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/30400 | [
"good first issue"
] | Finding indexes with `np.where(condition)` or `np.asarray(condition).nonzero()`
Throughout the repo, we use `np.where(condition)` for getting indexes, for instance in [SelectorMixin.get_support()](https://github.com/scikit-learn/scikit-learn/blob/fba028b07ed2b4e52dd3719dad0d990837bde28c/sklearn/feature_selection/_base... | 30,400 |
https://github.com/scikit-learn/scikit-learn/issues/30400 | [
"good first issue"
] | Finding indexes with `np.where(condition)` or `np.asarray(condition).nonzero()`
Throughout the repo, we use `np.where(condition)` for getting indexes, for instance in [SelectorMixin.get_support()](https://github.com/scikit-learn/scikit-learn/blob/fba028b07ed2b4e52dd3719dad0d990837bde28c/sklearn/feature_selection/_base... | 30,400 |
https://github.com/scikit-learn/scikit-learn/issues/30400 | [
"good first issue"
] | Finding indexes with `np.where(condition)` or `np.asarray(condition).nonzero()`
Throughout the repo, we use `np.where(condition)` for getting indexes, for instance in [SelectorMixin.get_support()](https://github.com/scikit-learn/scikit-learn/blob/fba028b07ed2b4e52dd3719dad0d990837bde28c/sklearn/feature_selection/_base... | 30,400 |
https://github.com/scikit-learn/scikit-learn/issues/30400 | [
"good first issue"
] | Finding indexes with `np.where(condition)` or `np.asarray(condition).nonzero()`
Throughout the repo, we use `np.where(condition)` for getting indexes, for instance in [SelectorMixin.get_support()](https://github.com/scikit-learn/scikit-learn/blob/fba028b07ed2b4e52dd3719dad0d990837bde28c/sklearn/feature_selection/_base... | 30,400 |
https://github.com/scikit-learn/scikit-learn/issues/30400 | [
"good first issue"
] | Finding indexes with `np.where(condition)` or `np.asarray(condition).nonzero()`
Throughout the repo, we use `np.where(condition)` for getting indexes, for instance in [SelectorMixin.get_support()](https://github.com/scikit-learn/scikit-learn/blob/fba028b07ed2b4e52dd3719dad0d990837bde28c/sklearn/feature_selection/_base... | 30,400 |
https://github.com/scikit-learn/scikit-learn/issues/30400 | [
"good first issue"
] | Finding indexes with `np.where(condition)` or `np.asarray(condition).nonzero()`
Throughout the repo, we use `np.where(condition)` for getting indexes, for instance in [SelectorMixin.get_support()](https://github.com/scikit-learn/scikit-learn/blob/fba028b07ed2b4e52dd3719dad0d990837bde28c/sklearn/feature_selection/_base... | 30,400 |
https://github.com/scikit-learn/scikit-learn/issues/30400 | [
"good first issue"
] | Finding indexes with `np.where(condition)` or `np.asarray(condition).nonzero()`
Throughout the repo, we use `np.where(condition)` for getting indexes, for instance in [SelectorMixin.get_support()](https://github.com/scikit-learn/scikit-learn/blob/fba028b07ed2b4e52dd3719dad0d990837bde28c/sklearn/feature_selection/_base... | 30,400 |
https://github.com/scikit-learn/scikit-learn/issues/30398 | [
"Documentation",
"Needs Decision - Include Feature"
] | New example about how to implement the SuperLearner in Python
### Describe the issue linked to the documentation
The SuperLearner is a stacking strategy that is very used in fields like Statistics (for instance in causal inference, survival analysis etc) to obtain a good machine learning model fitted to your data wit... | 30,398 |
https://github.com/scikit-learn/scikit-learn/issues/30398 | [
"Documentation",
"Needs Decision - Include Feature"
] | New example about how to implement the SuperLearner in Python
### Describe the issue linked to the documentation
The SuperLearner is a stacking strategy that is very used in fields like Statistics (for instance in causal inference, survival analysis etc) to obtain a good machine learning model fitted to your data wit... | 30,398 |
https://github.com/scikit-learn/scikit-learn/issues/30398 | [
"Documentation",
"Needs Decision - Include Feature"
] | New example about how to implement the SuperLearner in Python
### Describe the issue linked to the documentation
The SuperLearner is a stacking strategy that is very used in fields like Statistics (for instance in causal inference, survival analysis etc) to obtain a good machine learning model fitted to your data wit... | 30,398 |
https://github.com/scikit-learn/scikit-learn/issues/30398 | [
"Documentation",
"Needs Decision - Include Feature"
] | New example about how to implement the SuperLearner in Python
### Describe the issue linked to the documentation
The SuperLearner is a stacking strategy that is very used in fields like Statistics (for instance in causal inference, survival analysis etc) to obtain a good machine learning model fitted to your data wit... | 30,398 |
https://github.com/scikit-learn/scikit-learn/issues/30398 | [
"Documentation",
"Needs Decision - Include Feature"
] | New example about how to implement the SuperLearner in Python
### Describe the issue linked to the documentation
The SuperLearner is a stacking strategy that is very used in fields like Statistics (for instance in causal inference, survival analysis etc) to obtain a good machine learning model fitted to your data wit... | 30,398 |
https://github.com/scikit-learn/scikit-learn/issues/30396 | [
"Enhancement"
] | ENH Allow disabling refitting of cross-validation estimators
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/30233
<div type='discussions-op-text'>
<sup>Originally posted by **AhmedThahir** November 7, 2024</sup>
Feature request: Allow disable refitting of cross-validation estimators ... | 30,396 |
https://github.com/scikit-learn/scikit-learn/issues/30396 | [
"Enhancement"
] | ENH Allow disabling refitting of cross-validation estimators
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/30233
<div type='discussions-op-text'>
<sup>Originally posted by **AhmedThahir** November 7, 2024</sup>
Feature request: Allow disable refitting of cross-validation estimators ... | 30,396 |
https://github.com/scikit-learn/scikit-learn/issues/30396 | [
"Enhancement"
] | ENH Allow disabling refitting of cross-validation estimators
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/30233
<div type='discussions-op-text'>
<sup>Originally posted by **AhmedThahir** November 7, 2024</sup>
Feature request: Allow disable refitting of cross-validation estimators ... | 30,396 |
https://github.com/scikit-learn/scikit-learn/issues/30396 | [
"Enhancement"
] | ENH Allow disabling refitting of cross-validation estimators
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/30233
<div type='discussions-op-text'>
<sup>Originally posted by **AhmedThahir** November 7, 2024</sup>
Feature request: Allow disable refitting of cross-validation estimators ... | 30,396 |
https://github.com/scikit-learn/scikit-learn/issues/30396 | [
"Enhancement"
] | ENH Allow disabling refitting of cross-validation estimators
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/30233
<div type='discussions-op-text'>
<sup>Originally posted by **AhmedThahir** November 7, 2024</sup>
Feature request: Allow disable refitting of cross-validation estimators ... | 30,396 |
https://github.com/scikit-learn/scikit-learn/issues/30396 | [
"Enhancement"
] | ENH Allow disabling refitting of cross-validation estimators
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/30233
<div type='discussions-op-text'>
<sup>Originally posted by **AhmedThahir** November 7, 2024</sup>
Feature request: Allow disable refitting of cross-validation estimators ... | 30,396 |
https://github.com/scikit-learn/scikit-learn/issues/30396 | [
"Enhancement"
] | ENH Allow disabling refitting of cross-validation estimators
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/30233
<div type='discussions-op-text'>
<sup>Originally posted by **AhmedThahir** November 7, 2024</sup>
Feature request: Allow disable refitting of cross-validation estimators ... | 30,396 |
https://github.com/scikit-learn/scikit-learn/issues/30396 | [
"Enhancement"
] | ENH Allow disabling refitting of cross-validation estimators
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/30233
<div type='discussions-op-text'>
<sup>Originally posted by **AhmedThahir** November 7, 2024</sup>
Feature request: Allow disable refitting of cross-validation estimators ... | 30,396 |
https://github.com/scikit-learn/scikit-learn/issues/30396 | [
"Enhancement"
] | ENH Allow disabling refitting of cross-validation estimators
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/30233
<div type='discussions-op-text'>
<sup>Originally posted by **AhmedThahir** November 7, 2024</sup>
Feature request: Allow disable refitting of cross-validation estimators ... | 30,396 |
https://github.com/scikit-learn/scikit-learn/issues/30396 | [
"Enhancement"
] | ENH Allow disabling refitting of cross-validation estimators
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/30233
<div type='discussions-op-text'>
<sup>Originally posted by **AhmedThahir** November 7, 2024</sup>
Feature request: Allow disable refitting of cross-validation estimators ... | 30,396 |
https://github.com/scikit-learn/scikit-learn/issues/30396 | [
"Enhancement"
] | ENH Allow disabling refitting of cross-validation estimators
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/30233
<div type='discussions-op-text'>
<sup>Originally posted by **AhmedThahir** November 7, 2024</sup>
Feature request: Allow disable refitting of cross-validation estimators ... | 30,396 |
https://github.com/scikit-learn/scikit-learn/issues/30396 | [
"Enhancement"
] | ENH Allow disabling refitting of cross-validation estimators
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/30233
<div type='discussions-op-text'>
<sup>Originally posted by **AhmedThahir** November 7, 2024</sup>
Feature request: Allow disable refitting of cross-validation estimators ... | 30,396 |
https://github.com/scikit-learn/scikit-learn/issues/30394 | [
"New Feature",
"Needs Decision - Include Feature"
] | Is there any interest to provide SymmetricNMF
### Describe the workflow you want to enable
Hi! I have a [prototype implementation of Symmetric NMF](https://github.com/kushalkolar/symmetric-nmf) that I [ported from matlab](https://github.com/dakuang/symnmf). There are 2 main papers on it, the oldest one from 2012 has ... | 30,394 |
https://github.com/scikit-learn/scikit-learn/issues/30394 | [
"New Feature",
"Needs Decision - Include Feature"
] | Is there any interest to provide SymmetricNMF
### Describe the workflow you want to enable
Hi! I have a [prototype implementation of Symmetric NMF](https://github.com/kushalkolar/symmetric-nmf) that I [ported from matlab](https://github.com/dakuang/symnmf). There are 2 main papers on it, the oldest one from 2012 has ... | 30,394 |
https://github.com/scikit-learn/scikit-learn/issues/30391 | [
"Build / CI"
] | CI Use CIBW_ENABLE rather than CIBW_FREE_THREADED_SUPPORT in wheels builder
It seems like this is about CIBW_FREETHREADED_SUPPORT and CIBW_PRERELEASE_PYTHONS. There may be some complications for CIBW_PRERELEASE_PYTHONS which we are using for Windows minimal docker image.
> Added a new CIBW_ENABLE/enable feature tha... | 30,391 |
https://github.com/scikit-learn/scikit-learn/issues/30390 | [
"Build / CI"
] | CI Replace pytorch conda channel in CI lock-files
After a quick look, it seems like the only place we are using the pytorch channel is for the CUDA CI, cc @betatim.
The easiest thing to try would be to use the conda-forge pytorch-gpu package?
See https://github.com/pytorch/pytorch/issues/138506 for more details.... | 30,390 |
https://github.com/scikit-learn/scikit-learn/issues/30389 | [
"Easy",
"Documentation",
"help wanted"
] | Make `_check_n_features` and `_check_feature_names` public
Since we are moving, `_check_n_features` and `_check_feature_names` into a new module, I'm wondering if we should make them public as well.
I can imagine some people that don't want to use `validate_data` but still want to set `self.n_features_in_` or `self... | 30,389 |
https://github.com/scikit-learn/scikit-learn/issues/30389 | [
"Easy",
"Documentation",
"help wanted"
] | Make `_check_n_features` and `_check_feature_names` public
Since we are moving, `_check_n_features` and `_check_feature_names` into a new module, I'm wondering if we should make them public as well.
I can imagine some people that don't want to use `validate_data` but still want to set `self.n_features_in_` or `self... | 30,389 |
https://github.com/scikit-learn/scikit-learn/issues/30389 | [
"Easy",
"Documentation",
"help wanted"
] | Make `_check_n_features` and `_check_feature_names` public
Since we are moving, `_check_n_features` and `_check_feature_names` into a new module, I'm wondering if we should make them public as well.
I can imagine some people that don't want to use `validate_data` but still want to set `self.n_features_in_` or `self... | 30,389 |
https://github.com/scikit-learn/scikit-learn/issues/30389 | [
"Easy",
"Documentation",
"help wanted"
] | Make `_check_n_features` and `_check_feature_names` public
Since we are moving, `_check_n_features` and `_check_feature_names` into a new module, I'm wondering if we should make them public as well.
I can imagine some people that don't want to use `validate_data` but still want to set `self.n_features_in_` or `self... | 30,389 |
https://github.com/scikit-learn/scikit-learn/issues/30389 | [
"Easy",
"Documentation",
"help wanted"
] | Make `_check_n_features` and `_check_feature_names` public
Since we are moving, `_check_n_features` and `_check_feature_names` into a new module, I'm wondering if we should make them public as well.
I can imagine some people that don't want to use `validate_data` but still want to set `self.n_features_in_` or `self... | 30,389 |
https://github.com/scikit-learn/scikit-learn/issues/30389 | [
"Easy",
"Documentation",
"help wanted"
] | Make `_check_n_features` and `_check_feature_names` public
Since we are moving, `_check_n_features` and `_check_feature_names` into a new module, I'm wondering if we should make them public as well.
I can imagine some people that don't want to use `validate_data` but still want to set `self.n_features_in_` or `self... | 30,389 |
https://github.com/scikit-learn/scikit-learn/issues/30389 | [
"Easy",
"Documentation",
"help wanted"
] | Make `_check_n_features` and `_check_feature_names` public
Since we are moving, `_check_n_features` and `_check_feature_names` into a new module, I'm wondering if we should make them public as well.
I can imagine some people that don't want to use `validate_data` but still want to set `self.n_features_in_` or `self... | 30,389 |
https://github.com/scikit-learn/scikit-learn/issues/30389 | [
"Easy",
"Documentation",
"help wanted"
] | Make `_check_n_features` and `_check_feature_names` public
Since we are moving, `_check_n_features` and `_check_feature_names` into a new module, I'm wondering if we should make them public as well.
I can imagine some people that don't want to use `validate_data` but still want to set `self.n_features_in_` or `self... | 30,389 |
https://github.com/scikit-learn/scikit-learn/issues/30389 | [
"Easy",
"Documentation",
"help wanted"
] | Make `_check_n_features` and `_check_feature_names` public
Since we are moving, `_check_n_features` and `_check_feature_names` into a new module, I'm wondering if we should make them public as well.
I can imagine some people that don't want to use `validate_data` but still want to set `self.n_features_in_` or `self... | 30,389 |
https://github.com/scikit-learn/scikit-learn/issues/30389 | [
"Easy",
"Documentation",
"help wanted"
] | Make `_check_n_features` and `_check_feature_names` public
Since we are moving, `_check_n_features` and `_check_feature_names` into a new module, I'm wondering if we should make them public as well.
I can imagine some people that don't want to use `validate_data` but still want to set `self.n_features_in_` or `self... | 30,389 |
https://github.com/scikit-learn/scikit-learn/issues/30389 | [
"Easy",
"Documentation",
"help wanted"
] | Make `_check_n_features` and `_check_feature_names` public
Since we are moving, `_check_n_features` and `_check_feature_names` into a new module, I'm wondering if we should make them public as well.
I can imagine some people that don't want to use `validate_data` but still want to set `self.n_features_in_` or `self... | 30,389 |
https://github.com/scikit-learn/scikit-learn/issues/30389 | [
"Easy",
"Documentation",
"help wanted"
] | Make `_check_n_features` and `_check_feature_names` public
Since we are moving, `_check_n_features` and `_check_feature_names` into a new module, I'm wondering if we should make them public as well.
I can imagine some people that don't want to use `validate_data` but still want to set `self.n_features_in_` or `self... | 30,389 |
https://github.com/scikit-learn/scikit-learn/issues/30389 | [
"Easy",
"Documentation",
"help wanted"
] | Make `_check_n_features` and `_check_feature_names` public
Since we are moving, `_check_n_features` and `_check_feature_names` into a new module, I'm wondering if we should make them public as well.
I can imagine some people that don't want to use `validate_data` but still want to set `self.n_features_in_` or `self... | 30,389 |
https://github.com/scikit-learn/scikit-learn/issues/30389 | [
"Easy",
"Documentation",
"help wanted"
] | Make `_check_n_features` and `_check_feature_names` public
Since we are moving, `_check_n_features` and `_check_feature_names` into a new module, I'm wondering if we should make them public as well.
I can imagine some people that don't want to use `validate_data` but still want to set `self.n_features_in_` or `self... | 30,389 |
https://github.com/scikit-learn/scikit-learn/issues/30389 | [
"Easy",
"Documentation",
"help wanted"
] | Make `_check_n_features` and `_check_feature_names` public
Since we are moving, `_check_n_features` and `_check_feature_names` into a new module, I'm wondering if we should make them public as well.
I can imagine some people that don't want to use `validate_data` but still want to set `self.n_features_in_` or `self... | 30,389 |
https://github.com/scikit-learn/scikit-learn/issues/30389 | [
"Easy",
"Documentation",
"help wanted"
] | Make `_check_n_features` and `_check_feature_names` public
Since we are moving, `_check_n_features` and `_check_feature_names` into a new module, I'm wondering if we should make them public as well.
I can imagine some people that don't want to use `validate_data` but still want to set `self.n_features_in_` or `self... | 30,389 |
https://github.com/scikit-learn/scikit-learn/issues/30382 | [
"Bug",
"Numerical Stability"
] | Gaussian Mixture: Diagonal covariance vectors might contain unreasonably negative values when the input datatype is np.float32
### Describe the bug
The Gaussian Mixture implementation shows numerical instabilities on single-precision floating point input numbers, that even large values of the regularization paramet... | 30,382 |
https://github.com/scikit-learn/scikit-learn/issues/30382 | [
"Bug",
"Numerical Stability"
] | Gaussian Mixture: Diagonal covariance vectors might contain unreasonably negative values when the input datatype is np.float32
### Describe the bug
The Gaussian Mixture implementation shows numerical instabilities on single-precision floating point input numbers, that even large values of the regularization paramet... | 30,382 |
https://github.com/scikit-learn/scikit-learn/issues/30382 | [
"Bug",
"Numerical Stability"
] | Gaussian Mixture: Diagonal covariance vectors might contain unreasonably negative values when the input datatype is np.float32
### Describe the bug
The Gaussian Mixture implementation shows numerical instabilities on single-precision floating point input numbers, that even large values of the regularization paramet... | 30,382 |
https://github.com/scikit-learn/scikit-learn/issues/30382 | [
"Bug",
"Numerical Stability"
] | Gaussian Mixture: Diagonal covariance vectors might contain unreasonably negative values when the input datatype is np.float32
### Describe the bug
The Gaussian Mixture implementation shows numerical instabilities on single-precision floating point input numbers, that even large values of the regularization paramet... | 30,382 |
https://github.com/scikit-learn/scikit-learn/issues/30382 | [
"Bug",
"Numerical Stability"
] | Gaussian Mixture: Diagonal covariance vectors might contain unreasonably negative values when the input datatype is np.float32
### Describe the bug
The Gaussian Mixture implementation shows numerical instabilities on single-precision floating point input numbers, that even large values of the regularization paramet... | 30,382 |
https://github.com/scikit-learn/scikit-learn/issues/30382 | [
"Bug",
"Numerical Stability"
] | Gaussian Mixture: Diagonal covariance vectors might contain unreasonably negative values when the input datatype is np.float32
### Describe the bug
The Gaussian Mixture implementation shows numerical instabilities on single-precision floating point input numbers, that even large values of the regularization paramet... | 30,382 |
https://github.com/scikit-learn/scikit-learn/issues/30382 | [
"Bug",
"Numerical Stability"
] | Gaussian Mixture: Diagonal covariance vectors might contain unreasonably negative values when the input datatype is np.float32
### Describe the bug
The Gaussian Mixture implementation shows numerical instabilities on single-precision floating point input numbers, that even large values of the regularization paramet... | 30,382 |
https://github.com/scikit-learn/scikit-learn/issues/30382 | [
"Bug",
"Numerical Stability"
] | Gaussian Mixture: Diagonal covariance vectors might contain unreasonably negative values when the input datatype is np.float32
### Describe the bug
The Gaussian Mixture implementation shows numerical instabilities on single-precision floating point input numbers, that even large values of the regularization paramet... | 30,382 |
https://github.com/scikit-learn/scikit-learn/issues/30382 | [
"Bug",
"Numerical Stability"
] | Gaussian Mixture: Diagonal covariance vectors might contain unreasonably negative values when the input datatype is np.float32
### Describe the bug
The Gaussian Mixture implementation shows numerical instabilities on single-precision floating point input numbers, that even large values of the regularization paramet... | 30,382 |
https://github.com/scikit-learn/scikit-learn/issues/30382 | [
"Bug",
"Numerical Stability"
] | Gaussian Mixture: Diagonal covariance vectors might contain unreasonably negative values when the input datatype is np.float32
### Describe the bug
The Gaussian Mixture implementation shows numerical instabilities on single-precision floating point input numbers, that even large values of the regularization paramet... | 30,382 |
https://github.com/scikit-learn/scikit-learn/issues/30382 | [
"Bug",
"Numerical Stability"
] | Gaussian Mixture: Diagonal covariance vectors might contain unreasonably negative values when the input datatype is np.float32
### Describe the bug
The Gaussian Mixture implementation shows numerical instabilities on single-precision floating point input numbers, that even large values of the regularization paramet... | 30,382 |
https://github.com/scikit-learn/scikit-learn/issues/30382 | [
"Bug",
"Numerical Stability"
] | Gaussian Mixture: Diagonal covariance vectors might contain unreasonably negative values when the input datatype is np.float32
### Describe the bug
The Gaussian Mixture implementation shows numerical instabilities on single-precision floating point input numbers, that even large values of the regularization paramet... | 30,382 |
https://github.com/scikit-learn/scikit-learn/issues/30382 | [
"Bug",
"Numerical Stability"
] | Gaussian Mixture: Diagonal covariance vectors might contain unreasonably negative values when the input datatype is np.float32
### Describe the bug
The Gaussian Mixture implementation shows numerical instabilities on single-precision floating point input numbers, that even large values of the regularization paramet... | 30,382 |
https://github.com/scikit-learn/scikit-learn/issues/30382 | [
"Bug",
"Numerical Stability"
] | Gaussian Mixture: Diagonal covariance vectors might contain unreasonably negative values when the input datatype is np.float32
### Describe the bug
The Gaussian Mixture implementation shows numerical instabilities on single-precision floating point input numbers, that even large values of the regularization paramet... | 30,382 |
https://github.com/scikit-learn/scikit-learn/issues/30382 | [
"Bug",
"Numerical Stability"
] | Gaussian Mixture: Diagonal covariance vectors might contain unreasonably negative values when the input datatype is np.float32
### Describe the bug
The Gaussian Mixture implementation shows numerical instabilities on single-precision floating point input numbers, that even large values of the regularization paramet... | 30,382 |
https://github.com/scikit-learn/scikit-learn/issues/30382 | [
"Bug",
"Numerical Stability"
] | Gaussian Mixture: Diagonal covariance vectors might contain unreasonably negative values when the input datatype is np.float32
### Describe the bug
The Gaussian Mixture implementation shows numerical instabilities on single-precision floating point input numbers, that even large values of the regularization paramet... | 30,382 |
https://github.com/scikit-learn/scikit-learn/issues/30382 | [
"Bug",
"Numerical Stability"
] | Gaussian Mixture: Diagonal covariance vectors might contain unreasonably negative values when the input datatype is np.float32
### Describe the bug
The Gaussian Mixture implementation shows numerical instabilities on single-precision floating point input numbers, that even large values of the regularization paramet... | 30,382 |
https://github.com/scikit-learn/scikit-learn/issues/30382 | [
"Bug",
"Numerical Stability"
] | Gaussian Mixture: Diagonal covariance vectors might contain unreasonably negative values when the input datatype is np.float32
### Describe the bug
The Gaussian Mixture implementation shows numerical instabilities on single-precision floating point input numbers, that even large values of the regularization paramet... | 30,382 |
https://github.com/scikit-learn/scikit-learn/issues/30382 | [
"Bug",
"Numerical Stability"
] | Gaussian Mixture: Diagonal covariance vectors might contain unreasonably negative values when the input datatype is np.float32
### Describe the bug
The Gaussian Mixture implementation shows numerical instabilities on single-precision floating point input numbers, that even large values of the regularization paramet... | 30,382 |
https://github.com/scikit-learn/scikit-learn/issues/30382 | [
"Bug",
"Numerical Stability"
] | Gaussian Mixture: Diagonal covariance vectors might contain unreasonably negative values when the input datatype is np.float32
### Describe the bug
The Gaussian Mixture implementation shows numerical instabilities on single-precision floating point input numbers, that even large values of the regularization paramet... | 30,382 |
https://github.com/scikit-learn/scikit-learn/issues/30371 | [
"Bug",
"Needs Triage"
] | Meson Build system error
### Describe the bug
I am [building from source](https://scikit-learn.org/stable/developers/advanced_installation.html#building-from-source) with Miniforge3. This previously worked in `1.6.dev0`, but when I tried this time I got a Segmentation fault
### Steps/Code to Reproduce
```
$ conda ... | 30,371 |
https://github.com/scikit-learn/scikit-learn/issues/30371 | [
"Bug",
"Needs Triage"
] | Meson Build system error
### Describe the bug
I am [building from source](https://scikit-learn.org/stable/developers/advanced_installation.html#building-from-source) with Miniforge3. This previously worked in `1.6.dev0`, but when I tried this time I got a Segmentation fault
### Steps/Code to Reproduce
```
$ conda ... | 30,371 |
https://github.com/scikit-learn/scikit-learn/issues/30364 | [
"New Feature"
] | Expose `verbose_feature_names_out` in `make_union`
### Describe the workflow you want to enable
```python
from sklearn.pipeline import make_union
feature_union = make_union(..., verbose_feature_names_out=False)
```
### Describe your proposed solution
Add a keyword arg like in `make_column_transformer`
... | 30,364 |
https://github.com/scikit-learn/scikit-learn/issues/30364 | [
"New Feature"
] | Expose `verbose_feature_names_out` in `make_union`
### Describe the workflow you want to enable
```python
from sklearn.pipeline import make_union
feature_union = make_union(..., verbose_feature_names_out=False)
```
### Describe your proposed solution
Add a keyword arg like in `make_column_transformer`
... | 30,364 |
https://github.com/scikit-learn/scikit-learn/issues/30364 | [
"New Feature"
] | Expose `verbose_feature_names_out` in `make_union`
### Describe the workflow you want to enable
```python
from sklearn.pipeline import make_union
feature_union = make_union(..., verbose_feature_names_out=False)
```
### Describe your proposed solution
Add a keyword arg like in `make_column_transformer`
... | 30,364 |
https://github.com/scikit-learn/scikit-learn/issues/30357 | [
"Bug",
"frontend"
] | HTML display rendering poorly in vscode "Dark High Contrast" color theme
### Describe the bug
When I use vscode, I use the "Dark High Contrast" theme, as my eyes are tired. In this mode, some of the estimator names are not visible in the HTML display
### Steps/Code to Reproduce
Execute the following code in a vscod... | 30,357 |
https://github.com/scikit-learn/scikit-learn/issues/30357 | [
"Bug",
"frontend"
] | HTML display rendering poorly in vscode "Dark High Contrast" color theme
### Describe the bug
When I use vscode, I use the "Dark High Contrast" theme, as my eyes are tired. In this mode, some of the estimator names are not visible in the HTML display
### Steps/Code to Reproduce
Execute the following code in a vscod... | 30,357 |
https://github.com/scikit-learn/scikit-learn/issues/30357 | [
"Bug",
"frontend"
] | HTML display rendering poorly in vscode "Dark High Contrast" color theme
### Describe the bug
When I use vscode, I use the "Dark High Contrast" theme, as my eyes are tired. In this mode, some of the estimator names are not visible in the HTML display
### Steps/Code to Reproduce
Execute the following code in a vscod... | 30,357 |
https://github.com/scikit-learn/scikit-learn/issues/30357 | [
"Bug",
"frontend"
] | HTML display rendering poorly in vscode "Dark High Contrast" color theme
### Describe the bug
When I use vscode, I use the "Dark High Contrast" theme, as my eyes are tired. In this mode, some of the estimator names are not visible in the HTML display
### Steps/Code to Reproduce
Execute the following code in a vscod... | 30,357 |
https://github.com/scikit-learn/scikit-learn/issues/30357 | [
"Bug",
"frontend"
] | HTML display rendering poorly in vscode "Dark High Contrast" color theme
### Describe the bug
When I use vscode, I use the "Dark High Contrast" theme, as my eyes are tired. In this mode, some of the estimator names are not visible in the HTML display
### Steps/Code to Reproduce
Execute the following code in a vscod... | 30,357 |
https://github.com/scikit-learn/scikit-learn/issues/30357 | [
"Bug",
"frontend"
] | HTML display rendering poorly in vscode "Dark High Contrast" color theme
### Describe the bug
When I use vscode, I use the "Dark High Contrast" theme, as my eyes are tired. In this mode, some of the estimator names are not visible in the HTML display
### Steps/Code to Reproduce
Execute the following code in a vscod... | 30,357 |
https://github.com/scikit-learn/scikit-learn/issues/30357 | [
"Bug",
"frontend"
] | HTML display rendering poorly in vscode "Dark High Contrast" color theme
### Describe the bug
When I use vscode, I use the "Dark High Contrast" theme, as my eyes are tired. In this mode, some of the estimator names are not visible in the HTML display
### Steps/Code to Reproduce
Execute the following code in a vscod... | 30,357 |
https://github.com/scikit-learn/scikit-learn/issues/30357 | [
"Bug",
"frontend"
] | HTML display rendering poorly in vscode "Dark High Contrast" color theme
### Describe the bug
When I use vscode, I use the "Dark High Contrast" theme, as my eyes are tired. In this mode, some of the estimator names are not visible in the HTML display
### Steps/Code to Reproduce
Execute the following code in a vscod... | 30,357 |
https://github.com/scikit-learn/scikit-learn/issues/30357 | [
"Bug",
"frontend"
] | HTML display rendering poorly in vscode "Dark High Contrast" color theme
### Describe the bug
When I use vscode, I use the "Dark High Contrast" theme, as my eyes are tired. In this mode, some of the estimator names are not visible in the HTML display
### Steps/Code to Reproduce
Execute the following code in a vscod... | 30,357 |
https://github.com/scikit-learn/scikit-learn/issues/30354 | [
"Documentation"
] | Enhance "Choosing the Right Estimator" Graphic (scikit-learn algorithm cheat sheet)
### Describe the issue linked to the documentation
In its user guide, scikit-learn offers a [Choosing the right estimator](https://scikit-learn.org/stable/machine_learning_map.html) which is an interactive scikit-learn algorithm che... | 30,354 |
https://github.com/scikit-learn/scikit-learn/issues/30354 | [
"Documentation"
] | Enhance "Choosing the Right Estimator" Graphic (scikit-learn algorithm cheat sheet)
### Describe the issue linked to the documentation
In its user guide, scikit-learn offers a [Choosing the right estimator](https://scikit-learn.org/stable/machine_learning_map.html) which is an interactive scikit-learn algorithm che... | 30,354 |
https://github.com/scikit-learn/scikit-learn/issues/30354 | [
"Documentation"
] | Enhance "Choosing the Right Estimator" Graphic (scikit-learn algorithm cheat sheet)
### Describe the issue linked to the documentation
In its user guide, scikit-learn offers a [Choosing the right estimator](https://scikit-learn.org/stable/machine_learning_map.html) which is an interactive scikit-learn algorithm che... | 30,354 |
https://github.com/scikit-learn/scikit-learn/issues/30354 | [
"Documentation"
] | Enhance "Choosing the Right Estimator" Graphic (scikit-learn algorithm cheat sheet)
### Describe the issue linked to the documentation
In its user guide, scikit-learn offers a [Choosing the right estimator](https://scikit-learn.org/stable/machine_learning_map.html) which is an interactive scikit-learn algorithm che... | 30,354 |
https://github.com/scikit-learn/scikit-learn/issues/30353 | [
"Bug",
"Needs Investigation"
] | Hang when fitting `SVC` to a specific dataset
### Describe the bug
I am trying to fit an [`SVC`](https://scikit-learn.org/stable/modules/generated/sklearn.svm.SVC.html) to a specific dataset. The training process gets stuck, never finishing.
scikit-learn uses a fork of LIBSVM [version 3.10.0](https://github.com/... | 30,353 |
https://github.com/scikit-learn/scikit-learn/issues/30353 | [
"Bug",
"Needs Investigation"
] | Hang when fitting `SVC` to a specific dataset
### Describe the bug
I am trying to fit an [`SVC`](https://scikit-learn.org/stable/modules/generated/sklearn.svm.SVC.html) to a specific dataset. The training process gets stuck, never finishing.
scikit-learn uses a fork of LIBSVM [version 3.10.0](https://github.com/... | 30,353 |
https://github.com/scikit-learn/scikit-learn/issues/30353 | [
"Bug",
"Needs Investigation"
] | Hang when fitting `SVC` to a specific dataset
### Describe the bug
I am trying to fit an [`SVC`](https://scikit-learn.org/stable/modules/generated/sklearn.svm.SVC.html) to a specific dataset. The training process gets stuck, never finishing.
scikit-learn uses a fork of LIBSVM [version 3.10.0](https://github.com/... | 30,353 |
https://github.com/scikit-learn/scikit-learn/issues/30353 | [
"Bug",
"Needs Investigation"
] | Hang when fitting `SVC` to a specific dataset
### Describe the bug
I am trying to fit an [`SVC`](https://scikit-learn.org/stable/modules/generated/sklearn.svm.SVC.html) to a specific dataset. The training process gets stuck, never finishing.
scikit-learn uses a fork of LIBSVM [version 3.10.0](https://github.com/... | 30,353 |
https://github.com/scikit-learn/scikit-learn/issues/30352 | [
"Documentation",
"API"
] | Revisit the "chance level" for the different displays
@e-pet commented on different PRs & issues some interesting fact. I take the opportunity to consolidate some of those comments here.
First, we use the term "chance" that is ambiguous depending of the displays. The term "baseline" would probably be better. In add... | 30,352 |
https://github.com/scikit-learn/scikit-learn/issues/30352 | [
"Documentation",
"API"
] | Revisit the "chance level" for the different displays
@e-pet commented on different PRs & issues some interesting fact. I take the opportunity to consolidate some of those comments here.
First, we use the term "chance" that is ambiguous depending of the displays. The term "baseline" would probably be better. In add... | 30,352 |
https://github.com/scikit-learn/scikit-learn/issues/30352 | [
"Documentation",
"API"
] | Revisit the "chance level" for the different displays
@e-pet commented on different PRs & issues some interesting fact. I take the opportunity to consolidate some of those comments here.
First, we use the term "chance" that is ambiguous depending of the displays. The term "baseline" would probably be better. In add... | 30,352 |
https://github.com/scikit-learn/scikit-learn/issues/30352 | [
"Documentation",
"API"
] | Revisit the "chance level" for the different displays
@e-pet commented on different PRs & issues some interesting fact. I take the opportunity to consolidate some of those comments here.
First, we use the term "chance" that is ambiguous depending of the displays. The term "baseline" would probably be better. In add... | 30,352 |
https://github.com/scikit-learn/scikit-learn/issues/30352 | [
"Documentation",
"API"
] | Revisit the "chance level" for the different displays
@e-pet commented on different PRs & issues some interesting fact. I take the opportunity to consolidate some of those comments here.
First, we use the term "chance" that is ambiguous depending of the displays. The term "baseline" would probably be better. In add... | 30,352 |
https://github.com/scikit-learn/scikit-learn/issues/30352 | [
"Documentation",
"API"
] | Revisit the "chance level" for the different displays
@e-pet commented on different PRs & issues some interesting fact. I take the opportunity to consolidate some of those comments here.
First, we use the term "chance" that is ambiguous depending of the displays. The term "baseline" would probably be better. In add... | 30,352 |
https://github.com/scikit-learn/scikit-learn/issues/30352 | [
"Documentation",
"API"
] | Revisit the "chance level" for the different displays
@e-pet commented on different PRs & issues some interesting fact. I take the opportunity to consolidate some of those comments here.
First, we use the term "chance" that is ambiguous depending of the displays. The term "baseline" would probably be better. In add... | 30,352 |
https://github.com/scikit-learn/scikit-learn/issues/30352 | [
"Documentation",
"API"
] | Revisit the "chance level" for the different displays
@e-pet commented on different PRs & issues some interesting fact. I take the opportunity to consolidate some of those comments here.
First, we use the term "chance" that is ambiguous depending of the displays. The term "baseline" would probably be better. In add... | 30,352 |
https://github.com/scikit-learn/scikit-learn/issues/30352 | [
"Documentation",
"API"
] | Revisit the "chance level" for the different displays
@e-pet commented on different PRs & issues some interesting fact. I take the opportunity to consolidate some of those comments here.
First, we use the term "chance" that is ambiguous depending of the displays. The term "baseline" would probably be better. In add... | 30,352 |
https://github.com/scikit-learn/scikit-learn/issues/30352 | [
"Documentation",
"API"
] | Revisit the "chance level" for the different displays
@e-pet commented on different PRs & issues some interesting fact. I take the opportunity to consolidate some of those comments here.
First, we use the term "chance" that is ambiguous depending of the displays. The term "baseline" would probably be better. In add... | 30,352 |
https://github.com/scikit-learn/scikit-learn/issues/30352 | [
"Documentation",
"API"
] | Revisit the "chance level" for the different displays
@e-pet commented on different PRs & issues some interesting fact. I take the opportunity to consolidate some of those comments here.
First, we use the term "chance" that is ambiguous depending of the displays. The term "baseline" would probably be better. In add... | 30,352 |
https://github.com/scikit-learn/scikit-learn/issues/30352 | [
"Documentation",
"API"
] | Revisit the "chance level" for the different displays
@e-pet commented on different PRs & issues some interesting fact. I take the opportunity to consolidate some of those comments here.
First, we use the term "chance" that is ambiguous depending of the displays. The term "baseline" would probably be better. In add... | 30,352 |
https://github.com/scikit-learn/scikit-learn/issues/30339 | [
"Documentation"
] | DOC: clarify the documentation for the loss functions used in GBRT, and Absolute Error in particular.
### Describe the bug
From my understanding, currently there is no way to minimize the MAE (Mean Absolute Error). Quantile regression with quantile=0.5 will optimize for the Median Absolute Error. This would be diff... | 30,339 |
https://github.com/scikit-learn/scikit-learn/issues/30339 | [
"Documentation"
] | DOC: clarify the documentation for the loss functions used in GBRT, and Absolute Error in particular.
### Describe the bug
From my understanding, currently there is no way to minimize the MAE (Mean Absolute Error). Quantile regression with quantile=0.5 will optimize for the Median Absolute Error. This would be diff... | 30,339 |
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