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https://github.com/scikit-learn/scikit-learn/issues/29048 | [
"Enhancement"
] | Make `zero_division` parameter consistent in the different metric
This is an issue to report the step to actually take over the work of @marctorsoc in https://github.com/scikit-learn/scikit-learn/pull/23183 and split the PR into smaller one to facilitate the review process.
The intend is to make the `zero_division` p... | 29,048 | [
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0.046216... |
https://github.com/scikit-learn/scikit-learn/issues/29048 | [
"Enhancement"
] | Make `zero_division` parameter consistent in the different metric
This is an issue to report the step to actually take over the work of @marctorsoc in https://github.com/scikit-learn/scikit-learn/pull/23183 and split the PR into smaller one to facilitate the review process.
The intend is to make the `zero_division` p... | 29,048 | [
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0.046216... |
https://github.com/scikit-learn/scikit-learn/issues/29048 | [
"Enhancement"
] | Make `zero_division` parameter consistent in the different metric
This is an issue to report the step to actually take over the work of @marctorsoc in https://github.com/scikit-learn/scikit-learn/pull/23183 and split the PR into smaller one to facilitate the review process.
The intend is to make the `zero_division` p... | 29,048 | [
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0.046216... |
https://github.com/scikit-learn/scikit-learn/issues/29048 | [
"Enhancement"
] | Make `zero_division` parameter consistent in the different metric
This is an issue to report the step to actually take over the work of @marctorsoc in https://github.com/scikit-learn/scikit-learn/pull/23183 and split the PR into smaller one to facilitate the review process.
The intend is to make the `zero_division` p... | 29,048 | [
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0.046216... |
https://github.com/scikit-learn/scikit-learn/issues/29048 | [
"Enhancement"
] | Make `zero_division` parameter consistent in the different metric
This is an issue to report the step to actually take over the work of @marctorsoc in https://github.com/scikit-learn/scikit-learn/pull/23183 and split the PR into smaller one to facilitate the review process.
The intend is to make the `zero_division` p... | 29,048 | [
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0.046216... |
https://github.com/scikit-learn/scikit-learn/issues/29048 | [
"Enhancement"
] | Make `zero_division` parameter consistent in the different metric
This is an issue to report the step to actually take over the work of @marctorsoc in https://github.com/scikit-learn/scikit-learn/pull/23183 and split the PR into smaller one to facilitate the review process.
The intend is to make the `zero_division` p... | 29,048 | [
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0.046216... |
https://github.com/scikit-learn/scikit-learn/issues/29048 | [
"Enhancement"
] | Make `zero_division` parameter consistent in the different metric
This is an issue to report the step to actually take over the work of @marctorsoc in https://github.com/scikit-learn/scikit-learn/pull/23183 and split the PR into smaller one to facilitate the review process.
The intend is to make the `zero_division` p... | 29,048 | [
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0.03284919261932373,
0.046216... |
https://github.com/scikit-learn/scikit-learn/issues/29048 | [
"Enhancement"
] | Make `zero_division` parameter consistent in the different metric
This is an issue to report the step to actually take over the work of @marctorsoc in https://github.com/scikit-learn/scikit-learn/pull/23183 and split the PR into smaller one to facilitate the review process.
The intend is to make the `zero_division` p... | 29,048 | [
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0.03284919261932373,
0.046216... |
https://github.com/scikit-learn/scikit-learn/issues/29048 | [
"Enhancement"
] | Make `zero_division` parameter consistent in the different metric
This is an issue to report the step to actually take over the work of @marctorsoc in https://github.com/scikit-learn/scikit-learn/pull/23183 and split the PR into smaller one to facilitate the review process.
The intend is to make the `zero_division` p... | 29,048 | [
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0.0533316433429718,
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0.03284919261932373,
0.046216... |
https://github.com/scikit-learn/scikit-learn/issues/29048 | [
"Enhancement"
] | Make `zero_division` parameter consistent in the different metric
This is an issue to report the step to actually take over the work of @marctorsoc in https://github.com/scikit-learn/scikit-learn/pull/23183 and split the PR into smaller one to facilitate the review process.
The intend is to make the `zero_division` p... | 29,048 | [
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0.005561315920203924,
0.03284919261932373,
0.046216... |
https://github.com/scikit-learn/scikit-learn/issues/29048 | [
"Enhancement"
] | Make `zero_division` parameter consistent in the different metric
This is an issue to report the step to actually take over the work of @marctorsoc in https://github.com/scikit-learn/scikit-learn/pull/23183 and split the PR into smaller one to facilitate the review process.
The intend is to make the `zero_division` p... | 29,048 | [
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0.03284919261932373,
0.046216... |
https://github.com/scikit-learn/scikit-learn/issues/29048 | [
"Enhancement"
] | Make `zero_division` parameter consistent in the different metric
This is an issue to report the step to actually take over the work of @marctorsoc in https://github.com/scikit-learn/scikit-learn/pull/23183 and split the PR into smaller one to facilitate the review process.
The intend is to make the `zero_division` p... | 29,048 | [
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0.03284919261932373,
0.046216... |
https://github.com/scikit-learn/scikit-learn/issues/29048 | [
"Enhancement"
] | Make `zero_division` parameter consistent in the different metric
This is an issue to report the step to actually take over the work of @marctorsoc in https://github.com/scikit-learn/scikit-learn/pull/23183 and split the PR into smaller one to facilitate the review process.
The intend is to make the `zero_division` p... | 29,048 | [
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0.046216... |
https://github.com/scikit-learn/scikit-learn/issues/29048 | [
"Enhancement"
] | Make `zero_division` parameter consistent in the different metric
This is an issue to report the step to actually take over the work of @marctorsoc in https://github.com/scikit-learn/scikit-learn/pull/23183 and split the PR into smaller one to facilitate the review process.
The intend is to make the `zero_division` p... | 29,048 | [
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0.02186780609190464,
0.005561315920203924,
0.03284919261932373,
0.046216... |
https://github.com/scikit-learn/scikit-learn/issues/29048 | [
"Enhancement"
] | Make `zero_division` parameter consistent in the different metric
This is an issue to report the step to actually take over the work of @marctorsoc in https://github.com/scikit-learn/scikit-learn/pull/23183 and split the PR into smaller one to facilitate the review process.
The intend is to make the `zero_division` p... | 29,048 | [
-0.01399283017963171,
0.014668786898255348,
0.0533316433429718,
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0.02186780609190464,
0.005561315920203924,
0.03284919261932373,
0.046216... |
https://github.com/scikit-learn/scikit-learn/issues/29048 | [
"Enhancement"
] | Make `zero_division` parameter consistent in the different metric
This is an issue to report the step to actually take over the work of @marctorsoc in https://github.com/scikit-learn/scikit-learn/pull/23183 and split the PR into smaller one to facilitate the review process.
The intend is to make the `zero_division` p... | 29,048 | [
-0.01399283017963171,
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0.0533316433429718,
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0.02186780609190464,
0.005561315920203924,
0.03284919261932373,
0.046216... |
https://github.com/scikit-learn/scikit-learn/issues/29048 | [
"Enhancement"
] | Make `zero_division` parameter consistent in the different metric
This is an issue to report the step to actually take over the work of @marctorsoc in https://github.com/scikit-learn/scikit-learn/pull/23183 and split the PR into smaller one to facilitate the review process.
The intend is to make the `zero_division` p... | 29,048 | [
-0.01399283017963171,
0.014668786898255348,
0.0533316433429718,
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0.02186780609190464,
0.005561315920203924,
0.03284919261932373,
0.046216... |
https://github.com/scikit-learn/scikit-learn/issues/29048 | [
"Enhancement"
] | Make `zero_division` parameter consistent in the different metric
This is an issue to report the step to actually take over the work of @marctorsoc in https://github.com/scikit-learn/scikit-learn/pull/23183 and split the PR into smaller one to facilitate the review process.
The intend is to make the `zero_division` p... | 29,048 | [
-0.01399283017963171,
0.014668786898255348,
0.0533316433429718,
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0.02186780609190464,
0.005561315920203924,
0.03284919261932373,
0.046216... |
https://github.com/scikit-learn/scikit-learn/issues/29048 | [
"Enhancement"
] | Make `zero_division` parameter consistent in the different metric
This is an issue to report the step to actually take over the work of @marctorsoc in https://github.com/scikit-learn/scikit-learn/pull/23183 and split the PR into smaller one to facilitate the review process.
The intend is to make the `zero_division` p... | 29,048 | [
-0.01399283017963171,
0.014668786898255348,
0.0533316433429718,
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0.02186780609190464,
0.005561315920203924,
0.03284919261932373,
0.046216... |
https://github.com/scikit-learn/scikit-learn/issues/29048 | [
"Enhancement"
] | Make `zero_division` parameter consistent in the different metric
This is an issue to report the step to actually take over the work of @marctorsoc in https://github.com/scikit-learn/scikit-learn/pull/23183 and split the PR into smaller one to facilitate the review process.
The intend is to make the `zero_division` p... | 29,048 | [
-0.01399283017963171,
0.014668786898255348,
0.0533316433429718,
-0.032538075000047684,
0.05320441722869873,
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0.02186780609190464,
0.005561315920203924,
0.03284919261932373,
0.046216... |
https://github.com/scikit-learn/scikit-learn/issues/29048 | [
"Enhancement"
] | Make `zero_division` parameter consistent in the different metric
This is an issue to report the step to actually take over the work of @marctorsoc in https://github.com/scikit-learn/scikit-learn/pull/23183 and split the PR into smaller one to facilitate the review process.
The intend is to make the `zero_division` p... | 29,048 | [
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0.014668786898255348,
0.0533316433429718,
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0.02186780609190464,
0.005561315920203924,
0.03284919261932373,
0.046216... |
https://github.com/scikit-learn/scikit-learn/issues/29048 | [
"Enhancement"
] | Make `zero_division` parameter consistent in the different metric
This is an issue to report the step to actually take over the work of @marctorsoc in https://github.com/scikit-learn/scikit-learn/pull/23183 and split the PR into smaller one to facilitate the review process.
The intend is to make the `zero_division` p... | 29,048 | [
-0.01399283017963171,
0.014668786898255348,
0.0533316433429718,
-0.032538075000047684,
0.05320441722869873,
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0.02186780609190464,
0.005561315920203924,
0.03284919261932373,
0.046216... |
https://github.com/scikit-learn/scikit-learn/issues/29048 | [
"Enhancement"
] | Make `zero_division` parameter consistent in the different metric
This is an issue to report the step to actually take over the work of @marctorsoc in https://github.com/scikit-learn/scikit-learn/pull/23183 and split the PR into smaller one to facilitate the review process.
The intend is to make the `zero_division` p... | 29,048 | [
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0.014668786898255348,
0.0533316433429718,
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0.02186780609190464,
0.005561315920203924,
0.03284919261932373,
0.046216... |
https://github.com/scikit-learn/scikit-learn/issues/29048 | [
"Enhancement"
] | Make `zero_division` parameter consistent in the different metric
This is an issue to report the step to actually take over the work of @marctorsoc in https://github.com/scikit-learn/scikit-learn/pull/23183 and split the PR into smaller one to facilitate the review process.
The intend is to make the `zero_division` p... | 29,048 | [
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0.0533316433429718,
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0.02186780609190464,
0.005561315920203924,
0.03284919261932373,
0.046216... |
https://github.com/scikit-learn/scikit-learn/issues/29046 | [
"Enhancement"
] | MAINT define a single time _estimator_has and refactor code
From past discussion, I realized that we are defining the same `_estimator_has` in several places while it does exactly the same job and has the same semantic.
I think we should do a bit of cleaning by moving this function into a submodule in `sklearn.util... | 29,046 | [
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https://github.com/scikit-learn/scikit-learn/issues/29046 | [
"Enhancement"
] | MAINT define a single time _estimator_has and refactor code
From past discussion, I realized that we are defining the same `_estimator_has` in several places while it does exactly the same job and has the same semantic.
I think we should do a bit of cleaning by moving this function into a submodule in `sklearn.util... | 29,046 | [
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https://github.com/scikit-learn/scikit-learn/issues/29044 | [
"Bug"
] | ⚠️ CI failed on Linux_Nightly_PyPy.pypy3 (last failure: Jun 03, 2024) ⚠️
**CI is still failing on [Linux_Nightly_PyPy.pypy3](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=67132&view=logs&j=0b16f832-29d6-5b92-1c23-eb006f606a66)** (Jun 03, 2024)
Unable to find junit file. Please see link for det... | 29,044 | [
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0.053... |
https://github.com/scikit-learn/scikit-learn/issues/29044 | [
"Bug"
] | ⚠️ CI failed on Linux_Nightly_PyPy.pypy3 (last failure: Jun 03, 2024) ⚠️
**CI is still failing on [Linux_Nightly_PyPy.pypy3](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=67132&view=logs&j=0b16f832-29d6-5b92-1c23-eb006f606a66)** (Jun 03, 2024)
Unable to find junit file. Please see link for det... | 29,044 | [
0.029520375654101372,
0.004700454883277416,
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0.0681... |
https://github.com/scikit-learn/scikit-learn/issues/29043 | [
"Documentation",
"Developer API"
] | Revamp the developer documentation when it comes to roll scikit-learn compatible estimator
I find the documentation helping at writing a scikit-learn estimator a bit oldish: https://scikit-learn.org/dev/developers/develop.html
I think that we could revamp the documentation with a new look. Probably, we would like t... | 29,043 | [
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0.0585... |
https://github.com/scikit-learn/scikit-learn/issues/29042 | [
"Bug"
] | OneHotEncoder fails on missing values when Pandas uses PyArrow backend
### Describe the bug
A while back @thomasjpfan and @lorentzenchr contributed https://github.com/scikit-learn/scikit-learn/pull/17317 which enabled missing value support in `OneHotEncoder`
> For object dtypes, None and np.nan is support for missin... | 29,042 | [
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0.037413325160741806,
0.03332... |
https://github.com/scikit-learn/scikit-learn/issues/29042 | [
"Bug"
] | OneHotEncoder fails on missing values when Pandas uses PyArrow backend
### Describe the bug
A while back @thomasjpfan and @lorentzenchr contributed https://github.com/scikit-learn/scikit-learn/pull/17317 which enabled missing value support in `OneHotEncoder`
> For object dtypes, None and np.nan is support for missin... | 29,042 | [
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0.028509963303804398,
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0.03733905032277107,
0.016144607216119766,
0.037413325160741806,
0.03332... |
https://github.com/scikit-learn/scikit-learn/issues/29042 | [
"Bug"
] | OneHotEncoder fails on missing values when Pandas uses PyArrow backend
### Describe the bug
A while back @thomasjpfan and @lorentzenchr contributed https://github.com/scikit-learn/scikit-learn/pull/17317 which enabled missing value support in `OneHotEncoder`
> For object dtypes, None and np.nan is support for missin... | 29,042 | [
-0.0022378675639629364,
0.0980224534869194,
0.028509963303804398,
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0.08992457389831543,
0.020679041743278503,
0.0493602529168129,
0.020689623430371284,
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0.03733905032277107,
0.016144607216119766,
0.037413325160741806,
0.03332... |
https://github.com/scikit-learn/scikit-learn/issues/29042 | [
"Bug"
] | OneHotEncoder fails on missing values when Pandas uses PyArrow backend
### Describe the bug
A while back @thomasjpfan and @lorentzenchr contributed https://github.com/scikit-learn/scikit-learn/pull/17317 which enabled missing value support in `OneHotEncoder`
> For object dtypes, None and np.nan is support for missin... | 29,042 | [
-0.0022378675639629364,
0.0980224534869194,
0.028509963303804398,
-0.04389560967683792,
0.08992457389831543,
0.020679041743278503,
0.0493602529168129,
0.020689623430371284,
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-0.009715620428323746,
0.03733905032277107,
0.016144607216119766,
0.037413325160741806,
0.03332... |
https://github.com/scikit-learn/scikit-learn/issues/29040 | [
"Documentation",
"Needs Triage"
] | "Building from source" instructions are outdated
### Describe the issue linked to the documentation
https://scikit-learn.org/stable/developers/advanced_installation.html#building-from-source seems to be a few years old, and doesn't leverage Meson. https://scikit-learn.org/stable/developers/advanced_installation.html#... | 29,040 | [
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0.07786098122596741,
0.020082935690879822,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/29040 | [
"Documentation",
"Needs Triage"
] | "Building from source" instructions are outdated
### Describe the issue linked to the documentation
https://scikit-learn.org/stable/developers/advanced_installation.html#building-from-source seems to be a few years old, and doesn't leverage Meson. https://scikit-learn.org/stable/developers/advanced_installation.html#... | 29,040 | [
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0.03454377129673958,
0.07786098122596741,
0.020082935690879822,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/29032 | [
"New Feature"
] | Improve `FunctionTransformer` diagram representation
### Describe the workflow you want to enable
Currently, using multiple `FunctionTransformers` in a pipeline leads to an uninformative view:
```python
import pandas as pd
from sklearn.pipeline import make_pipeline
from sklearn.preprocessing import FunctionTran... | 29,032 | [
-0.022034209221601486,
0.04361189901828766,
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0.0056962366215884686,
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0.07267193496227264,
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0.0035064714029431343,
-0.002921957289800048,
-0.00010576139902696013,
0.036882974207401276,
0.022084707394242287... |
https://github.com/scikit-learn/scikit-learn/issues/29032 | [
"New Feature"
] | Improve `FunctionTransformer` diagram representation
### Describe the workflow you want to enable
Currently, using multiple `FunctionTransformers` in a pipeline leads to an uninformative view:
```python
import pandas as pd
from sklearn.pipeline import make_pipeline
from sklearn.preprocessing import FunctionTran... | 29,032 | [
-0.022034209221601486,
0.04361189901828766,
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-0.02535749040544033,
0.0056962366215884686,
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0.07267193496227264,
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0.0035064714029431343,
-0.002921957289800048,
-0.00010576139902696013,
0.036882974207401276,
0.022084707394242287... |
https://github.com/scikit-learn/scikit-learn/issues/29032 | [
"New Feature"
] | Improve `FunctionTransformer` diagram representation
### Describe the workflow you want to enable
Currently, using multiple `FunctionTransformers` in a pipeline leads to an uninformative view:
```python
import pandas as pd
from sklearn.pipeline import make_pipeline
from sklearn.preprocessing import FunctionTran... | 29,032 | [
-0.022034209221601486,
0.04361189901828766,
-0.014070417732000351,
-0.02535749040544033,
0.0056962366215884686,
-0.024692270904779434,
0.07267193496227264,
-0.020999085158109665,
0.0035064714029431343,
-0.002921957289800048,
-0.00010576139902696013,
0.036882974207401276,
0.022084707394242287... |
https://github.com/scikit-learn/scikit-learn/issues/29032 | [
"New Feature"
] | Improve `FunctionTransformer` diagram representation
### Describe the workflow you want to enable
Currently, using multiple `FunctionTransformers` in a pipeline leads to an uninformative view:
```python
import pandas as pd
from sklearn.pipeline import make_pipeline
from sklearn.preprocessing import FunctionTran... | 29,032 | [
-0.022034209221601486,
0.04361189901828766,
-0.014070417732000351,
-0.02535749040544033,
0.0056962366215884686,
-0.024692270904779434,
0.07267193496227264,
-0.020999085158109665,
0.0035064714029431343,
-0.002921957289800048,
-0.00010576139902696013,
0.036882974207401276,
0.022084707394242287... |
https://github.com/scikit-learn/scikit-learn/issues/29032 | [
"New Feature"
] | Improve `FunctionTransformer` diagram representation
### Describe the workflow you want to enable
Currently, using multiple `FunctionTransformers` in a pipeline leads to an uninformative view:
```python
import pandas as pd
from sklearn.pipeline import make_pipeline
from sklearn.preprocessing import FunctionTran... | 29,032 | [
-0.022034209221601486,
0.04361189901828766,
-0.014070417732000351,
-0.02535749040544033,
0.0056962366215884686,
-0.024692270904779434,
0.07267193496227264,
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0.0035064714029431343,
-0.002921957289800048,
-0.00010576139902696013,
0.036882974207401276,
0.022084707394242287... |
https://github.com/scikit-learn/scikit-learn/issues/29032 | [
"New Feature"
] | Improve `FunctionTransformer` diagram representation
### Describe the workflow you want to enable
Currently, using multiple `FunctionTransformers` in a pipeline leads to an uninformative view:
```python
import pandas as pd
from sklearn.pipeline import make_pipeline
from sklearn.preprocessing import FunctionTran... | 29,032 | [
-0.022034209221601486,
0.04361189901828766,
-0.014070417732000351,
-0.02535749040544033,
0.0056962366215884686,
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0.07267193496227264,
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0.0035064714029431343,
-0.002921957289800048,
-0.00010576139902696013,
0.036882974207401276,
0.022084707394242287... |
https://github.com/scikit-learn/scikit-learn/issues/29032 | [
"New Feature"
] | Improve `FunctionTransformer` diagram representation
### Describe the workflow you want to enable
Currently, using multiple `FunctionTransformers` in a pipeline leads to an uninformative view:
```python
import pandas as pd
from sklearn.pipeline import make_pipeline
from sklearn.preprocessing import FunctionTran... | 29,032 | [
-0.022034209221601486,
0.04361189901828766,
-0.014070417732000351,
-0.02535749040544033,
0.0056962366215884686,
-0.024692270904779434,
0.07267193496227264,
-0.020999085158109665,
0.0035064714029431343,
-0.002921957289800048,
-0.00010576139902696013,
0.036882974207401276,
0.022084707394242287... |
https://github.com/scikit-learn/scikit-learn/issues/29032 | [
"New Feature"
] | Improve `FunctionTransformer` diagram representation
### Describe the workflow you want to enable
Currently, using multiple `FunctionTransformers` in a pipeline leads to an uninformative view:
```python
import pandas as pd
from sklearn.pipeline import make_pipeline
from sklearn.preprocessing import FunctionTran... | 29,032 | [
-0.022034209221601486,
0.04361189901828766,
-0.014070417732000351,
-0.02535749040544033,
0.0056962366215884686,
-0.024692270904779434,
0.07267193496227264,
-0.020999085158109665,
0.0035064714029431343,
-0.002921957289800048,
-0.00010576139902696013,
0.036882974207401276,
0.022084707394242287... |
https://github.com/scikit-learn/scikit-learn/issues/29032 | [
"New Feature"
] | Improve `FunctionTransformer` diagram representation
### Describe the workflow you want to enable
Currently, using multiple `FunctionTransformers` in a pipeline leads to an uninformative view:
```python
import pandas as pd
from sklearn.pipeline import make_pipeline
from sklearn.preprocessing import FunctionTran... | 29,032 | [
-0.022034209221601486,
0.04361189901828766,
-0.014070417732000351,
-0.02535749040544033,
0.0056962366215884686,
-0.024692270904779434,
0.07267193496227264,
-0.020999085158109665,
0.0035064714029431343,
-0.002921957289800048,
-0.00010576139902696013,
0.036882974207401276,
0.022084707394242287... |
https://github.com/scikit-learn/scikit-learn/issues/29032 | [
"New Feature"
] | Improve `FunctionTransformer` diagram representation
### Describe the workflow you want to enable
Currently, using multiple `FunctionTransformers` in a pipeline leads to an uninformative view:
```python
import pandas as pd
from sklearn.pipeline import make_pipeline
from sklearn.preprocessing import FunctionTran... | 29,032 | [
-0.022034209221601486,
0.04361189901828766,
-0.014070417732000351,
-0.02535749040544033,
0.0056962366215884686,
-0.024692270904779434,
0.07267193496227264,
-0.020999085158109665,
0.0035064714029431343,
-0.002921957289800048,
-0.00010576139902696013,
0.036882974207401276,
0.022084707394242287... |
https://github.com/scikit-learn/scikit-learn/issues/29027 | [
"Documentation",
"Enhancement",
"RFC"
] | DOC Investigate scipy-doctest for more convenient doctests
I learned about [scipy-doctest](https://github.com/scipy/scipy_doctest) recent release in the [Scientific Python Discourse announcement](https://discuss.scientific-python.org/t/ann-scipy-doctest-package/1181). Apparently, scipy-doctest has been used internally... | 29,027 | [
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0.005252887960523367,
0.011348243802785873,
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0.038492485880851746,
0.047891534864902496,
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0.024370089173316956,
0.06416715681552887,
0.02766948938369751,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/29027 | [
"Documentation",
"Enhancement",
"RFC"
] | DOC Investigate scipy-doctest for more convenient doctests
I learned about [scipy-doctest](https://github.com/scipy/scipy_doctest) recent release in the [Scientific Python Discourse announcement](https://discuss.scientific-python.org/t/ann-scipy-doctest-package/1181). Apparently, scipy-doctest has been used internally... | 29,027 | [
-0.008429857902228832,
0.005252887960523367,
0.011348243802785873,
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0.005157266743481159,
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0.038492485880851746,
0.047891534864902496,
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0.024370089173316956,
0.06416715681552887,
0.02766948938369751,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/29027 | [
"Documentation",
"Enhancement",
"RFC"
] | DOC Investigate scipy-doctest for more convenient doctests
I learned about [scipy-doctest](https://github.com/scipy/scipy_doctest) recent release in the [Scientific Python Discourse announcement](https://discuss.scientific-python.org/t/ann-scipy-doctest-package/1181). Apparently, scipy-doctest has been used internally... | 29,027 | [
-0.008429857902228832,
0.005252887960523367,
0.011348243802785873,
-0.011066035367548466,
0.005157266743481159,
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0.038492485880851746,
0.047891534864902496,
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-0.039486732333898544,
0.024370089173316956,
0.06416715681552887,
0.02766948938369751,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/29027 | [
"Documentation",
"Enhancement",
"RFC"
] | DOC Investigate scipy-doctest for more convenient doctests
I learned about [scipy-doctest](https://github.com/scipy/scipy_doctest) recent release in the [Scientific Python Discourse announcement](https://discuss.scientific-python.org/t/ann-scipy-doctest-package/1181). Apparently, scipy-doctest has been used internally... | 29,027 | [
-0.008429857902228832,
0.005252887960523367,
0.011348243802785873,
-0.011066035367548466,
0.005157266743481159,
-0.01994599588215351,
0.038492485880851746,
0.047891534864902496,
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-0.039486732333898544,
0.024370089173316956,
0.06416715681552887,
0.02766948938369751,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/29027 | [
"Documentation",
"Enhancement",
"RFC"
] | DOC Investigate scipy-doctest for more convenient doctests
I learned about [scipy-doctest](https://github.com/scipy/scipy_doctest) recent release in the [Scientific Python Discourse announcement](https://discuss.scientific-python.org/t/ann-scipy-doctest-package/1181). Apparently, scipy-doctest has been used internally... | 29,027 | [
-0.008429857902228832,
0.005252887960523367,
0.011348243802785873,
-0.011066035367548466,
0.005157266743481159,
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0.038492485880851746,
0.047891534864902496,
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-0.039486732333898544,
0.024370089173316956,
0.06416715681552887,
0.02766948938369751,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/29027 | [
"Documentation",
"Enhancement",
"RFC"
] | DOC Investigate scipy-doctest for more convenient doctests
I learned about [scipy-doctest](https://github.com/scipy/scipy_doctest) recent release in the [Scientific Python Discourse announcement](https://discuss.scientific-python.org/t/ann-scipy-doctest-package/1181). Apparently, scipy-doctest has been used internally... | 29,027 | [
-0.008429857902228832,
0.005252887960523367,
0.011348243802785873,
-0.011066035367548466,
0.005157266743481159,
-0.01994599588215351,
0.038492485880851746,
0.047891534864902496,
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-0.039486732333898544,
0.024370089173316956,
0.06416715681552887,
0.02766948938369751,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/29027 | [
"Documentation",
"Enhancement",
"RFC"
] | DOC Investigate scipy-doctest for more convenient doctests
I learned about [scipy-doctest](https://github.com/scipy/scipy_doctest) recent release in the [Scientific Python Discourse announcement](https://discuss.scientific-python.org/t/ann-scipy-doctest-package/1181). Apparently, scipy-doctest has been used internally... | 29,027 | [
-0.008429857902228832,
0.005252887960523367,
0.011348243802785873,
-0.011066035367548466,
0.005157266743481159,
-0.01994599588215351,
0.038492485880851746,
0.047891534864902496,
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-0.039486732333898544,
0.024370089173316956,
0.06416715681552887,
0.02766948938369751,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/29027 | [
"Documentation",
"Enhancement",
"RFC"
] | DOC Investigate scipy-doctest for more convenient doctests
I learned about [scipy-doctest](https://github.com/scipy/scipy_doctest) recent release in the [Scientific Python Discourse announcement](https://discuss.scientific-python.org/t/ann-scipy-doctest-package/1181). Apparently, scipy-doctest has been used internally... | 29,027 | [
-0.008429857902228832,
0.005252887960523367,
0.011348243802785873,
-0.011066035367548466,
0.005157266743481159,
-0.01994599588215351,
0.038492485880851746,
0.047891534864902496,
-0.013537595048546791,
-0.039486732333898544,
0.024370089173316956,
0.06416715681552887,
0.02766948938369751,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/29027 | [
"Documentation",
"Enhancement",
"RFC"
] | DOC Investigate scipy-doctest for more convenient doctests
I learned about [scipy-doctest](https://github.com/scipy/scipy_doctest) recent release in the [Scientific Python Discourse announcement](https://discuss.scientific-python.org/t/ann-scipy-doctest-package/1181). Apparently, scipy-doctest has been used internally... | 29,027 | [
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0.024370089173316956,
0.06416715681552887,
0.02766948938369751,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/29027 | [
"Documentation",
"Enhancement",
"RFC"
] | DOC Investigate scipy-doctest for more convenient doctests
I learned about [scipy-doctest](https://github.com/scipy/scipy_doctest) recent release in the [Scientific Python Discourse announcement](https://discuss.scientific-python.org/t/ann-scipy-doctest-package/1181). Apparently, scipy-doctest has been used internally... | 29,027 | [
-0.008429857902228832,
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0.038492485880851746,
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0.024370089173316956,
0.06416715681552887,
0.02766948938369751,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/29027 | [
"Documentation",
"Enhancement",
"RFC"
] | DOC Investigate scipy-doctest for more convenient doctests
I learned about [scipy-doctest](https://github.com/scipy/scipy_doctest) recent release in the [Scientific Python Discourse announcement](https://discuss.scientific-python.org/t/ann-scipy-doctest-package/1181). Apparently, scipy-doctest has been used internally... | 29,027 | [
-0.008429857902228832,
0.005252887960523367,
0.011348243802785873,
-0.011066035367548466,
0.005157266743481159,
-0.01994599588215351,
0.038492485880851746,
0.047891534864902496,
-0.013537595048546791,
-0.039486732333898544,
0.024370089173316956,
0.06416715681552887,
0.02766948938369751,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/29019 | [
"Bug",
"Blocker"
] | TunedThreasholdClassifierCV failing inside a SearchCV object
I changed the existing example slightly, to put the estimator inside the SearchCV instead of tuning after the search. Here's the reproducer:
```py
# %%
from sklearn.datasets import fetch_openml
# %%
credit_card = fetch_openml(data_id=1597, as_frame=... | 29,019 | [
0.010315453633666039,
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0.025093667209148407,
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0.004201357718557119,
0.010137631557881832,
-0.028132131323218346,
-0.020318802446126938,
-0.006176863331347704,
0.054938629269599915,
0.037641558796167374,
0... |
https://github.com/scikit-learn/scikit-learn/issues/29017 | [
"New Feature",
"Needs Decision"
] | Using decision boundary display to plot the relationship between any 2 features if model is fitted to more than 2 features
### Describe the workflow you want to enable
Currently, it seems like it is not possible to pass in a model that has been fitted to more than 2 features to the DecisionBoundaryDisplay.from_estima... | 29,017 | [
-0.04523108899593353,
0.061795923858881,
0.017816442996263504,
-0.022876150906085968,
-0.0019943302031606436,
-0.03272773697972298,
0.057897165417671204,
-0.007560160476714373,
0.06640840321779251,
-0.0011042600963264704,
0.012589032761752605,
0.03444192185997963,
-0.037906281650066376,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/29017 | [
"New Feature",
"Needs Decision"
] | Using decision boundary display to plot the relationship between any 2 features if model is fitted to more than 2 features
### Describe the workflow you want to enable
Currently, it seems like it is not possible to pass in a model that has been fitted to more than 2 features to the DecisionBoundaryDisplay.from_estima... | 29,017 | [
-0.047680530697107315,
0.03307618573307991,
0.022936709225177765,
-0.034895818680524826,
-0.012751090340316296,
-0.04393603652715683,
0.06856152415275574,
-0.029199693351984024,
0.04535285755991936,
-0.00039926363388076425,
0.024592451751232147,
0.04118858650326729,
-0.0363590233027935,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/29017 | [
"New Feature",
"Needs Decision"
] | Using decision boundary display to plot the relationship between any 2 features if model is fitted to more than 2 features
### Describe the workflow you want to enable
Currently, it seems like it is not possible to pass in a model that has been fitted to more than 2 features to the DecisionBoundaryDisplay.from_estima... | 29,017 | [
-0.05506305769085884,
0.045563388615846634,
0.015000986866652966,
-0.029319506138563156,
0.0030619993340224028,
-0.031069602817296982,
0.0563005656003952,
-0.01140973623842001,
0.06043054908514023,
0.008692070841789246,
0.012553270906209946,
0.0436994805932045,
-0.032858848571777344,
0.086... |
https://github.com/scikit-learn/scikit-learn/issues/29017 | [
"New Feature",
"Needs Decision"
] | Using decision boundary display to plot the relationship between any 2 features if model is fitted to more than 2 features
### Describe the workflow you want to enable
Currently, it seems like it is not possible to pass in a model that has been fitted to more than 2 features to the DecisionBoundaryDisplay.from_estima... | 29,017 | [
-0.057930588722229004,
0.04819249361753464,
0.015102160163223743,
-0.02939603105187416,
0.0025464666541665792,
-0.03027457371354103,
0.05532539263367653,
-0.010841824114322662,
0.0606374628841877,
0.01094925869256258,
0.010869874618947506,
0.04497469589114189,
-0.03493357077240944,
0.08397... |
https://github.com/scikit-learn/scikit-learn/issues/29017 | [
"New Feature",
"Needs Decision"
] | Using decision boundary display to plot the relationship between any 2 features if model is fitted to more than 2 features
### Describe the workflow you want to enable
Currently, it seems like it is not possible to pass in a model that has been fitted to more than 2 features to the DecisionBoundaryDisplay.from_estima... | 29,017 | [
-0.04176538065075874,
0.059518299996852875,
0.019550496712327003,
-0.025341344997286797,
0.0030360310338437557,
-0.03212527930736542,
0.0523063987493515,
-0.008408181369304657,
0.07115527242422104,
0.0009603961952961981,
0.018749896436929703,
0.04082375019788742,
-0.03347862511873245,
0.07... |
https://github.com/scikit-learn/scikit-learn/issues/29016 | [
"Bug"
] | MultiOutputClassifier does not rely on estimator to provide pairwise tag
### Describe the bug
I use the `MultiOutputClassifier` function to make `SVC` multilabel.
Then, if I use the linear or rbf kernel the cross_validation function works perfectly fine.
However, when I use `SVC` with precomputed kernel is h... | 29,016 | [
-0.0023773550055921078,
-0.011430581100285053,
0.03924034535884857,
0.02402607351541519,
0.09324675798416138,
0.007511110045015812,
0.05196285620331764,
0.021229885518550873,
0.04111936688423157,
0.004174003843218088,
0.01088882889598608,
0.08739224821329117,
0.014485282823443413,
-0.00028... |
https://github.com/scikit-learn/scikit-learn/issues/29016 | [
"Bug"
] | MultiOutputClassifier does not rely on estimator to provide pairwise tag
### Describe the bug
I use the `MultiOutputClassifier` function to make `SVC` multilabel.
Then, if I use the linear or rbf kernel the cross_validation function works perfectly fine.
However, when I use `SVC` with precomputed kernel is h... | 29,016 | [
-0.0023773550055921078,
-0.011430581100285053,
0.03924034535884857,
0.02402607351541519,
0.09324675798416138,
0.007511110045015812,
0.05196285620331764,
0.021229885518550873,
0.04111936688423157,
0.004174003843218088,
0.01088882889598608,
0.08739224821329117,
0.014485282823443413,
-0.00028... |
https://github.com/scikit-learn/scikit-learn/issues/29016 | [
"Bug"
] | MultiOutputClassifier does not rely on estimator to provide pairwise tag
### Describe the bug
I use the `MultiOutputClassifier` function to make `SVC` multilabel.
Then, if I use the linear or rbf kernel the cross_validation function works perfectly fine.
However, when I use `SVC` with precomputed kernel is h... | 29,016 | [
-0.0023773550055921078,
-0.011430581100285053,
0.03924034535884857,
0.02402607351541519,
0.09324675798416138,
0.007511110045015812,
0.05196285620331764,
0.021229885518550873,
0.04111936688423157,
0.004174003843218088,
0.01088882889598608,
0.08739224821329117,
0.014485282823443413,
-0.00028... |
https://github.com/scikit-learn/scikit-learn/issues/29016 | [
"Bug"
] | MultiOutputClassifier does not rely on estimator to provide pairwise tag
### Describe the bug
I use the `MultiOutputClassifier` function to make `SVC` multilabel.
Then, if I use the linear or rbf kernel the cross_validation function works perfectly fine.
However, when I use `SVC` with precomputed kernel is h... | 29,016 | [
-0.0023773550055921078,
-0.011430581100285053,
0.03924034535884857,
0.02402607351541519,
0.09324675798416138,
0.007511110045015812,
0.05196285620331764,
0.021229885518550873,
0.04111936688423157,
0.004174003843218088,
0.01088882889598608,
0.08739224821329117,
0.014485282823443413,
-0.00028... |
https://github.com/scikit-learn/scikit-learn/issues/29016 | [
"Bug"
] | MultiOutputClassifier does not rely on estimator to provide pairwise tag
### Describe the bug
I use the `MultiOutputClassifier` function to make `SVC` multilabel.
Then, if I use the linear or rbf kernel the cross_validation function works perfectly fine.
However, when I use `SVC` with precomputed kernel is h... | 29,016 | [
-0.0023773550055921078,
-0.011430581100285053,
0.03924034535884857,
0.02402607351541519,
0.09324675798416138,
0.007511110045015812,
0.05196285620331764,
0.021229885518550873,
0.04111936688423157,
0.004174003843218088,
0.01088882889598608,
0.08739224821329117,
0.014485282823443413,
-0.00028... |
https://github.com/scikit-learn/scikit-learn/issues/29013 | [
"Bug",
"Build / CI",
"free-threading"
] | Pyodide build broken by updating meson.build to C17
Scheduled Pyodide build failed today see [build log](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=66512&view=logs&jobId=6fac3219-cc32-5595-eb73-7f086a643b12&j=6fac3219-cc32-5595-eb73-7f086a643b12&t=6856d197-9931-5ad8-f897-5714e4bdfa31)
```
... | 29,013 | [
0.01730509288609028,
0.04534152150154114,
-0.01847153715789318,
-0.02896447479724884,
0.049188047647476196,
0.03125739470124245,
-0.023525329306721687,
0.006330831907689571,
-0.08644122630357742,
-0.025133319199085236,
0.022924339398741722,
0.07447364926338196,
0.01035221852362156,
0.00867... |
https://github.com/scikit-learn/scikit-learn/issues/29013 | [
"Bug",
"Build / CI",
"free-threading"
] | Pyodide build broken by updating meson.build to C17
Scheduled Pyodide build failed today see [build log](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=66512&view=logs&jobId=6fac3219-cc32-5595-eb73-7f086a643b12&j=6fac3219-cc32-5595-eb73-7f086a643b12&t=6856d197-9931-5ad8-f897-5714e4bdfa31)
```
... | 29,013 | [
0.01730509288609028,
0.04534152150154114,
-0.01847153715789318,
-0.02896447479724884,
0.049188047647476196,
0.03125739470124245,
-0.023525329306721687,
0.006330831907689571,
-0.08644122630357742,
-0.025133319199085236,
0.022924339398741722,
0.07447364926338196,
0.01035221852362156,
0.00867... |
https://github.com/scikit-learn/scikit-learn/issues/29013 | [
"Bug",
"Build / CI",
"free-threading"
] | Pyodide build broken by updating meson.build to C17
Scheduled Pyodide build failed today see [build log](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=66512&view=logs&jobId=6fac3219-cc32-5595-eb73-7f086a643b12&j=6fac3219-cc32-5595-eb73-7f086a643b12&t=6856d197-9931-5ad8-f897-5714e4bdfa31)
```
... | 29,013 | [
0.01730509288609028,
0.04534152150154114,
-0.01847153715789318,
-0.02896447479724884,
0.049188047647476196,
0.03125739470124245,
-0.023525329306721687,
0.006330831907689571,
-0.08644122630357742,
-0.025133319199085236,
0.022924339398741722,
0.07447364926338196,
0.01035221852362156,
0.00867... |
https://github.com/scikit-learn/scikit-learn/issues/29009 | [
"Documentation"
] | Incorrect documented output shape for `predict` method of linear models when `n_targets` > 1
### Describe the issue linked to the documentation
For some classes under `sklearn.linear_model` such as `LinearRegression`, `Ridge`, `RidgeCV`, and a bunch of others, the documentation for the `predict` method states that ... | 29,009 | [
0.029374713078141212,
0.0073606898076832294,
0.007543640676885843,
0.0334276482462883,
0.06391315907239914,
-0.06078891456127167,
0.07017149776220322,
0.016578979790210724,
0.00815337523818016,
0.021169167011976242,
0.04728911817073822,
0.04823300242424011,
-0.0063680624589324,
0.035939093... |
https://github.com/scikit-learn/scikit-learn/issues/29009 | [
"Documentation"
] | Incorrect documented output shape for `predict` method of linear models when `n_targets` > 1
### Describe the issue linked to the documentation
For some classes under `sklearn.linear_model` such as `LinearRegression`, `Ridge`, `RidgeCV`, and a bunch of others, the documentation for the `predict` method states that ... | 29,009 | [
0.028332553803920746,
-0.004966226406395435,
0.011464093811810017,
0.03337186947464943,
0.06601637601852417,
-0.06089409068226814,
0.069978728890419,
0.013848673552274704,
0.01032294612377882,
0.02266133576631546,
0.044782187789678574,
0.04557523876428604,
-0.003385057905688882,
0.03247146... |
https://github.com/scikit-learn/scikit-learn/issues/29000 | [
"Bug"
] | KFold(n_samples=n) not equivalent to LeaveOneOut() cv in CalibratedClassifierCV()
### Describe the bug
Calling `CalibratedClassifierCV()` with `cv=KFold(n_samples=n)` (where n is the number of samples) can give different results than using `cv=LeaveOneOut()`, but the docs for `LeaveOneOut()` say these should be equ... | 29,000 | [
-0.01941857859492302,
-0.08439432084560394,
0.008541448973119259,
0.01435158122330904,
0.0403575599193573,
-0.014815397560596466,
0.0789540633559227,
0.003297176444903016,
0.011609920300543308,
0.002429279265925288,
0.06789106130599976,
0.04617781564593315,
0.030406204983592033,
0.02852617... |
https://github.com/scikit-learn/scikit-learn/issues/29000 | [
"Bug"
] | KFold(n_samples=n) not equivalent to LeaveOneOut() cv in CalibratedClassifierCV()
### Describe the bug
Calling `CalibratedClassifierCV()` with `cv=KFold(n_samples=n)` (where n is the number of samples) can give different results than using `cv=LeaveOneOut()`, but the docs for `LeaveOneOut()` say these should be equ... | 29,000 | [
-0.01941857859492302,
-0.08439432084560394,
0.008541448973119259,
0.01435158122330904,
0.0403575599193573,
-0.014815397560596466,
0.0789540633559227,
0.003297176444903016,
0.011609920300543308,
0.002429279265925288,
0.06789106130599976,
0.04617781564593315,
0.030406204983592033,
0.02852617... |
https://github.com/scikit-learn/scikit-learn/issues/29000 | [
"Bug"
] | KFold(n_samples=n) not equivalent to LeaveOneOut() cv in CalibratedClassifierCV()
### Describe the bug
Calling `CalibratedClassifierCV()` with `cv=KFold(n_samples=n)` (where n is the number of samples) can give different results than using `cv=LeaveOneOut()`, but the docs for `LeaveOneOut()` say these should be equ... | 29,000 | [
-0.01941857859492302,
-0.08439432084560394,
0.008541448973119259,
0.01435158122330904,
0.0403575599193573,
-0.014815397560596466,
0.0789540633559227,
0.003297176444903016,
0.011609920300543308,
0.002429279265925288,
0.06789106130599976,
0.04617781564593315,
0.030406204983592033,
0.02852617... |
https://github.com/scikit-learn/scikit-learn/issues/29000 | [
"Bug"
] | KFold(n_samples=n) not equivalent to LeaveOneOut() cv in CalibratedClassifierCV()
### Describe the bug
Calling `CalibratedClassifierCV()` with `cv=KFold(n_samples=n)` (where n is the number of samples) can give different results than using `cv=LeaveOneOut()`, but the docs for `LeaveOneOut()` say these should be equ... | 29,000 | [
-0.01941857859492302,
-0.08439432084560394,
0.008541448973119259,
0.01435158122330904,
0.0403575599193573,
-0.014815397560596466,
0.0789540633559227,
0.003297176444903016,
0.011609920300543308,
0.002429279265925288,
0.06789106130599976,
0.04617781564593315,
0.030406204983592033,
0.02852617... |
https://github.com/scikit-learn/scikit-learn/issues/29000 | [
"Bug"
] | KFold(n_samples=n) not equivalent to LeaveOneOut() cv in CalibratedClassifierCV()
### Describe the bug
Calling `CalibratedClassifierCV()` with `cv=KFold(n_samples=n)` (where n is the number of samples) can give different results than using `cv=LeaveOneOut()`, but the docs for `LeaveOneOut()` say these should be equ... | 29,000 | [
-0.01941857859492302,
-0.08439432084560394,
0.008541448973119259,
0.01435158122330904,
0.0403575599193573,
-0.014815397560596466,
0.0789540633559227,
0.003297176444903016,
0.011609920300543308,
0.002429279265925288,
0.06789106130599976,
0.04617781564593315,
0.030406204983592033,
0.02852617... |
https://github.com/scikit-learn/scikit-learn/issues/29000 | [
"Bug"
] | KFold(n_samples=n) not equivalent to LeaveOneOut() cv in CalibratedClassifierCV()
### Describe the bug
Calling `CalibratedClassifierCV()` with `cv=KFold(n_samples=n)` (where n is the number of samples) can give different results than using `cv=LeaveOneOut()`, but the docs for `LeaveOneOut()` say these should be equ... | 29,000 | [
-0.01941857859492302,
-0.08439432084560394,
0.008541448973119259,
0.01435158122330904,
0.0403575599193573,
-0.014815397560596466,
0.0789540633559227,
0.003297176444903016,
0.011609920300543308,
0.002429279265925288,
0.06789106130599976,
0.04617781564593315,
0.030406204983592033,
0.02852617... |
https://github.com/scikit-learn/scikit-learn/issues/29000 | [
"Bug"
] | KFold(n_samples=n) not equivalent to LeaveOneOut() cv in CalibratedClassifierCV()
### Describe the bug
Calling `CalibratedClassifierCV()` with `cv=KFold(n_samples=n)` (where n is the number of samples) can give different results than using `cv=LeaveOneOut()`, but the docs for `LeaveOneOut()` say these should be equ... | 29,000 | [
-0.01941857859492302,
-0.08439432084560394,
0.008541448973119259,
0.01435158122330904,
0.0403575599193573,
-0.014815397560596466,
0.0789540633559227,
0.003297176444903016,
0.011609920300543308,
0.002429279265925288,
0.06789106130599976,
0.04617781564593315,
0.030406204983592033,
0.02852617... |
https://github.com/scikit-learn/scikit-learn/issues/29000 | [
"Bug"
] | KFold(n_samples=n) not equivalent to LeaveOneOut() cv in CalibratedClassifierCV()
### Describe the bug
Calling `CalibratedClassifierCV()` with `cv=KFold(n_samples=n)` (where n is the number of samples) can give different results than using `cv=LeaveOneOut()`, but the docs for `LeaveOneOut()` say these should be equ... | 29,000 | [
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0.02852617... |
https://github.com/scikit-learn/scikit-learn/issues/29000 | [
"Bug"
] | KFold(n_samples=n) not equivalent to LeaveOneOut() cv in CalibratedClassifierCV()
### Describe the bug
Calling `CalibratedClassifierCV()` with `cv=KFold(n_samples=n)` (where n is the number of samples) can give different results than using `cv=LeaveOneOut()`, but the docs for `LeaveOneOut()` say these should be equ... | 29,000 | [
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0.030406204983592033,
0.02852617... |
https://github.com/scikit-learn/scikit-learn/issues/29000 | [
"Bug"
] | KFold(n_samples=n) not equivalent to LeaveOneOut() cv in CalibratedClassifierCV()
### Describe the bug
Calling `CalibratedClassifierCV()` with `cv=KFold(n_samples=n)` (where n is the number of samples) can give different results than using `cv=LeaveOneOut()`, but the docs for `LeaveOneOut()` say these should be equ... | 29,000 | [
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0.04617781564593315,
0.030406204983592033,
0.02852617... |
https://github.com/scikit-learn/scikit-learn/issues/28996 | [
"New Feature",
"Needs Decision - Include Feature"
] | Enhancement: Add Summary Output for Linear Regression Models
### Describe the workflow you want to enable
While scikit-learn excels in predictive modeling, users often need detailed statistical summaries to interpret their regression results.
I propose we develop options for users wanting comprehensive statistical... | 28,996 | [
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0... |
https://github.com/scikit-learn/scikit-learn/issues/28996 | [
"New Feature",
"Needs Decision - Include Feature"
] | Enhancement: Add Summary Output for Linear Regression Models
### Describe the workflow you want to enable
While scikit-learn excels in predictive modeling, users often need detailed statistical summaries to interpret their regression results.
I propose we develop options for users wanting comprehensive statistical... | 28,996 | [
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0.05430573597550392,
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0.11158... |
https://github.com/scikit-learn/scikit-learn/issues/28996 | [
"New Feature",
"Needs Decision - Include Feature"
] | Enhancement: Add Summary Output for Linear Regression Models
### Describe the workflow you want to enable
While scikit-learn excels in predictive modeling, users often need detailed statistical summaries to interpret their regression results.
I propose we develop options for users wanting comprehensive statistical... | 28,996 | [
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0.055956851691007614,
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0.1262... |
https://github.com/scikit-learn/scikit-learn/issues/28995 | [
"New Feature",
"API",
"Needs Decision",
"RFC",
"module:metrics"
] | Add "scoring" argument to estimator's ``score`` method
### Describe the workflow you want to enable
I want to enable non-accuracy metrics to ``estimator.score``, and ultimately deprecate the default values of ``accuracy`` and ``r2``. I would call it ``scoring`` though it's a bit redundant but consistent.
That woul... | 28,995 | [
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https://github.com/scikit-learn/scikit-learn/issues/28995 | [
"New Feature",
"API",
"Needs Decision",
"RFC",
"module:metrics"
] | Add "scoring" argument to estimator's ``score`` method
### Describe the workflow you want to enable
I want to enable non-accuracy metrics to ``estimator.score``, and ultimately deprecate the default values of ``accuracy`` and ``r2``. I would call it ``scoring`` though it's a bit redundant but consistent.
That woul... | 28,995 | [
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0.093093... |
https://github.com/scikit-learn/scikit-learn/issues/28995 | [
"New Feature",
"API",
"Needs Decision",
"RFC",
"module:metrics"
] | Add "scoring" argument to estimator's ``score`` method
### Describe the workflow you want to enable
I want to enable non-accuracy metrics to ``estimator.score``, and ultimately deprecate the default values of ``accuracy`` and ``r2``. I would call it ``scoring`` though it's a bit redundant but consistent.
That woul... | 28,995 | [
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https://github.com/scikit-learn/scikit-learn/issues/28995 | [
"New Feature",
"API",
"Needs Decision",
"RFC",
"module:metrics"
] | Add "scoring" argument to estimator's ``score`` method
### Describe the workflow you want to enable
I want to enable non-accuracy metrics to ``estimator.score``, and ultimately deprecate the default values of ``accuracy`` and ``r2``. I would call it ``scoring`` though it's a bit redundant but consistent.
That woul... | 28,995 | [
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https://github.com/scikit-learn/scikit-learn/issues/28995 | [
"New Feature",
"API",
"Needs Decision",
"RFC",
"module:metrics"
] | Add "scoring" argument to estimator's ``score`` method
### Describe the workflow you want to enable
I want to enable non-accuracy metrics to ``estimator.score``, and ultimately deprecate the default values of ``accuracy`` and ``r2``. I would call it ``scoring`` though it's a bit redundant but consistent.
That woul... | 28,995 | [
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https://github.com/scikit-learn/scikit-learn/issues/28995 | [
"New Feature",
"API",
"Needs Decision",
"RFC",
"module:metrics"
] | Add "scoring" argument to estimator's ``score`` method
### Describe the workflow you want to enable
I want to enable non-accuracy metrics to ``estimator.score``, and ultimately deprecate the default values of ``accuracy`` and ``r2``. I would call it ``scoring`` though it's a bit redundant but consistent.
That woul... | 28,995 | [
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https://github.com/scikit-learn/scikit-learn/issues/28995 | [
"New Feature",
"API",
"Needs Decision",
"RFC",
"module:metrics"
] | Add "scoring" argument to estimator's ``score`` method
### Describe the workflow you want to enable
I want to enable non-accuracy metrics to ``estimator.score``, and ultimately deprecate the default values of ``accuracy`` and ``r2``. I would call it ``scoring`` though it's a bit redundant but consistent.
That woul... | 28,995 | [
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0.0... |
https://github.com/scikit-learn/scikit-learn/issues/28995 | [
"New Feature",
"API",
"Needs Decision",
"RFC",
"module:metrics"
] | Add "scoring" argument to estimator's ``score`` method
### Describe the workflow you want to enable
I want to enable non-accuracy metrics to ``estimator.score``, and ultimately deprecate the default values of ``accuracy`` and ``r2``. I would call it ``scoring`` though it's a bit redundant but consistent.
That woul... | 28,995 | [
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https://github.com/scikit-learn/scikit-learn/issues/28995 | [
"New Feature",
"API",
"Needs Decision",
"RFC",
"module:metrics"
] | Add "scoring" argument to estimator's ``score`` method
### Describe the workflow you want to enable
I want to enable non-accuracy metrics to ``estimator.score``, and ultimately deprecate the default values of ``accuracy`` and ``r2``. I would call it ``scoring`` though it's a bit redundant but consistent.
That woul... | 28,995 | [
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0.0833... |
https://github.com/scikit-learn/scikit-learn/issues/28995 | [
"New Feature",
"API",
"Needs Decision",
"RFC",
"module:metrics"
] | Add "scoring" argument to estimator's ``score`` method
### Describe the workflow you want to enable
I want to enable non-accuracy metrics to ``estimator.score``, and ultimately deprecate the default values of ``accuracy`` and ``r2``. I would call it ``scoring`` though it's a bit redundant but consistent.
That woul... | 28,995 | [
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https://github.com/scikit-learn/scikit-learn/issues/28995 | [
"New Feature",
"API",
"Needs Decision",
"RFC",
"module:metrics"
] | Add "scoring" argument to estimator's ``score`` method
### Describe the workflow you want to enable
I want to enable non-accuracy metrics to ``estimator.score``, and ultimately deprecate the default values of ``accuracy`` and ``r2``. I would call it ``scoring`` though it's a bit redundant but consistent.
That woul... | 28,995 | [
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https://github.com/scikit-learn/scikit-learn/issues/28995 | [
"New Feature",
"API",
"Needs Decision",
"RFC",
"module:metrics"
] | Add "scoring" argument to estimator's ``score`` method
### Describe the workflow you want to enable
I want to enable non-accuracy metrics to ``estimator.score``, and ultimately deprecate the default values of ``accuracy`` and ``r2``. I would call it ``scoring`` though it's a bit redundant but consistent.
That woul... | 28,995 | [
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0.09... |
https://github.com/scikit-learn/scikit-learn/issues/28995 | [
"New Feature",
"API",
"Needs Decision",
"RFC",
"module:metrics"
] | Add "scoring" argument to estimator's ``score`` method
### Describe the workflow you want to enable
I want to enable non-accuracy metrics to ``estimator.score``, and ultimately deprecate the default values of ``accuracy`` and ``r2``. I would call it ``scoring`` though it's a bit redundant but consistent.
That woul... | 28,995 | [
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0.0930... |
https://github.com/scikit-learn/scikit-learn/issues/28995 | [
"New Feature",
"API",
"Needs Decision",
"RFC",
"module:metrics"
] | Add "scoring" argument to estimator's ``score`` method
### Describe the workflow you want to enable
I want to enable non-accuracy metrics to ``estimator.score``, and ultimately deprecate the default values of ``accuracy`` and ``r2``. I would call it ``scoring`` though it's a bit redundant but consistent.
That woul... | 28,995 | [
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https://github.com/scikit-learn/scikit-learn/issues/28995 | [
"New Feature",
"API",
"Needs Decision",
"RFC",
"module:metrics"
] | Add "scoring" argument to estimator's ``score`` method
### Describe the workflow you want to enable
I want to enable non-accuracy metrics to ``estimator.score``, and ultimately deprecate the default values of ``accuracy`` and ``r2``. I would call it ``scoring`` though it's a bit redundant but consistent.
That woul... | 28,995 | [
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