defines three popular metrics for evaluating clustering performance when there are no ground-truth cluster labels: [sklearn.metrics.silhouette_score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html... | 27,259 |
https://github.com/scikit-learn/scikit-learn/issues/27259 | [
"New Feature",
"Needs Decision - Include Feature"
] | New clustering metrics
### Describe the workflow you want to enable
Scikit-learn defines three popular metrics for evaluating clustering performance when there are no ground-truth cluster labels: [sklearn.metrics.silhouette_score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html... | 27,259 |
https://github.com/scikit-learn/scikit-learn/issues/27259 | [
"New Feature",
"Needs Decision - Include Feature"
] | New clustering metrics
### Describe the workflow you want to enable
Scikit-learn defines three popular metrics for evaluating clustering performance when there are no ground-truth cluster labels: [sklearn.metrics.silhouette_score](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html... | 27,259 |
https://github.com/scikit-learn/scikit-learn/issues/27256 | [
"Bug",
"Needs Triage"
] | Lasso incompatible with scipy=1.11 with sparse X
### Describe the bug
The Lasso() regressor seems to be incompatible with the newest release of scipy=1.11.0 with sparse X input.
### Steps/Code to Reproduce
```
import numpy as np
from scipy.sparse import csc_array
from sklearn.linear_model import Lasso
if _... | 27,256 |
https://github.com/scikit-learn/scikit-learn/issues/27256 | [
"Bug",
"Needs Triage"
] | Lasso incompatible with scipy=1.11 with sparse X
### Describe the bug
The Lasso() regressor seems to be incompatible with the newest release of scipy=1.11.0 with sparse X input.
### Steps/Code to Reproduce
```
import numpy as np
from scipy.sparse import csc_array
from sklearn.linear_model import Lasso
if _... | 27,256 |
https://github.com/scikit-learn/scikit-learn/issues/27255 | [
"Documentation",
"Needs Triage"
] | Issue in copy to clipboard while Installing
### Describe the issue linked to the documentation
While I was installing scikit-learn I found a small issue when I do select Copy to Clipboard it is not copying the actual text which is "pip install -U scikit-learn"
instead it is copying like
"python3 -m venv sklearn-v... | 27,255 |
https://github.com/scikit-learn/scikit-learn/issues/27249 | [
"New Feature",
"module:metrics",
"Needs Triage"
] | sklearn.metrics.logAUC
### Describe the workflow you want to enable
Computing logAUC values.
### Describe your proposed solution
$LogAUC_\lambda=\frac{\sum_{i}^{where~x_i\ge\lambda} (\log_{10} x_{i+1} - \log_{10} x_i)(\frac{y_{i+1}+y_i}{2})}{\log_{10}\frac{1}{\lambda}}$
### Describe alternatives you've considered... | 27,249 |
https://github.com/scikit-learn/scikit-learn/issues/27249 | [
"New Feature",
"module:metrics",
"Needs Triage"
] | sklearn.metrics.logAUC
### Describe the workflow you want to enable
Computing logAUC values.
### Describe your proposed solution
$LogAUC_\lambda=\frac{\sum_{i}^{where~x_i\ge\lambda} (\log_{10} x_{i+1} - \log_{10} x_i)(\frac{y_{i+1}+y_i}{2})}{\log_{10}\frac{1}{\lambda}}$
### Describe alternatives you've considered... | 27,249 |
https://github.com/scikit-learn/scikit-learn/issues/27249 | [
"New Feature",
"module:metrics",
"Needs Triage"
] | sklearn.metrics.logAUC
### Describe the workflow you want to enable
Computing logAUC values.
### Describe your proposed solution
$LogAUC_\lambda=\frac{\sum_{i}^{where~x_i\ge\lambda} (\log_{10} x_{i+1} - \log_{10} x_i)(\frac{y_{i+1}+y_i}{2})}{\log_{10}\frac{1}{\lambda}}$
### Describe alternatives you've considered... | 27,249 |
https://github.com/scikit-learn/scikit-learn/issues/27249 | [
"New Feature",
"module:metrics",
"Needs Triage"
] | sklearn.metrics.logAUC
### Describe the workflow you want to enable
Computing logAUC values.
### Describe your proposed solution
$LogAUC_\lambda=\frac{\sum_{i}^{where~x_i\ge\lambda} (\log_{10} x_{i+1} - \log_{10} x_i)(\frac{y_{i+1}+y_i}{2})}{\log_{10}\frac{1}{\lambda}}$
### Describe alternatives you've considered... | 27,249 |
https://github.com/scikit-learn/scikit-learn/issues/27249 | [
"New Feature",
"module:metrics",
"Needs Triage"
] | sklearn.metrics.logAUC
### Describe the workflow you want to enable
Computing logAUC values.
### Describe your proposed solution
$LogAUC_\lambda=\frac{\sum_{i}^{where~x_i\ge\lambda} (\log_{10} x_{i+1} - \log_{10} x_i)(\frac{y_{i+1}+y_i}{2})}{\log_{10}\frac{1}{\lambda}}$
### Describe alternatives you've considered... | 27,249 |
https://github.com/scikit-learn/scikit-learn/issues/27249 | [
"New Feature",
"module:metrics",
"Needs Triage"
] | sklearn.metrics.logAUC
### Describe the workflow you want to enable
Computing logAUC values.
### Describe your proposed solution
$LogAUC_\lambda=\frac{\sum_{i}^{where~x_i\ge\lambda} (\log_{10} x_{i+1} - \log_{10} x_i)(\frac{y_{i+1}+y_i}{2})}{\log_{10}\frac{1}{\lambda}}$
### Describe alternatives you've considered... | 27,249 |
https://github.com/scikit-learn/scikit-learn/issues/27249 | [
"New Feature",
"module:metrics",
"Needs Triage"
] | sklearn.metrics.logAUC
### Describe the workflow you want to enable
Computing logAUC values.
### Describe your proposed solution
$LogAUC_\lambda=\frac{\sum_{i}^{where~x_i\ge\lambda} (\log_{10} x_{i+1} - \log_{10} x_i)(\frac{y_{i+1}+y_i}{2})}{\log_{10}\frac{1}{\lambda}}$
### Describe alternatives you've considered... | 27,249 |
https://github.com/scikit-learn/scikit-learn/issues/27249 | [
"New Feature",
"module:metrics",
"Needs Triage"
] | sklearn.metrics.logAUC
### Describe the workflow you want to enable
Computing logAUC values.
### Describe your proposed solution
$LogAUC_\lambda=\frac{\sum_{i}^{where~x_i\ge\lambda} (\log_{10} x_{i+1} - \log_{10} x_i)(\frac{y_{i+1}+y_i}{2})}{\log_{10}\frac{1}{\lambda}}$
### Describe alternatives you've considered... | 27,249 |
https://github.com/scikit-learn/scikit-learn/issues/27236 | [
"Bug"
] | BisectingKmeans - intertia per cluster
### Describe the bug
Hi,
I have been using the sklearn package recently for some simple clustering. It appears to me that there is a typo in the BisectingKMeans class. In the `_inertia_per_cluster` method, we need to compute the inertia per-cluster. However, in the current ve... | 27,236 |
https://github.com/scikit-learn/scikit-learn/issues/27200 | [
"New Feature",
"Needs Decision",
"Needs Decision - Include Feature"
] | Implementation of Robust Random Cut Forest (RRCF) Algorithm
### Describe the workflow you want to enable
Enable users to perform robust anomaly detection using the Robust Random Cut Forest (RRCF) algorithm within the scikit-learn library.
### Describe your proposed solution
## Proposed Solution
I suggest t... | 27,200 |
https://github.com/scikit-learn/scikit-learn/issues/27200 | [
"New Feature",
"Needs Decision",
"Needs Decision - Include Feature"
] | Implementation of Robust Random Cut Forest (RRCF) Algorithm
### Describe the workflow you want to enable
Enable users to perform robust anomaly detection using the Robust Random Cut Forest (RRCF) algorithm within the scikit-learn library.
### Describe your proposed solution
## Proposed Solution
I suggest t... | 27,200 |
https://github.com/scikit-learn/scikit-learn/issues/27200 | [
"New Feature",
"Needs Decision",
"Needs Decision - Include Feature"
] | Implementation of Robust Random Cut Forest (RRCF) Algorithm
### Describe the workflow you want to enable
Enable users to perform robust anomaly detection using the Robust Random Cut Forest (RRCF) algorithm within the scikit-learn library.
### Describe your proposed solution
## Proposed Solution
I suggest t... | 27,200 |
https://github.com/scikit-learn/scikit-learn/issues/27200 | [
"New Feature",
"Needs Decision",
"Needs Decision - Include Feature"
] | Implementation of Robust Random Cut Forest (RRCF) Algorithm
### Describe the workflow you want to enable
Enable users to perform robust anomaly detection using the Robust Random Cut Forest (RRCF) algorithm within the scikit-learn library.
### Describe your proposed solution
## Proposed Solution
I suggest t... | 27,200 |
https://github.com/scikit-learn/scikit-learn/issues/27200 | [
"New Feature",
"Needs Decision",
"Needs Decision - Include Feature"
] | Implementation of Robust Random Cut Forest (RRCF) Algorithm
### Describe the workflow you want to enable
Enable users to perform robust anomaly detection using the Robust Random Cut Forest (RRCF) algorithm within the scikit-learn library.
### Describe your proposed solution
## Proposed Solution
I suggest t... | 27,200 |
https://github.com/scikit-learn/scikit-learn/issues/27200 | [
"New Feature",
"Needs Decision",
"Needs Decision - Include Feature"
] | Implementation of Robust Random Cut Forest (RRCF) Algorithm
### Describe the workflow you want to enable
Enable users to perform robust anomaly detection using the Robust Random Cut Forest (RRCF) algorithm within the scikit-learn library.
### Describe your proposed solution
## Proposed Solution
I suggest t... | 27,200 |
https://github.com/scikit-learn/scikit-learn/issues/27200 | [
"New Feature",
"Needs Decision",
"Needs Decision - Include Feature"
] | Implementation of Robust Random Cut Forest (RRCF) Algorithm
### Describe the workflow you want to enable
Enable users to perform robust anomaly detection using the Robust Random Cut Forest (RRCF) algorithm within the scikit-learn library.
### Describe your proposed solution
## Proposed Solution
I suggest t... | 27,200 |
https://github.com/scikit-learn/scikit-learn/issues/27200 | [
"New Feature",
"Needs Decision",
"Needs Decision - Include Feature"
] | Implementation of Robust Random Cut Forest (RRCF) Algorithm
### Describe the workflow you want to enable
Enable users to perform robust anomaly detection using the Robust Random Cut Forest (RRCF) algorithm within the scikit-learn library.
### Describe your proposed solution
## Proposed Solution
I suggest t... | 27,200 |
https://github.com/scikit-learn/scikit-learn/issues/27200 | [
"New Feature",
"Needs Decision",
"Needs Decision - Include Feature"
] | Implementation of Robust Random Cut Forest (RRCF) Algorithm
### Describe the workflow you want to enable
Enable users to perform robust anomaly detection using the Robust Random Cut Forest (RRCF) algorithm within the scikit-learn library.
### Describe your proposed solution
## Proposed Solution
I suggest t... | 27,200 |
https://github.com/scikit-learn/scikit-learn/issues/27200 | [
"New Feature",
"Needs Decision",
"Needs Decision - Include Feature"
] | Implementation of Robust Random Cut Forest (RRCF) Algorithm
### Describe the workflow you want to enable
Enable users to perform robust anomaly detection using the Robust Random Cut Forest (RRCF) algorithm within the scikit-learn library.
### Describe your proposed solution
## Proposed Solution
I suggest t... | 27,200 |
https://github.com/scikit-learn/scikit-learn/issues/27200 | [
"New Feature",
"Needs Decision",
"Needs Decision - Include Feature"
] | Implementation of Robust Random Cut Forest (RRCF) Algorithm
### Describe the workflow you want to enable
Enable users to perform robust anomaly detection using the Robust Random Cut Forest (RRCF) algorithm within the scikit-learn library.
### Describe your proposed solution
## Proposed Solution
I suggest t... | 27,200 |
https://github.com/scikit-learn/scikit-learn/issues/27200 | [
"New Feature",
"Needs Decision",
"Needs Decision - Include Feature"
] | Implementation of Robust Random Cut Forest (RRCF) Algorithm
### Describe the workflow you want to enable
Enable users to perform robust anomaly detection using the Robust Random Cut Forest (RRCF) algorithm within the scikit-learn library.
### Describe your proposed solution
## Proposed Solution
I suggest t... | 27,200 |
https://github.com/scikit-learn/scikit-learn/issues/27200 | [
"New Feature",
"Needs Decision",
"Needs Decision - Include Feature"
] | Implementation of Robust Random Cut Forest (RRCF) Algorithm
### Describe the workflow you want to enable
Enable users to perform robust anomaly detection using the Robust Random Cut Forest (RRCF) algorithm within the scikit-learn library.
### Describe your proposed solution
## Proposed Solution
I suggest t... | 27,200 |
https://github.com/scikit-learn/scikit-learn/issues/27197 | [
"Needs Triage"
] | ⚠️ CI failed on Wheel builder ⚠️
**CI failed on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/6007650858)** (Aug 29, 2023)
COMMENT:
## CI is no longer failing! ✅
[Successful run](https://github.com/scikit-learn/scikit-learn/actions/runs/6020290075) on Aug 30, 2023 | 27,197 |
https://github.com/scikit-learn/scikit-learn/issues/27195 | [
"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=58415&view=logs&j=78a0bf4f-79e5-5387-94ec-13e67d216d6e)** (Aug 29, 2023)
- test_pairwise_distances_argkmin[45-float32-parallel_on_X-cityblock-... | 27,195 |
https://github.com/scikit-learn/scikit-learn/issues/27195 | [
"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=58415&view=logs&j=78a0bf4f-79e5-5387-94ec-13e67d216d6e)** (Aug 29, 2023)
- test_pairwise_distances_argkmin[45-float32-parallel_on_X-cityblock-... | 27,195 |
https://github.com/scikit-learn/scikit-learn/issues/27193 | [
"Documentation"
] | Better documentation for `RFECV`
There is almost no description in the documentation of how `RFECV` actually works. The [user guide](https://scikit-learn.org/stable/modules/feature_selection.html#rfe) simply says
> [RFECV](https://scikit-learn.org/stable/modules/generated/sklearn.feature_selection.RFECV.html#sklear... | 27,193 |
https://github.com/scikit-learn/scikit-learn/issues/27193 | [
"Documentation"
] | Better documentation for `RFECV`
There is almost no description in the documentation of how `RFECV` actually works. The [user guide](https://scikit-learn.org/stable/modules/feature_selection.html#rfe) simply says
> [RFECV](https://scikit-learn.org/stable/modules/generated/sklearn.feature_selection.RFECV.html#sklear... | 27,193 |
https://github.com/scikit-learn/scikit-learn/issues/27193 | [
"Documentation"
] | Better documentation for `RFECV`
There is almost no description in the documentation of how `RFECV` actually works. The [user guide](https://scikit-learn.org/stable/modules/feature_selection.html#rfe) simply says
> [RFECV](https://scikit-learn.org/stable/modules/generated/sklearn.feature_selection.RFECV.html#sklear... | 27,193 |
https://github.com/scikit-learn/scikit-learn/issues/27193 | [
"Documentation"
] | Better documentation for `RFECV`
There is almost no description in the documentation of how `RFECV` actually works. The [user guide](https://scikit-learn.org/stable/modules/feature_selection.html#rfe) simply says
> [RFECV](https://scikit-learn.org/stable/modules/generated/sklearn.feature_selection.RFECV.html#sklear... | 27,193 |
https://github.com/scikit-learn/scikit-learn/issues/27193 | [
"Documentation"
] | Better documentation for `RFECV`
There is almost no description in the documentation of how `RFECV` actually works. The [user guide](https://scikit-learn.org/stable/modules/feature_selection.html#rfe) simply says
> [RFECV](https://scikit-learn.org/stable/modules/generated/sklearn.feature_selection.RFECV.html#sklear... | 27,193 |
https://github.com/scikit-learn/scikit-learn/issues/27192 | [
"New Feature",
"Needs Decision"
] | Update the Ledoit-Wolf covariance shrinkage methodology to include modern methods
### Describe the workflow you want to enable
I've been working on implementing partial correlation with basis shrinkage in Python. in particular, I've been porting R code to Python.
The relevant partial correlation publications a... | 27,192 |
https://github.com/scikit-learn/scikit-learn/issues/27192 | [
"New Feature",
"Needs Decision"
] | Update the Ledoit-Wolf covariance shrinkage methodology to include modern methods
### Describe the workflow you want to enable
I've been working on implementing partial correlation with basis shrinkage in Python. in particular, I've been porting R code to Python.
The relevant partial correlation publications a... | 27,192 |
https://github.com/scikit-learn/scikit-learn/issues/27192 | [
"New Feature",
"Needs Decision"
] | Update the Ledoit-Wolf covariance shrinkage methodology to include modern methods
### Describe the workflow you want to enable
I've been working on implementing partial correlation with basis shrinkage in Python. in particular, I've been porting R code to Python.
The relevant partial correlation publications a... | 27,192 |
https://github.com/scikit-learn/scikit-learn/issues/27192 | [
"New Feature",
"Needs Decision"
] | Update the Ledoit-Wolf covariance shrinkage methodology to include modern methods
### Describe the workflow you want to enable
I've been working on implementing partial correlation with basis shrinkage in Python. in particular, I've been porting R code to Python.
The relevant partial correlation publications a... | 27,192 |
https://github.com/scikit-learn/scikit-learn/issues/27192 | [
"New Feature",
"Needs Decision"
] | Update the Ledoit-Wolf covariance shrinkage methodology to include modern methods
### Describe the workflow you want to enable
I've been working on implementing partial correlation with basis shrinkage in Python. in particular, I've been porting R code to Python.
The relevant partial correlation publications a... | 27,192 |
https://github.com/scikit-learn/scikit-learn/issues/27192 | [
"New Feature",
"Needs Decision"
] | Update the Ledoit-Wolf covariance shrinkage methodology to include modern methods
### Describe the workflow you want to enable
I've been working on implementing partial correlation with basis shrinkage in Python. in particular, I've been porting R code to Python.
The relevant partial correlation publications a... | 27,192 |
https://github.com/scikit-learn/scikit-learn/issues/27192 | [
"New Feature",
"Needs Decision"
] | Update the Ledoit-Wolf covariance shrinkage methodology to include modern methods
### Describe the workflow you want to enable
I've been working on implementing partial correlation with basis shrinkage in Python. in particular, I've been porting R code to Python.
The relevant partial correlation publications a... | 27,192 |
https://github.com/scikit-learn/scikit-learn/issues/27189 | [
"Bug"
] | F1 score not calculated properly
### Describe the bug
According to the [definition](https://en.wikipedia.org/wiki/F-score) of the F1 score for two classes, it can be calculated as
$$
2 \frac{2tp}{2tp + fp + fn}
$$
or
$$
2 \frac{precision * recall}{precision + recall}
$$
From what I can see, scikit... | 27,189 |
https://github.com/scikit-learn/scikit-learn/issues/27189 | [
"Bug"
] | F1 score not calculated properly
### Describe the bug
According to the [definition](https://en.wikipedia.org/wiki/F-score) of the F1 score for two classes, it can be calculated as
$$
2 \frac{2tp}{2tp + fp + fn}
$$
or
$$
2 \frac{precision * recall}{precision + recall}
$$
From what I can see, scikit... | 27,189 |
https://github.com/scikit-learn/scikit-learn/issues/27189 | [
"Bug"
] | F1 score not calculated properly
### Describe the bug
According to the [definition](https://en.wikipedia.org/wiki/F-score) of the F1 score for two classes, it can be calculated as
$$
2 \frac{2tp}{2tp + fp + fn}
$$
or
$$
2 \frac{precision * recall}{precision + recall}
$$
From what I can see, scikit... | 27,189 |
https://github.com/scikit-learn/scikit-learn/issues/27189 | [
"Bug"
] | F1 score not calculated properly
### Describe the bug
According to the [definition](https://en.wikipedia.org/wiki/F-score) of the F1 score for two classes, it can be calculated as
$$
2 \frac{2tp}{2tp + fp + fn}
$$
or
$$
2 \frac{precision * recall}{precision + recall}
$$
From what I can see, scikit... | 27,189 |
https://github.com/scikit-learn/scikit-learn/issues/27189 | [
"Bug"
] | F1 score not calculated properly
### Describe the bug
According to the [definition](https://en.wikipedia.org/wiki/F-score) of the F1 score for two classes, it can be calculated as
$$
2 \frac{2tp}{2tp + fp + fn}
$$
or
$$
2 \frac{precision * recall}{precision + recall}
$$
From what I can see, scikit... | 27,189 |
https://github.com/scikit-learn/scikit-learn/issues/27189 | [
"Bug"
] | F1 score not calculated properly
### Describe the bug
According to the [definition](https://en.wikipedia.org/wiki/F-score) of the F1 score for two classes, it can be calculated as
$$
2 \frac{2tp}{2tp + fp + fn}
$$
or
$$
2 \frac{precision * recall}{precision + recall}
$$
From what I can see, scikit... | 27,189 |
https://github.com/scikit-learn/scikit-learn/issues/27189 | [
"Bug"
] | F1 score not calculated properly
### Describe the bug
According to the [definition](https://en.wikipedia.org/wiki/F-score) of the F1 score for two classes, it can be calculated as
$$
2 \frac{2tp}{2tp + fp + fn}
$$
or
$$
2 \frac{precision * recall}{precision + recall}
$$
From what I can see, scikit... | 27,189 |
https://github.com/scikit-learn/scikit-learn/issues/27189 | [
"Bug"
] | F1 score not calculated properly
### Describe the bug
According to the [definition](https://en.wikipedia.org/wiki/F-score) of the F1 score for two classes, it can be calculated as
$$
2 \frac{2tp}{2tp + fp + fn}
$$
or
$$
2 \frac{precision * recall}{precision + recall}
$$
From what I can see, scikit... | 27,189 |
https://github.com/scikit-learn/scikit-learn/issues/27189 | [
"Bug"
] | F1 score not calculated properly
### Describe the bug
According to the [definition](https://en.wikipedia.org/wiki/F-score) of the F1 score for two classes, it can be calculated as
$$
2 \frac{2tp}{2tp + fp + fn}
$$
or
$$
2 \frac{precision * recall}{precision + recall}
$$
From what I can see, scikit... | 27,189 |
https://github.com/scikit-learn/scikit-learn/issues/27189 | [
"Bug"
] | F1 score not calculated properly
### Describe the bug
According to the [definition](https://en.wikipedia.org/wiki/F-score) of the F1 score for two classes, it can be calculated as
$$
2 \frac{2tp}{2tp + fp + fn}
$$
or
$$
2 \frac{precision * recall}{precision + recall}
$$
From what I can see, scikit... | 27,189 |
https://github.com/scikit-learn/scikit-learn/issues/27189 | [
"Bug"
] | F1 score not calculated properly
### Describe the bug
According to the [definition](https://en.wikipedia.org/wiki/F-score) of the F1 score for two classes, it can be calculated as
$$
2 \frac{2tp}{2tp + fp + fn}
$$
or
$$
2 \frac{precision * recall}{precision + recall}
$$
From what I can see, scikit... | 27,189 |
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 |
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