html_url stringlengths 57 57 | labels listlengths 1 6 | text stringlengths 32 258k | issue_number int64 22.4k 33k | embedding listlengths 768 768 |
|---|---|---|---|---|
https://github.com/scikit-learn/scikit-learn/issues/32312 | [
"Bug"
] | Error handling pandas missing values in SimpleImputer
### Describe the bug
I recently installed the stable release of scikit-learn v1.7.2, and noticed that when passing missing_values=pd.NA to the SimpleImputer object, it throws the following error when trying to inspect the object:
TypeError: boolean value of NA is... | 32,312 | [
0.009656786918640137,
0.032174002379179,
0.0023760811891406775,
-0.06883271038532257,
0.054908160120248795,
-0.0022459302563220263,
0.0640801265835762,
0.025707418099045753,
0.010396385565400124,
-0.000028102438591304235,
0.02527552656829357,
0.01458690594881773,
0.037879277020692825,
0.01... |
https://github.com/scikit-learn/scikit-learn/issues/32312 | [
"Bug"
] | Error handling pandas missing values in SimpleImputer
### Describe the bug
I recently installed the stable release of scikit-learn v1.7.2, and noticed that when passing missing_values=pd.NA to the SimpleImputer object, it throws the following error when trying to inspect the object:
TypeError: boolean value of NA is... | 32,312 | [
0.009656786918640137,
0.032174002379179,
0.0023760811891406775,
-0.06883271038532257,
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-0.0022459302563220263,
0.0640801265835762,
0.025707418099045753,
0.010396385565400124,
-0.000028102438591304235,
0.02527552656829357,
0.01458690594881773,
0.037879277020692825,
0.01... |
https://github.com/scikit-learn/scikit-learn/issues/32312 | [
"Bug"
] | Error handling pandas missing values in SimpleImputer
### Describe the bug
I recently installed the stable release of scikit-learn v1.7.2, and noticed that when passing missing_values=pd.NA to the SimpleImputer object, it throws the following error when trying to inspect the object:
TypeError: boolean value of NA is... | 32,312 | [
0.009656786918640137,
0.032174002379179,
0.0023760811891406775,
-0.06883271038532257,
0.054908160120248795,
-0.0022459302563220263,
0.0640801265835762,
0.025707418099045753,
0.010396385565400124,
-0.000028102438591304235,
0.02527552656829357,
0.01458690594881773,
0.037879277020692825,
0.01... |
https://github.com/scikit-learn/scikit-learn/issues/32312 | [
"Bug"
] | Error handling pandas missing values in SimpleImputer
### Describe the bug
I recently installed the stable release of scikit-learn v1.7.2, and noticed that when passing missing_values=pd.NA to the SimpleImputer object, it throws the following error when trying to inspect the object:
TypeError: boolean value of NA is... | 32,312 | [
0.009656786918640137,
0.032174002379179,
0.0023760811891406775,
-0.06883271038532257,
0.054908160120248795,
-0.0022459302563220263,
0.0640801265835762,
0.025707418099045753,
0.010396385565400124,
-0.000028102438591304235,
0.02527552656829357,
0.01458690594881773,
0.037879277020692825,
0.01... |
https://github.com/scikit-learn/scikit-learn/issues/32312 | [
"Bug"
] | Error handling pandas missing values in SimpleImputer
### Describe the bug
I recently installed the stable release of scikit-learn v1.7.2, and noticed that when passing missing_values=pd.NA to the SimpleImputer object, it throws the following error when trying to inspect the object:
TypeError: boolean value of NA is... | 32,312 | [
0.009656786918640137,
0.032174002379179,
0.0023760811891406775,
-0.06883271038532257,
0.054908160120248795,
-0.0022459302563220263,
0.0640801265835762,
0.025707418099045753,
0.010396385565400124,
-0.000028102438591304235,
0.02527552656829357,
0.01458690594881773,
0.037879277020692825,
0.01... |
https://github.com/scikit-learn/scikit-learn/issues/32312 | [
"Bug"
] | Error handling pandas missing values in SimpleImputer
### Describe the bug
I recently installed the stable release of scikit-learn v1.7.2, and noticed that when passing missing_values=pd.NA to the SimpleImputer object, it throws the following error when trying to inspect the object:
TypeError: boolean value of NA is... | 32,312 | [
0.009656786918640137,
0.032174002379179,
0.0023760811891406775,
-0.06883271038532257,
0.054908160120248795,
-0.0022459302563220263,
0.0640801265835762,
0.025707418099045753,
0.010396385565400124,
-0.000028102438591304235,
0.02527552656829357,
0.01458690594881773,
0.037879277020692825,
0.01... |
https://github.com/scikit-learn/scikit-learn/issues/32312 | [
"Bug"
] | Error handling pandas missing values in SimpleImputer
### Describe the bug
I recently installed the stable release of scikit-learn v1.7.2, and noticed that when passing missing_values=pd.NA to the SimpleImputer object, it throws the following error when trying to inspect the object:
TypeError: boolean value of NA is... | 32,312 | [
0.009656786918640137,
0.032174002379179,
0.0023760811891406775,
-0.06883271038532257,
0.054908160120248795,
-0.0022459302563220263,
0.0640801265835762,
0.025707418099045753,
0.010396385565400124,
-0.000028102438591304235,
0.02527552656829357,
0.01458690594881773,
0.037879277020692825,
0.01... |
https://github.com/scikit-learn/scikit-learn/issues/32306 | [
"Needs Triage"
] | Test issue
bla
COMMENT:
Oops I thought I was testing something on my fork 😅. | 32,306 | [
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0... |
https://github.com/scikit-learn/scikit-learn/issues/32303 | [
"Needs Triage"
] | ⚠️ CI failed on Wheel builder (last failure: Sep 30, 2025) ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/18118103579)** (Sep 30, 2025)
COMMENT:
This was the last build with the hang in the macOS wheel. This should be fixed by #32273, we will see that this mornin... | 32,303 | [
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0.0112... |
https://github.com/scikit-learn/scikit-learn/issues/32303 | [
"Needs Triage"
] | ⚠️ CI failed on Wheel builder (last failure: Sep 30, 2025) ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/18118103579)** (Sep 30, 2025)
COMMENT:
## CI is no longer failing! ✅
[Successful run](https://github.com/scikit-learn/scikit-learn/actions/runs/18150741800)... | 32,303 | [
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0.08... |
https://github.com/scikit-learn/scikit-learn/issues/32294 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_Runs.pylatest_conda_forge_mkl (last failure: Sep 29, 2025) ⚠️
**CI failed on [Linux_Runs.pylatest_conda_forge_mkl](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=80512&view=logs&j=dde5042c-7464-5d47-9507-31bdd2ee0a3a)** (Sep 29, 2025)
- test_fit_transform[98]
COMMENT:
rel... | 32,294 | [
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0.01664438471198082,
0.0985... |
https://github.com/scikit-learn/scikit-learn/issues/32294 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_Runs.pylatest_conda_forge_mkl (last failure: Sep 29, 2025) ⚠️
**CI failed on [Linux_Runs.pylatest_conda_forge_mkl](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=80512&view=logs&j=dde5042c-7464-5d47-9507-31bdd2ee0a3a)** (Sep 29, 2025)
- test_fit_transform[98]
COMMENT:
## ... | 32,294 | [
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https://github.com/scikit-learn/scikit-learn/issues/32292 | [
"Bug",
"Needs Triage"
] | scikit-learn crash silently on Window11 with conda
### Describe the bug
I run my program but it silently crashed.
I think it's a problem that scikit-learn is incompatible with numpy or scipy in some place.
I will show the environment ,the code and the output. Here is a minimal reproducible example.
In this example，I ... | 32,292 | [
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0.05575614422559738,
0.0003985974472016096,
0.040... |
https://github.com/scikit-learn/scikit-learn/issues/32289 | [
"Documentation"
] | DOC: specify behavior of `_weighted_percentile` with `average=True`
### Describe the bug
When using `sklearn.utils.stats._weighted_percentile(..., average=True)` with floating-point weights and such that the "average code path" is expected to be taken (i.e. [those lines](https://github.com/scikit-learn/scikit-learn/b... | 32,289 | [
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0.014447110705077648,
0.014016675762832165,
0.050825007259845734,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32289 | [
"Documentation"
] | DOC: specify behavior of `_weighted_percentile` with `average=True`
### Describe the bug
When using `sklearn.utils.stats._weighted_percentile(..., average=True)` with floating-point weights and such that the "average code path" is expected to be taken (i.e. [those lines](https://github.com/scikit-learn/scikit-learn/b... | 32,289 | [
0.00578284403309226,
0.009070029482245445,
0.024166500195860863,
0.00750912819057703,
0.08080977201461792,
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-0.01936463452875614,
0.014447110705077648,
0.014016675762832165,
0.050825007259845734,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32289 | [
"Documentation"
] | DOC: specify behavior of `_weighted_percentile` with `average=True`
### Describe the bug
When using `sklearn.utils.stats._weighted_percentile(..., average=True)` with floating-point weights and such that the "average code path" is expected to be taken (i.e. [those lines](https://github.com/scikit-learn/scikit-learn/b... | 32,289 | [
0.00578284403309226,
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0.024166500195860863,
0.00750912819057703,
0.08080977201461792,
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-0.00997181050479412,
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0.014447110705077648,
0.014016675762832165,
0.050825007259845734,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32289 | [
"Documentation"
] | DOC: specify behavior of `_weighted_percentile` with `average=True`
### Describe the bug
When using `sklearn.utils.stats._weighted_percentile(..., average=True)` with floating-point weights and such that the "average code path" is expected to be taken (i.e. [those lines](https://github.com/scikit-learn/scikit-learn/b... | 32,289 | [
0.00578284403309226,
0.009070029482245445,
0.024166500195860863,
0.00750912819057703,
0.08080977201461792,
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-0.01936463452875614,
0.014447110705077648,
0.014016675762832165,
0.050825007259845734,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32289 | [
"Documentation"
] | DOC: specify behavior of `_weighted_percentile` with `average=True`
### Describe the bug
When using `sklearn.utils.stats._weighted_percentile(..., average=True)` with floating-point weights and such that the "average code path" is expected to be taken (i.e. [those lines](https://github.com/scikit-learn/scikit-learn/b... | 32,289 | [
0.00578284403309226,
0.009070029482245445,
0.024166500195860863,
0.00750912819057703,
0.08080977201461792,
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-0.00997181050479412,
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-0.01936463452875614,
0.014447110705077648,
0.014016675762832165,
0.050825007259845734,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32289 | [
"Documentation"
] | DOC: specify behavior of `_weighted_percentile` with `average=True`
### Describe the bug
When using `sklearn.utils.stats._weighted_percentile(..., average=True)` with floating-point weights and such that the "average code path" is expected to be taken (i.e. [those lines](https://github.com/scikit-learn/scikit-learn/b... | 32,289 | [
0.00578284403309226,
0.009070029482245445,
0.024166500195860863,
0.00750912819057703,
0.08080977201461792,
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0.014447110705077648,
0.014016675762832165,
0.050825007259845734,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32289 | [
"Documentation"
] | DOC: specify behavior of `_weighted_percentile` with `average=True`
### Describe the bug
When using `sklearn.utils.stats._weighted_percentile(..., average=True)` with floating-point weights and such that the "average code path" is expected to be taken (i.e. [those lines](https://github.com/scikit-learn/scikit-learn/b... | 32,289 | [
0.00578284403309226,
0.009070029482245445,
0.024166500195860863,
0.00750912819057703,
0.08080977201461792,
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-0.00997181050479412,
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-0.01936463452875614,
0.014447110705077648,
0.014016675762832165,
0.050825007259845734,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32289 | [
"Documentation"
] | DOC: specify behavior of `_weighted_percentile` with `average=True`
### Describe the bug
When using `sklearn.utils.stats._weighted_percentile(..., average=True)` with floating-point weights and such that the "average code path" is expected to be taken (i.e. [those lines](https://github.com/scikit-learn/scikit-learn/b... | 32,289 | [
0.00578284403309226,
0.009070029482245445,
0.024166500195860863,
0.00750912819057703,
0.08080977201461792,
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-0.00997181050479412,
-0.010879362933337688,
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-0.01936463452875614,
0.014447110705077648,
0.014016675762832165,
0.050825007259845734,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32289 | [
"Documentation"
] | DOC: specify behavior of `_weighted_percentile` with `average=True`
### Describe the bug
When using `sklearn.utils.stats._weighted_percentile(..., average=True)` with floating-point weights and such that the "average code path" is expected to be taken (i.e. [those lines](https://github.com/scikit-learn/scikit-learn/b... | 32,289 | [
0.00578284403309226,
0.009070029482245445,
0.024166500195860863,
0.00750912819057703,
0.08080977201461792,
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-0.00997181050479412,
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-0.01936463452875614,
0.014447110705077648,
0.014016675762832165,
0.050825007259845734,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32289 | [
"Documentation"
] | DOC: specify behavior of `_weighted_percentile` with `average=True`
### Describe the bug
When using `sklearn.utils.stats._weighted_percentile(..., average=True)` with floating-point weights and such that the "average code path" is expected to be taken (i.e. [those lines](https://github.com/scikit-learn/scikit-learn/b... | 32,289 | [
0.00578284403309226,
0.009070029482245445,
0.024166500195860863,
0.00750912819057703,
0.08080977201461792,
-0.013118317350745201,
-0.00997181050479412,
-0.010879362933337688,
-0.007536009419709444,
-0.01936463452875614,
0.014447110705077648,
0.014016675762832165,
0.050825007259845734,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32284 | [
"Bug",
"Needs Triage"
] | BUG: Decision trees: Incorrect/missing handling of missing values in `tree.decision_path(X)`
### Describe the bug
NaNs handling is missing from the function `tree.decision_path`, hence NaNs may end up in the incorrect path (i.e. `tree.decision_path` returns incorrect ouput).
See PR https://github.com/scikit-learn/sc... | 32,284 | [
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0.03520064055919647,
-... |
https://github.com/scikit-learn/scikit-learn/issues/32284 | [
"Bug",
"Needs Triage"
] | BUG: Decision trees: Incorrect/missing handling of missing values in `tree.decision_path(X)`
### Describe the bug
NaNs handling is missing from the function `tree.decision_path`, hence NaNs may end up in the incorrect path (i.e. `tree.decision_path` returns incorrect ouput).
See PR https://github.com/scikit-learn/sc... | 32,284 | [
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0.06577439606189728,
0.03520064055919647,
-... |
https://github.com/scikit-learn/scikit-learn/issues/32283 | [
"Bug",
"Performance"
] | PERF: `np_compat` sort/argsort much slower than `np`
#### EDIT: It's because `np_compat` uses stable sort by default, while numpy doesn't
### Describe the bug
By `np_compat` I mean: `from sklearn.externals.array_api_compat import numpy as np_compat`, which is the numpy used for instance in `sklearn.utils.stats._weig... | 32,283 | [
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https://github.com/scikit-learn/scikit-learn/issues/32283 | [
"Bug",
"Performance"
] | PERF: `np_compat` sort/argsort much slower than `np`
#### EDIT: It's because `np_compat` uses stable sort by default, while numpy doesn't
### Describe the bug
By `np_compat` I mean: `from sklearn.externals.array_api_compat import numpy as np_compat`, which is the numpy used for instance in `sklearn.utils.stats._weig... | 32,283 | [
0.0031463897321373224,
0.05298870801925659,
0.01918865740299225,
0.0033978086430579424,
0.03871722146868706,
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-0.00551843224093318,
0.0397535003721714,
0.01631135307252407,
-0.03624811768531799,
-0.0067324768751859665,
0.06599533557891846,
0.017492499202489853,
-0.064... |
https://github.com/scikit-learn/scikit-learn/issues/32283 | [
"Bug",
"Performance"
] | PERF: `np_compat` sort/argsort much slower than `np`
#### EDIT: It's because `np_compat` uses stable sort by default, while numpy doesn't
### Describe the bug
By `np_compat` I mean: `from sklearn.externals.array_api_compat import numpy as np_compat`, which is the numpy used for instance in `sklearn.utils.stats._weig... | 32,283 | [
0.0031463897321373224,
0.05298870801925659,
0.01918865740299225,
0.0033978086430579424,
0.03871722146868706,
0.0026722268667072058,
-0.00551843224093318,
0.0397535003721714,
0.01631135307252407,
-0.03624811768531799,
-0.0067324768751859665,
0.06599533557891846,
0.017492499202489853,
-0.064... |
https://github.com/scikit-learn/scikit-learn/issues/32283 | [
"Bug",
"Performance"
] | PERF: `np_compat` sort/argsort much slower than `np`
#### EDIT: It's because `np_compat` uses stable sort by default, while numpy doesn't
### Describe the bug
By `np_compat` I mean: `from sklearn.externals.array_api_compat import numpy as np_compat`, which is the numpy used for instance in `sklearn.utils.stats._weig... | 32,283 | [
0.0031463897321373224,
0.05298870801925659,
0.01918865740299225,
0.0033978086430579424,
0.03871722146868706,
0.0026722268667072058,
-0.00551843224093318,
0.0397535003721714,
0.01631135307252407,
-0.03624811768531799,
-0.0067324768751859665,
0.06599533557891846,
0.017492499202489853,
-0.064... |
https://github.com/scikit-learn/scikit-learn/issues/32279 | [
"Bug",
"Build / CI"
] | Wheels CI hang with macOS x86_64 (aka Intel) with scipy 1.16.2
### Describe the bug
Noticed in https://github.com/scikit-learn/scikit-learn/issues/32171.
Work-around with `scipy<1.16.2` in https://github.com/scikit-learn/scikit-learn/pull/32273.
As noted in https://github.com/scikit-learn/scikit-learn/issues/32171#... | 32,279 | [
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0.002736672293394804,
0.00... |
https://github.com/scikit-learn/scikit-learn/issues/32279 | [
"Bug",
"Build / CI"
] | Wheels CI hang with macOS x86_64 (aka Intel) with scipy 1.16.2
### Describe the bug
Noticed in https://github.com/scikit-learn/scikit-learn/issues/32171.
Work-around with `scipy<1.16.2` in https://github.com/scikit-learn/scikit-learn/pull/32273.
As noted in https://github.com/scikit-learn/scikit-learn/issues/32171#... | 32,279 | [
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... |
https://github.com/scikit-learn/scikit-learn/issues/32279 | [
"Bug",
"Build / CI"
] | Wheels CI hang with macOS x86_64 (aka Intel) with scipy 1.16.2
### Describe the bug
Noticed in https://github.com/scikit-learn/scikit-learn/issues/32171.
Work-around with `scipy<1.16.2` in https://github.com/scikit-learn/scikit-learn/pull/32273.
As noted in https://github.com/scikit-learn/scikit-learn/issues/32171#... | 32,279 | [
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0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32278 | [
"Array API"
] | MNT Redundant `xp` argument in` _average`
The [<code>_average</code>](https://github.com/scikit-learn/scikit-learn/blob/4fd34545e517d164881126ce539aa8bfabae86d2/sklearn/utils/_array_api.py#L621) function accepts a namespace variable `xp` as input. However, even when a non-None `xp` is provided, the function still call... | 32,278 | [
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0.05838305503129959,
-0.00446... |
https://github.com/scikit-learn/scikit-learn/issues/32276 | [
"Bug",
"Needs Triage"
] | Fix the pip name
### Describe the bug
Please have consistent naming for the pip install command and the actual module code. I should not have to look up how to install sklearn every time I want to use it cause it has a weird pip install command.
### Steps/Code to Reproduce
import sklearn
### Expected Results
I ... | 32,276 | [
0.05310817435383797,
-0.03586188331246376,
-0.008572443388402462,
-0.04478581249713898,
0.06083066016435623,
0.037164106965065,
0.02582685835659504,
-0.00969963800162077,
0.05891221761703491,
0.00977807305753231,
0.03699742630124092,
0.11869139969348907,
0.013989003375172615,
0.03314888849... |
https://github.com/scikit-learn/scikit-learn/issues/32272 | [
"Bug"
] | Decision/Extra trees & missing values: split ignored when NaNs + single unique value in feature
### Describe the bug
When feature values consist of only NaNs and another value, the feature is considered as constant by this if:
```Cython
if (
# All values for this feature are missing, or
... | 32,272 | [
0.007996754720807076,
-0.029921788722276688,
0.011506113223731518,
0.00033704566885717213,
0.05127838999032974,
-0.04095982760190964,
-0.004014615435153246,
-0.011409646831452847,
-0.042503125965595245,
-0.04206379875540733,
0.06324101984500885,
0.0004314121906645596,
0.016420001164078712,
... |
https://github.com/scikit-learn/scikit-learn/issues/32272 | [
"Bug"
] | Decision/Extra trees & missing values: split ignored when NaNs + single unique value in feature
### Describe the bug
When feature values consist of only NaNs and another value, the feature is considered as constant by this if:
```Cython
if (
# All values for this feature are missing, or
... | 32,272 | [
0.007996754720807076,
-0.029921788722276688,
0.011506113223731518,
0.00033704566885717213,
0.05127838999032974,
-0.04095982760190964,
-0.004014615435153246,
-0.011409646831452847,
-0.042503125965595245,
-0.04206379875540733,
0.06324101984500885,
0.0004314121906645596,
0.016420001164078712,
... |
https://github.com/scikit-learn/scikit-learn/issues/32272 | [
"Bug"
] | Decision/Extra trees & missing values: split ignored when NaNs + single unique value in feature
### Describe the bug
When feature values consist of only NaNs and another value, the feature is considered as constant by this if:
```Cython
if (
# All values for this feature are missing, or
... | 32,272 | [
0.007996754720807076,
-0.029921788722276688,
0.011506113223731518,
0.00033704566885717213,
0.05127838999032974,
-0.04095982760190964,
-0.004014615435153246,
-0.011409646831452847,
-0.042503125965595245,
-0.04206379875540733,
0.06324101984500885,
0.0004314121906645596,
0.016420001164078712,
... |
https://github.com/scikit-learn/scikit-learn/issues/32272 | [
"Bug"
] | Decision/Extra trees & missing values: split ignored when NaNs + single unique value in feature
### Describe the bug
When feature values consist of only NaNs and another value, the feature is considered as constant by this if:
```Cython
if (
# All values for this feature are missing, or
... | 32,272 | [
0.007996754720807076,
-0.029921788722276688,
0.011506113223731518,
0.00033704566885717213,
0.05127838999032974,
-0.04095982760190964,
-0.004014615435153246,
-0.011409646831452847,
-0.042503125965595245,
-0.04206379875540733,
0.06324101984500885,
0.0004314121906645596,
0.016420001164078712,
... |
https://github.com/scikit-learn/scikit-learn/issues/32269 | [
"Needs Triage"
] | ⚠️ CI failed on macOS.pylatest_conda_forge_mkl (last failure: Sep 25, 2025) ⚠️
**CI failed on [macOS.pylatest_conda_forge_mkl](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=80351&view=logs&j=97641769-79fb-5590-9088-a30ce9b850b9)** (Sep 25, 2025)
Unable to find junit file. Please see link for d... | 32,269 | [
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0.0070180403999984264,
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0.05035626143217087,
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0.... |
https://github.com/scikit-learn/scikit-learn/issues/32263 | [
"Documentation",
"RFC"
] | marimo for WASM notebooks
### Describe the issue linked to the documentation
I couldn't help but notice that the docs have Jupyter lite and binder. The binder links seem to fail at the moment and while the Jupyterlite seems to run ok ... would folks maybe be open to marimo notebooks for this as an alternative?
<img... | 32,263 | [
-0.012032847851514816,
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0.007295797113329172,
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0.0898522213101387,
0.11504051089286804,
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0.051755182445049286,
-0.03180110454559326,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/32263 | [
"Documentation",
"RFC"
] | marimo for WASM notebooks
### Describe the issue linked to the documentation
I couldn't help but notice that the docs have Jupyter lite and binder. The binder links seem to fail at the moment and while the Jupyterlite seems to run ok ... would folks maybe be open to marimo notebooks for this as an alternative?
<img... | 32,263 | [
0.028403183445334435,
0.0030803410336375237,
0.00740445451810956,
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0.005668277386575937,
0.07270203530788422,
0.11720402538776398,
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0.054197799414396286,
-0.027166519314050674,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/32263 | [
"Documentation",
"RFC"
] | marimo for WASM notebooks
### Describe the issue linked to the documentation
I couldn't help but notice that the docs have Jupyter lite and binder. The binder links seem to fail at the moment and while the Jupyterlite seems to run ok ... would folks maybe be open to marimo notebooks for this as an alternative?
<img... | 32,263 | [
-0.009584960527718067,
0.004494006745517254,
0.013188510201871395,
-0.03761419653892517,
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0.08941468596458435,
0.10989528149366379,
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0.05869641527533531,
-0.0352913960814476,
0.03... |
https://github.com/scikit-learn/scikit-learn/issues/32263 | [
"Documentation",
"RFC"
] | marimo for WASM notebooks
### Describe the issue linked to the documentation
I couldn't help but notice that the docs have Jupyter lite and binder. The binder links seem to fail at the moment and while the Jupyterlite seems to run ok ... would folks maybe be open to marimo notebooks for this as an alternative?
<img... | 32,263 | [
-0.012686636298894882,
0.00160204095300287,
0.012576516717672348,
-0.032875366508960724,
0.0067093223333358765,
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0.08884124457836151,
0.11714964359998703,
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0.05413941666483879,
-0.03112705983221531,
0.03... |
https://github.com/scikit-learn/scikit-learn/issues/32263 | [
"Documentation",
"RFC"
] | marimo for WASM notebooks
### Describe the issue linked to the documentation
I couldn't help but notice that the docs have Jupyter lite and binder. The binder links seem to fail at the moment and while the Jupyterlite seems to run ok ... would folks maybe be open to marimo notebooks for this as an alternative?
<img... | 32,263 | [
-0.01695888489484787,
0.0032539914827793837,
0.004591057077050209,
-0.0315825454890728,
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0.09316060692071915,
0.11496530473232269,
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0.050428565591573715,
-0.030183853581547737,
0... |
https://github.com/scikit-learn/scikit-learn/issues/32263 | [
"Documentation",
"RFC"
] | marimo for WASM notebooks
### Describe the issue linked to the documentation
I couldn't help but notice that the docs have Jupyter lite and binder. The binder links seem to fail at the moment and while the Jupyterlite seems to run ok ... would folks maybe be open to marimo notebooks for this as an alternative?
<img... | 32,263 | [
0.0014111072523519397,
0.008243653923273087,
0.0027993868570774794,
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0.08210153877735138,
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0.04889136925339699,
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0... |
https://github.com/scikit-learn/scikit-learn/issues/32263 | [
"Documentation",
"RFC"
] | marimo for WASM notebooks
### Describe the issue linked to the documentation
I couldn't help but notice that the docs have Jupyter lite and binder. The binder links seem to fail at the moment and while the Jupyterlite seems to run ok ... would folks maybe be open to marimo notebooks for this as an alternative?
<img... | 32,263 | [
-0.023758379742503166,
-0.013894842937588692,
0.0070412978529930115,
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0.0960938110947609,
0.10115247964859009,
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0.0743165835738182,
-0.037254221737384796,
... |
https://github.com/scikit-learn/scikit-learn/issues/32263 | [
"Documentation",
"RFC"
] | marimo for WASM notebooks
### Describe the issue linked to the documentation
I couldn't help but notice that the docs have Jupyter lite and binder. The binder links seem to fail at the moment and while the Jupyterlite seems to run ok ... would folks maybe be open to marimo notebooks for this as an alternative?
<img... | 32,263 | [
0.004227804020047188,
-0.004588785115629435,
0.004858066793531179,
-0.028545718640089035,
0.0016716007376089692,
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0.07338617742061615,
0.11409776657819748,
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0.05692775174975395,
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0... |
https://github.com/scikit-learn/scikit-learn/issues/32263 | [
"Documentation",
"RFC"
] | marimo for WASM notebooks
### Describe the issue linked to the documentation
I couldn't help but notice that the docs have Jupyter lite and binder. The binder links seem to fail at the moment and while the Jupyterlite seems to run ok ... would folks maybe be open to marimo notebooks for this as an alternative?
<img... | 32,263 | [
-0.02086980640888214,
0.00011436732893344015,
0.0068681202828884125,
-0.03331011161208153,
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0.08489127457141876,
0.11169514805078506,
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0.06277578324079514,
-0.03278408572077751,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32263 | [
"Documentation",
"RFC"
] | marimo for WASM notebooks
### Describe the issue linked to the documentation
I couldn't help but notice that the docs have Jupyter lite and binder. The binder links seem to fail at the moment and while the Jupyterlite seems to run ok ... would folks maybe be open to marimo notebooks for this as an alternative?
<img... | 32,263 | [
-0.010525885038077831,
-0.00500721437856555,
0.004563700407743454,
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0.0011216314742341638,
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0.08810073137283325,
0.11770877987146378,
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0.05139005556702614,
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0... |
https://github.com/scikit-learn/scikit-learn/issues/32247 | [
"Documentation"
] | `type_of_target` returns 'multiclass' instead of 'continuous' on regression tasks with integer values e.g. house prices.
### Describe the bug
`utils.multiclass.type_of_target` returns 'multiclass' when y is the target of a regression problem that only takes integer values, even when cast to "float".
This appeared wh... | 32,247 | [
-0.047813739627599716,
0.054327964782714844,
0.017256831750273705,
-0.013268677517771721,
0.0948621928691864,
-0.015256850980222225,
0.04258139058947563,
0.05258167162537575,
-0.02373080514371395,
-0.02080029435455799,
-0.006194128189235926,
0.05442750081419945,
-0.014465836808085442,
0.02... |
https://github.com/scikit-learn/scikit-learn/issues/32247 | [
"Documentation"
] | `type_of_target` returns 'multiclass' instead of 'continuous' on regression tasks with integer values e.g. house prices.
### Describe the bug
`utils.multiclass.type_of_target` returns 'multiclass' when y is the target of a regression problem that only takes integer values, even when cast to "float".
This appeared wh... | 32,247 | [
-0.047813739627599716,
0.054327964782714844,
0.017256831750273705,
-0.013268677517771721,
0.0948621928691864,
-0.015256850980222225,
0.04258139058947563,
0.05258167162537575,
-0.02373080514371395,
-0.02080029435455799,
-0.006194128189235926,
0.05442750081419945,
-0.014465836808085442,
0.02... |
https://github.com/scikit-learn/scikit-learn/issues/32247 | [
"Documentation"
] | `type_of_target` returns 'multiclass' instead of 'continuous' on regression tasks with integer values e.g. house prices.
### Describe the bug
`utils.multiclass.type_of_target` returns 'multiclass' when y is the target of a regression problem that only takes integer values, even when cast to "float".
This appeared wh... | 32,247 | [
-0.047813739627599716,
0.054327964782714844,
0.017256831750273705,
-0.013268677517771721,
0.0948621928691864,
-0.015256850980222225,
0.04258139058947563,
0.05258167162537575,
-0.02373080514371395,
-0.02080029435455799,
-0.006194128189235926,
0.05442750081419945,
-0.014465836808085442,
0.02... |
https://github.com/scikit-learn/scikit-learn/issues/32247 | [
"Documentation"
] | `type_of_target` returns 'multiclass' instead of 'continuous' on regression tasks with integer values e.g. house prices.
### Describe the bug
`utils.multiclass.type_of_target` returns 'multiclass' when y is the target of a regression problem that only takes integer values, even when cast to "float".
This appeared wh... | 32,247 | [
-0.047813739627599716,
0.054327964782714844,
0.017256831750273705,
-0.013268677517771721,
0.0948621928691864,
-0.015256850980222225,
0.04258139058947563,
0.05258167162537575,
-0.02373080514371395,
-0.02080029435455799,
-0.006194128189235926,
0.05442750081419945,
-0.014465836808085442,
0.02... |
https://github.com/scikit-learn/scikit-learn/issues/32247 | [
"Documentation"
] | `type_of_target` returns 'multiclass' instead of 'continuous' on regression tasks with integer values e.g. house prices.
### Describe the bug
`utils.multiclass.type_of_target` returns 'multiclass' when y is the target of a regression problem that only takes integer values, even when cast to "float".
This appeared wh... | 32,247 | [
-0.047813739627599716,
0.054327964782714844,
0.017256831750273705,
-0.013268677517771721,
0.0948621928691864,
-0.015256850980222225,
0.04258139058947563,
0.05258167162537575,
-0.02373080514371395,
-0.02080029435455799,
-0.006194128189235926,
0.05442750081419945,
-0.014465836808085442,
0.02... |
https://github.com/scikit-learn/scikit-learn/issues/32247 | [
"Documentation"
] | `type_of_target` returns 'multiclass' instead of 'continuous' on regression tasks with integer values e.g. house prices.
### Describe the bug
`utils.multiclass.type_of_target` returns 'multiclass' when y is the target of a regression problem that only takes integer values, even when cast to "float".
This appeared wh... | 32,247 | [
-0.047813739627599716,
0.054327964782714844,
0.017256831750273705,
-0.013268677517771721,
0.0948621928691864,
-0.015256850980222225,
0.04258139058947563,
0.05258167162537575,
-0.02373080514371395,
-0.02080029435455799,
-0.006194128189235926,
0.05442750081419945,
-0.014465836808085442,
0.02... |
https://github.com/scikit-learn/scikit-learn/issues/32247 | [
"Documentation"
] | `type_of_target` returns 'multiclass' instead of 'continuous' on regression tasks with integer values e.g. house prices.
### Describe the bug
`utils.multiclass.type_of_target` returns 'multiclass' when y is the target of a regression problem that only takes integer values, even when cast to "float".
This appeared wh... | 32,247 | [
-0.047813739627599716,
0.054327964782714844,
0.017256831750273705,
-0.013268677517771721,
0.0948621928691864,
-0.015256850980222225,
0.04258139058947563,
0.05258167162537575,
-0.02373080514371395,
-0.02080029435455799,
-0.006194128189235926,
0.05442750081419945,
-0.014465836808085442,
0.02... |
https://github.com/scikit-learn/scikit-learn/issues/32247 | [
"Documentation"
] | `type_of_target` returns 'multiclass' instead of 'continuous' on regression tasks with integer values e.g. house prices.
### Describe the bug
`utils.multiclass.type_of_target` returns 'multiclass' when y is the target of a regression problem that only takes integer values, even when cast to "float".
This appeared wh... | 32,247 | [
-0.047813739627599716,
0.054327964782714844,
0.017256831750273705,
-0.013268677517771721,
0.0948621928691864,
-0.015256850980222225,
0.04258139058947563,
0.05258167162537575,
-0.02373080514371395,
-0.02080029435455799,
-0.006194128189235926,
0.05442750081419945,
-0.014465836808085442,
0.02... |
https://github.com/scikit-learn/scikit-learn/issues/32247 | [
"Documentation"
] | `type_of_target` returns 'multiclass' instead of 'continuous' on regression tasks with integer values e.g. house prices.
### Describe the bug
`utils.multiclass.type_of_target` returns 'multiclass' when y is the target of a regression problem that only takes integer values, even when cast to "float".
This appeared wh... | 32,247 | [
-0.047813739627599716,
0.054327964782714844,
0.017256831750273705,
-0.013268677517771721,
0.0948621928691864,
-0.015256850980222225,
0.04258139058947563,
0.05258167162537575,
-0.02373080514371395,
-0.02080029435455799,
-0.006194128189235926,
0.05442750081419945,
-0.014465836808085442,
0.02... |
https://github.com/scikit-learn/scikit-learn/issues/32247 | [
"Documentation"
] | `type_of_target` returns 'multiclass' instead of 'continuous' on regression tasks with integer values e.g. house prices.
### Describe the bug
`utils.multiclass.type_of_target` returns 'multiclass' when y is the target of a regression problem that only takes integer values, even when cast to "float".
This appeared wh... | 32,247 | [
-0.047813739627599716,
0.054327964782714844,
0.017256831750273705,
-0.013268677517771721,
0.0948621928691864,
-0.015256850980222225,
0.04258139058947563,
0.05258167162537575,
-0.02373080514371395,
-0.02080029435455799,
-0.006194128189235926,
0.05442750081419945,
-0.014465836808085442,
0.02... |
https://github.com/scikit-learn/scikit-learn/issues/32247 | [
"Documentation"
] | `type_of_target` returns 'multiclass' instead of 'continuous' on regression tasks with integer values e.g. house prices.
### Describe the bug
`utils.multiclass.type_of_target` returns 'multiclass' when y is the target of a regression problem that only takes integer values, even when cast to "float".
This appeared wh... | 32,247 | [
-0.047813739627599716,
0.054327964782714844,
0.017256831750273705,
-0.013268677517771721,
0.0948621928691864,
-0.015256850980222225,
0.04258139058947563,
0.05258167162537575,
-0.02373080514371395,
-0.02080029435455799,
-0.006194128189235926,
0.05442750081419945,
-0.014465836808085442,
0.02... |
https://github.com/scikit-learn/scikit-learn/issues/32247 | [
"Documentation"
] | `type_of_target` returns 'multiclass' instead of 'continuous' on regression tasks with integer values e.g. house prices.
### Describe the bug
`utils.multiclass.type_of_target` returns 'multiclass' when y is the target of a regression problem that only takes integer values, even when cast to "float".
This appeared wh... | 32,247 | [
-0.047813739627599716,
0.054327964782714844,
0.017256831750273705,
-0.013268677517771721,
0.0948621928691864,
-0.015256850980222225,
0.04258139058947563,
0.05258167162537575,
-0.02373080514371395,
-0.02080029435455799,
-0.006194128189235926,
0.05442750081419945,
-0.014465836808085442,
0.02... |
https://github.com/scikit-learn/scikit-learn/issues/32247 | [
"Documentation"
] | `type_of_target` returns 'multiclass' instead of 'continuous' on regression tasks with integer values e.g. house prices.
### Describe the bug
`utils.multiclass.type_of_target` returns 'multiclass' when y is the target of a regression problem that only takes integer values, even when cast to "float".
This appeared wh... | 32,247 | [
-0.047813739627599716,
0.054327964782714844,
0.017256831750273705,
-0.013268677517771721,
0.0948621928691864,
-0.015256850980222225,
0.04258139058947563,
0.05258167162537575,
-0.02373080514371395,
-0.02080029435455799,
-0.006194128189235926,
0.05442750081419945,
-0.014465836808085442,
0.02... |
https://github.com/scikit-learn/scikit-learn/issues/32247 | [
"Documentation"
] | `type_of_target` returns 'multiclass' instead of 'continuous' on regression tasks with integer values e.g. house prices.
### Describe the bug
`utils.multiclass.type_of_target` returns 'multiclass' when y is the target of a regression problem that only takes integer values, even when cast to "float".
This appeared wh... | 32,247 | [
-0.047813739627599716,
0.054327964782714844,
0.017256831750273705,
-0.013268677517771721,
0.0948621928691864,
-0.015256850980222225,
0.04258139058947563,
0.05258167162537575,
-0.02373080514371395,
-0.02080029435455799,
-0.006194128189235926,
0.05442750081419945,
-0.014465836808085442,
0.02... |
https://github.com/scikit-learn/scikit-learn/issues/32247 | [
"Documentation"
] | `type_of_target` returns 'multiclass' instead of 'continuous' on regression tasks with integer values e.g. house prices.
### Describe the bug
`utils.multiclass.type_of_target` returns 'multiclass' when y is the target of a regression problem that only takes integer values, even when cast to "float".
This appeared wh... | 32,247 | [
-0.047813739627599716,
0.054327964782714844,
0.017256831750273705,
-0.013268677517771721,
0.0948621928691864,
-0.015256850980222225,
0.04258139058947563,
0.05258167162537575,
-0.02373080514371395,
-0.02080029435455799,
-0.006194128189235926,
0.05442750081419945,
-0.014465836808085442,
0.02... |
https://github.com/scikit-learn/scikit-learn/issues/32247 | [
"Documentation"
] | `type_of_target` returns 'multiclass' instead of 'continuous' on regression tasks with integer values e.g. house prices.
### Describe the bug
`utils.multiclass.type_of_target` returns 'multiclass' when y is the target of a regression problem that only takes integer values, even when cast to "float".
This appeared wh... | 32,247 | [
-0.047813739627599716,
0.054327964782714844,
0.017256831750273705,
-0.013268677517771721,
0.0948621928691864,
-0.015256850980222225,
0.04258139058947563,
0.05258167162537575,
-0.02373080514371395,
-0.02080029435455799,
-0.006194128189235926,
0.05442750081419945,
-0.014465836808085442,
0.02... |
https://github.com/scikit-learn/scikit-learn/issues/32225 | [
"Easy",
"Documentation",
"module:datasets"
] | Target value described as "average" instead of "median" in sklearn.datasets.fetch_california_housing documentation
### Describe the issue linked to the documentation
Returned target is described as
"Each value corresponds to the average house value in units of 100,000."
In 8.2 of the User Guide the return value is d... | 32,225 | [
-0.04940607026219368,
-0.016913769766688347,
-0.01880917139351368,
-0.009499131701886654,
0.03557133674621582,
0.02558409422636032,
0.05005708336830139,
-0.013982467353343964,
-0.024750838056206703,
0.008596755564212799,
0.023763855919241905,
0.024822097271680832,
0.037359755486249924,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32216 | [
"RFC"
] | RFC Consider changing the output of transformer returning sparse matrix to sparse array
Currently, we have a couple of transformer that returns sparse matrix. With the work on array-api in the ecosystem, it could actually be annoying because matrix are not array and might not be supported.
To illustrate with an examp... | 32,216 | [
0.002409800887107849,
0.06879854202270508,
0.027784625068306923,
-0.002927371533587575,
0.05938058719038963,
-0.013339021243155003,
0.03010917641222477,
0.05349055677652359,
-0.051594968885183334,
-0.03887825459241867,
0.01966465823352337,
0.026319675147533417,
-0.014203714206814766,
0.020... |
https://github.com/scikit-learn/scikit-learn/issues/32216 | [
"RFC"
] | RFC Consider changing the output of transformer returning sparse matrix to sparse array
Currently, we have a couple of transformer that returns sparse matrix. With the work on array-api in the ecosystem, it could actually be annoying because matrix are not array and might not be supported.
To illustrate with an examp... | 32,216 | [
0.009799925610423088,
0.0775490552186966,
0.03228176012635231,
-0.021259035915136337,
0.05466727539896965,
-0.003944384399801493,
0.02500261552631855,
0.03891890496015549,
-0.0447939895093441,
-0.025328034535050392,
0.029826583340764046,
0.012083195149898529,
-0.018581202253699303,
0.00498... |
https://github.com/scikit-learn/scikit-learn/issues/32216 | [
"RFC"
] | RFC Consider changing the output of transformer returning sparse matrix to sparse array
Currently, we have a couple of transformer that returns sparse matrix. With the work on array-api in the ecosystem, it could actually be annoying because matrix are not array and might not be supported.
To illustrate with an examp... | 32,216 | [
0.015809938311576843,
0.07214876264333725,
0.02581104077398777,
-0.0014243110781535506,
0.05467400327324867,
-0.013261191546916962,
0.032370686531066895,
0.05215520039200783,
-0.0541473813354969,
-0.04345417767763138,
0.019550973549485207,
0.02112410217523575,
-0.007448872085660696,
0.0218... |
https://github.com/scikit-learn/scikit-learn/issues/32216 | [
"RFC"
] | RFC Consider changing the output of transformer returning sparse matrix to sparse array
Currently, we have a couple of transformer that returns sparse matrix. With the work on array-api in the ecosystem, it could actually be annoying because matrix are not array and might not be supported.
To illustrate with an examp... | 32,216 | [
0.010529627092182636,
0.06825348734855652,
0.027875574305653572,
0.0022012614645063877,
0.06444753706455231,
-0.005459357053041458,
0.031070413067936897,
0.04590058699250221,
-0.052966874092817307,
-0.033532194793224335,
0.013340300880372524,
0.029202857986092567,
-0.010927937924861908,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/32214 | [
"Bug",
"module:test-suite"
] | ⚠️ CI failed on macOS.pylatest_conda_forge_mkl_no_openmp (last failure: Sep 18, 2025) ⚠️
**CI failed on [macOS.pylatest_conda_forge_mkl_no_openmp](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=80124&view=logs&j=8b4d29c4-7356-5617-94d6-7bef17a56394)** (Sep 18, 2025)
- test_fit_transform[76]
CO... | 32,214 | [
-0.026781460270285606,
0.015417157672345638,
-0.041929516941308975,
-0.034893788397312164,
0.043609749525785446,
-0.012663808651268482,
0.01692252978682518,
0.058518171310424805,
-0.018362687900662422,
0.004385504871606827,
0.025038080289959908,
0.06556972861289978,
0.010538332164287567,
0... |
https://github.com/scikit-learn/scikit-learn/issues/32214 | [
"Bug",
"module:test-suite"
] | ⚠️ CI failed on macOS.pylatest_conda_forge_mkl_no_openmp (last failure: Sep 18, 2025) ⚠️
**CI failed on [macOS.pylatest_conda_forge_mkl_no_openmp](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=80124&view=logs&j=8b4d29c4-7356-5617-94d6-7bef17a56394)** (Sep 18, 2025)
- test_fit_transform[76]
CO... | 32,214 | [
-0.029776524752378464,
0.01450474001467228,
-0.03190144896507263,
-0.023502714931964874,
0.05301840230822563,
-0.01751229539513588,
0.016091059893369675,
0.0478394441306591,
-0.02511870488524437,
0.016378991305828094,
0.027372388169169426,
0.05797703191637993,
0.013605842366814613,
0.07481... |
https://github.com/scikit-learn/scikit-learn/issues/32214 | [
"Bug",
"module:test-suite"
] | ⚠️ CI failed on macOS.pylatest_conda_forge_mkl_no_openmp (last failure: Sep 18, 2025) ⚠️
**CI failed on [macOS.pylatest_conda_forge_mkl_no_openmp](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=80124&view=logs&j=8b4d29c4-7356-5617-94d6-7bef17a56394)** (Sep 18, 2025)
- test_fit_transform[76]
CO... | 32,214 | [
-0.02745644748210907,
0.02801268920302391,
-0.03601708263158798,
-0.034380391240119934,
0.046041619032621384,
-0.008062804117798805,
0.016716301441192627,
0.04787068068981171,
-0.03504736348986626,
0.016229311004281044,
0.032496366649866104,
0.04812640696763992,
0.008128010667860508,
0.110... |
https://github.com/scikit-learn/scikit-learn/issues/32213 | [
"Documentation"
] | Missing Python 3.14 in Readme and Pypi
### Describe the issue linked to the documentation
At <https://github.com/scikit-learn/scikit-learn/releases/tag/1.7.2> it is stated that the new release 1.7.2 supports Python 3.14 but neither at <https://pypi.org/project/scikit-learn/> nor in the repo's readme file this is refl... | 32,213 | [
0.02162172831594944,
-0.024408582597970963,
-0.009806565940380096,
-0.07888847589492798,
0.02309260703623295,
0.033385392278432846,
0.05354979261755943,
0.031156115233898163,
0.01694585382938385,
-0.006178558338433504,
0.047918032854795456,
0.07364305108785629,
0.0081982696428895,
0.016752... |
https://github.com/scikit-learn/scikit-learn/issues/32213 | [
"Documentation"
] | Missing Python 3.14 in Readme and Pypi
### Describe the issue linked to the documentation
At <https://github.com/scikit-learn/scikit-learn/releases/tag/1.7.2> it is stated that the new release 1.7.2 supports Python 3.14 but neither at <https://pypi.org/project/scikit-learn/> nor in the repo's readme file this is refl... | 32,213 | [
0.03224949538707733,
-0.011594058945775032,
-0.007980386726558208,
-0.07249971479177475,
0.017925765365362167,
0.031392257660627365,
0.04131622985005379,
0.010953525081276894,
0.0014479527017101645,
-0.012199414893984795,
0.043170150369405746,
0.07431962341070175,
0.01484724972397089,
0.01... |
https://github.com/scikit-learn/scikit-learn/issues/32213 | [
"Documentation"
] | Missing Python 3.14 in Readme and Pypi
### Describe the issue linked to the documentation
At <https://github.com/scikit-learn/scikit-learn/releases/tag/1.7.2> it is stated that the new release 1.7.2 supports Python 3.14 but neither at <https://pypi.org/project/scikit-learn/> nor in the repo's readme file this is refl... | 32,213 | [
0.01896486058831215,
-0.012725134380161762,
-0.01021798700094223,
-0.08212766796350479,
0.019704941660165787,
0.029788946732878685,
0.048643916845321655,
0.02905195578932762,
0.01345105841755867,
-0.004828379023820162,
0.042625900357961655,
0.07129677385091782,
0.007676398381590843,
0.0182... |
https://github.com/scikit-learn/scikit-learn/issues/32210 | [
"Bug",
"Needs Triage"
] | `LinearRegression` singular values differ from `model.singular_` if computed manually
### Describe the bug
I was looking around scipy's singular value functions and wanted to see if I can get the same singular values of a matrix X as `LinearRegression` model (`model.singular_`). I couldn't and looked at how sklearn d... | 32,210 | [
-0.01842644065618515,
-0.020354609936475754,
0.02853173017501831,
0.049940142780542374,
0.08500143140554428,
-0.013406469486653805,
0.04445674270391464,
-0.006890354678034782,
0.04144027456641197,
0.013679969124495983,
-0.016315968707203865,
0.06779329478740692,
0.0009838859550654888,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32210 | [
"Bug",
"Needs Triage"
] | `LinearRegression` singular values differ from `model.singular_` if computed manually
### Describe the bug
I was looking around scipy's singular value functions and wanted to see if I can get the same singular values of a matrix X as `LinearRegression` model (`model.singular_`). I couldn't and looked at how sklearn d... | 32,210 | [
-0.01842644065618515,
-0.020354609936475754,
0.02853173017501831,
0.049940142780542374,
0.08500143140554428,
-0.013406469486653805,
0.04445674270391464,
-0.006890354678034782,
0.04144027456641197,
0.013679969124495983,
-0.016315968707203865,
0.06779329478740692,
0.0009838859550654888,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32207 | [
"Needs Decision",
"RFC"
] | RFC: Proposal for autoclose option for non-compliant PRs
Following up on the discussion in #31679 about low-effort contributions (like ai-generated with low human supervision), @lucyleeow and me worked out an idea: We would like to propose introducing an autoclose option for PRs that gets triggered when setting an "au... | 32,207 | [
0.004014828708022833,
0.03294063359498978,
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https://github.com/scikit-learn/scikit-learn/issues/32207 | [
"Needs Decision",
"RFC"
] | RFC: Proposal for autoclose option for non-compliant PRs
Following up on the discussion in #31679 about low-effort contributions (like ai-generated with low human supervision), @lucyleeow and me worked out an idea: We would like to propose introducing an autoclose option for PRs that gets triggered when setting an "au... | 32,207 | [
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https://github.com/scikit-learn/scikit-learn/issues/32207 | [
"Needs Decision",
"RFC"
] | RFC: Proposal for autoclose option for non-compliant PRs
Following up on the discussion in #31679 about low-effort contributions (like ai-generated with low human supervision), @lucyleeow and me worked out an idea: We would like to propose introducing an autoclose option for PRs that gets triggered when setting an "au... | 32,207 | [
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https://github.com/scikit-learn/scikit-learn/issues/32207 | [
"Needs Decision",
"RFC"
] | RFC: Proposal for autoclose option for non-compliant PRs
Following up on the discussion in #31679 about low-effort contributions (like ai-generated with low human supervision), @lucyleeow and me worked out an idea: We would like to propose introducing an autoclose option for PRs that gets triggered when setting an "au... | 32,207 | [
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https://github.com/scikit-learn/scikit-learn/issues/32207 | [
"Needs Decision",
"RFC"
] | RFC: Proposal for autoclose option for non-compliant PRs
Following up on the discussion in #31679 about low-effort contributions (like ai-generated with low human supervision), @lucyleeow and me worked out an idea: We would like to propose introducing an autoclose option for PRs that gets triggered when setting an "au... | 32,207 | [
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https://github.com/scikit-learn/scikit-learn/issues/32207 | [
"Needs Decision",
"RFC"
] | RFC: Proposal for autoclose option for non-compliant PRs
Following up on the discussion in #31679 about low-effort contributions (like ai-generated with low human supervision), @lucyleeow and me worked out an idea: We would like to propose introducing an autoclose option for PRs that gets triggered when setting an "au... | 32,207 | [
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https://github.com/scikit-learn/scikit-learn/issues/32207 | [
"Needs Decision",
"RFC"
] | RFC: Proposal for autoclose option for non-compliant PRs
Following up on the discussion in #31679 about low-effort contributions (like ai-generated with low human supervision), @lucyleeow and me worked out an idea: We would like to propose introducing an autoclose option for PRs that gets triggered when setting an "au... | 32,207 | [
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https://github.com/scikit-learn/scikit-learn/issues/32207 | [
"Needs Decision",
"RFC"
] | RFC: Proposal for autoclose option for non-compliant PRs
Following up on the discussion in #31679 about low-effort contributions (like ai-generated with low human supervision), @lucyleeow and me worked out an idea: We would like to propose introducing an autoclose option for PRs that gets triggered when setting an "au... | 32,207 | [
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0.001... |
https://github.com/scikit-learn/scikit-learn/issues/32207 | [
"Needs Decision",
"RFC"
] | RFC: Proposal for autoclose option for non-compliant PRs
Following up on the discussion in #31679 about low-effort contributions (like ai-generated with low human supervision), @lucyleeow and me worked out an idea: We would like to propose introducing an autoclose option for PRs that gets triggered when setting an "au... | 32,207 | [
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https://github.com/scikit-learn/scikit-learn/issues/32207 | [
"Needs Decision",
"RFC"
] | RFC: Proposal for autoclose option for non-compliant PRs
Following up on the discussion in #31679 about low-effort contributions (like ai-generated with low human supervision), @lucyleeow and me worked out an idea: We would like to propose introducing an autoclose option for PRs that gets triggered when setting an "au... | 32,207 | [
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0.001... |
https://github.com/scikit-learn/scikit-learn/issues/32207 | [
"Needs Decision",
"RFC"
] | RFC: Proposal for autoclose option for non-compliant PRs
Following up on the discussion in #31679 about low-effort contributions (like ai-generated with low human supervision), @lucyleeow and me worked out an idea: We would like to propose introducing an autoclose option for PRs that gets triggered when setting an "au... | 32,207 | [
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0.001... |
https://github.com/scikit-learn/scikit-learn/issues/32207 | [
"Needs Decision",
"RFC"
] | RFC: Proposal for autoclose option for non-compliant PRs
Following up on the discussion in #31679 about low-effort contributions (like ai-generated with low human supervision), @lucyleeow and me worked out an idea: We would like to propose introducing an autoclose option for PRs that gets triggered when setting an "au... | 32,207 | [
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0.001... |
https://github.com/scikit-learn/scikit-learn/issues/32207 | [
"Needs Decision",
"RFC"
] | RFC: Proposal for autoclose option for non-compliant PRs
Following up on the discussion in #31679 about low-effort contributions (like ai-generated with low human supervision), @lucyleeow and me worked out an idea: We would like to propose introducing an autoclose option for PRs that gets triggered when setting an "au... | 32,207 | [
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0.001... |
https://github.com/scikit-learn/scikit-learn/issues/32207 | [
"Needs Decision",
"RFC"
] | RFC: Proposal for autoclose option for non-compliant PRs
Following up on the discussion in #31679 about low-effort contributions (like ai-generated with low human supervision), @lucyleeow and me worked out an idea: We would like to propose introducing an autoclose option for PRs that gets triggered when setting an "au... | 32,207 | [
0.004014828708022833,
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0.001... |
https://github.com/scikit-learn/scikit-learn/issues/32207 | [
"Needs Decision",
"RFC"
] | RFC: Proposal for autoclose option for non-compliant PRs
Following up on the discussion in #31679 about low-effort contributions (like ai-generated with low human supervision), @lucyleeow and me worked out an idea: We would like to propose introducing an autoclose option for PRs that gets triggered when setting an "au... | 32,207 | [
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0.001... |
https://github.com/scikit-learn/scikit-learn/issues/32207 | [
"Needs Decision",
"RFC"
] | RFC: Proposal for autoclose option for non-compliant PRs
Following up on the discussion in #31679 about low-effort contributions (like ai-generated with low human supervision), @lucyleeow and me worked out an idea: We would like to propose introducing an autoclose option for PRs that gets triggered when setting an "au... | 32,207 | [
0.004014828708022833,
0.03294063359498978,
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-0.025936251506209373,
0.001... |
https://github.com/scikit-learn/scikit-learn/issues/32207 | [
"Needs Decision",
"RFC"
] | RFC: Proposal for autoclose option for non-compliant PRs
Following up on the discussion in #31679 about low-effort contributions (like ai-generated with low human supervision), @lucyleeow and me worked out an idea: We would like to propose introducing an autoclose option for PRs that gets triggered when setting an "au... | 32,207 | [
0.004014828708022833,
0.03294063359498978,
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0.008393313735723495,
-0.025936251506209373,
0.001... |
https://github.com/scikit-learn/scikit-learn/issues/32207 | [
"Needs Decision",
"RFC"
] | RFC: Proposal for autoclose option for non-compliant PRs
Following up on the discussion in #31679 about low-effort contributions (like ai-generated with low human supervision), @lucyleeow and me worked out an idea: We would like to propose introducing an autoclose option for PRs that gets triggered when setting an "au... | 32,207 | [
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0.001... |
https://github.com/scikit-learn/scikit-learn/issues/32207 | [
"Needs Decision",
"RFC"
] | RFC: Proposal for autoclose option for non-compliant PRs
Following up on the discussion in #31679 about low-effort contributions (like ai-generated with low human supervision), @lucyleeow and me worked out an idea: We would like to propose introducing an autoclose option for PRs that gets triggered when setting an "au... | 32,207 | [
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-0.025936251506209373,
0.001... |
https://github.com/scikit-learn/scikit-learn/issues/32207 | [
"Needs Decision",
"RFC"
] | RFC: Proposal for autoclose option for non-compliant PRs
Following up on the discussion in #31679 about low-effort contributions (like ai-generated with low human supervision), @lucyleeow and me worked out an idea: We would like to propose introducing an autoclose option for PRs that gets triggered when setting an "au... | 32,207 | [
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0.001... |
https://github.com/scikit-learn/scikit-learn/issues/32207 | [
"Needs Decision",
"RFC"
] | RFC: Proposal for autoclose option for non-compliant PRs
Following up on the discussion in #31679 about low-effort contributions (like ai-generated with low human supervision), @lucyleeow and me worked out an idea: We would like to propose introducing an autoclose option for PRs that gets triggered when setting an "au... | 32,207 | [
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-0.025936251506209373,
0.001... |
https://github.com/scikit-learn/scikit-learn/issues/32207 | [
"Needs Decision",
"RFC"
] | RFC: Proposal for autoclose option for non-compliant PRs
Following up on the discussion in #31679 about low-effort contributions (like ai-generated with low human supervision), @lucyleeow and me worked out an idea: We would like to propose introducing an autoclose option for PRs that gets triggered when setting an "au... | 32,207 | [
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0.0022056715097278357,
0.0699387863278389,
0.008393313735723495,
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0.001... |
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