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/24614 | [
"New Feature",
"Needs Decision",
"module:linear_model",
"Needs Decision - Include Feature"
] | GLM doesn't have an offset option
### Describe the workflow you want to enable
As described at #24155, GLM should also support the offset option.
### Describe your proposed solution
For example
```python
from sklearn.linear_model import PoissonRegressor
glm = PoissonRegressor(
alpha=0,... | 24,614 | [
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0.... |
https://github.com/scikit-learn/scikit-learn/issues/24614 | [
"New Feature",
"Needs Decision",
"module:linear_model",
"Needs Decision - Include Feature"
] | GLM doesn't have an offset option
### Describe the workflow you want to enable
As described at #24155, GLM should also support the offset option.
### Describe your proposed solution
For example
```python
from sklearn.linear_model import PoissonRegressor
glm = PoissonRegressor(
alpha=0,... | 24,614 | [
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0.034... |
https://github.com/scikit-learn/scikit-learn/issues/24614 | [
"New Feature",
"Needs Decision",
"module:linear_model",
"Needs Decision - Include Feature"
] | GLM doesn't have an offset option
### Describe the workflow you want to enable
As described at #24155, GLM should also support the offset option.
### Describe your proposed solution
For example
```python
from sklearn.linear_model import PoissonRegressor
glm = PoissonRegressor(
alpha=0,... | 24,614 | [
0.009932013228535652,
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0.... |
https://github.com/scikit-learn/scikit-learn/issues/24614 | [
"New Feature",
"Needs Decision",
"module:linear_model",
"Needs Decision - Include Feature"
] | GLM doesn't have an offset option
### Describe the workflow you want to enable
As described at #24155, GLM should also support the offset option.
### Describe your proposed solution
For example
```python
from sklearn.linear_model import PoissonRegressor
glm = PoissonRegressor(
alpha=0,... | 24,614 | [
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0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24614 | [
"New Feature",
"Needs Decision",
"module:linear_model",
"Needs Decision - Include Feature"
] | GLM doesn't have an offset option
### Describe the workflow you want to enable
As described at #24155, GLM should also support the offset option.
### Describe your proposed solution
For example
```python
from sklearn.linear_model import PoissonRegressor
glm = PoissonRegressor(
alpha=0,... | 24,614 | [
0.005446990951895714,
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https://github.com/scikit-learn/scikit-learn/issues/24614 | [
"New Feature",
"Needs Decision",
"module:linear_model",
"Needs Decision - Include Feature"
] | GLM doesn't have an offset option
### Describe the workflow you want to enable
As described at #24155, GLM should also support the offset option.
### Describe your proposed solution
For example
```python
from sklearn.linear_model import PoissonRegressor
glm = PoissonRegressor(
alpha=0,... | 24,614 | [
-0.010149517096579075,
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0.028... |
https://github.com/scikit-learn/scikit-learn/issues/24612 | [
"Bug",
"Build / CI",
"Blocker"
] | ⚠️ CI failed on Wheel builder ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/3278795901)** (Oct 19, 2022)
COMMENT:
The main problem that causes the windows test runs to fail (when importing scikit-learn modules to collect the tests) seems to be a missing compiled... | 24,612 | [
-0.01724543422460556,
0.06035095453262329,
-0.017693815752863884,
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0.019756171852350235,
0.0620235875248909,
0.04110604152083397,
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0.026626743376255035,
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0.016814157366752625,
-0.014971420168876648,
0.0603... |
https://github.com/scikit-learn/scikit-learn/issues/24612 | [
"Bug",
"Build / CI",
"Blocker"
] | ⚠️ CI failed on Wheel builder ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/3278795901)** (Oct 19, 2022)
COMMENT:
The absence of compiled extension is the source of failure for the Windows 64bit wheels only, that is:
https://github.com/scikit-learn/scikit-learn... | 24,612 | [
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0.... |
https://github.com/scikit-learn/scikit-learn/issues/24612 | [
"Bug",
"Build / CI",
"Blocker"
] | ⚠️ CI failed on Wheel builder ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/3278795901)** (Oct 19, 2022)
COMMENT:
Thanks. It's weird because there is a 32 bit windows build for scipy 1.9.1 but not for 1.9.2:
https://pypi.org/project/scipy/1.9.1/#files
I am... | 24,612 | [
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0.0759... |
https://github.com/scikit-learn/scikit-learn/issues/24612 | [
"Bug",
"Build / CI",
"Blocker"
] | ⚠️ CI failed on Wheel builder ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/3278795901)** (Oct 19, 2022)
COMMENT:
> The absence of compiled extension is the source of failure for the Windows 64bit wheels only.
This point still needs investigation though. | 24,612 | [
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0.03244... |
https://github.com/scikit-learn/scikit-learn/issues/24612 | [
"Bug",
"Build / CI",
"Blocker"
] | ⚠️ CI failed on Wheel builder ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/3278795901)** (Oct 19, 2022)
COMMENT:
As discussed in #24621, we probably should find a way to let pip use `--prefer-binary` when installing the build and test dependencies. Not sure how... | 24,612 | [
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0.0057377321645617485,
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0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24612 | [
"Bug",
"Build / CI",
"Blocker"
] | ⚠️ CI failed on Wheel builder ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/3278795901)** (Oct 19, 2022)
COMMENT:
@ogrisel Could this be a feature request for [cibuildwheel](https://github.com/pypa/cibuildwheel) itself? | 24,612 | [
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0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24612 | [
"Bug",
"Build / CI",
"Blocker"
] | ⚠️ CI failed on Wheel builder ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/3278795901)** (Oct 19, 2022)
COMMENT:
> > The absence of compiled extension is the source of failure for the Windows 64bit wheels only.
>
> This point still needs investigation though... | 24,612 | [
-0.03547456115484238,
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... |
https://github.com/scikit-learn/scikit-learn/issues/24612 | [
"Bug",
"Build / CI",
"Blocker"
] | ⚠️ CI failed on Wheel builder ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/3278795901)** (Oct 19, 2022)
COMMENT:
Looking at the fix in https://github.com/scikit-learn/scikit-learn/pull/24631, I think the issue with Windows 64bit is that SciPy 1.9.2 no longer sh... | 24,612 | [
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0.0487... |
https://github.com/scikit-learn/scikit-learn/issues/24612 | [
"Bug",
"Build / CI",
"Blocker"
] | ⚠️ CI failed on Wheel builder ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/3278795901)** (Oct 19, 2022)
COMMENT:
> This point is solved by https://github.com/scikit-learn/scikit-learn/pull/24446/files#diff-e0a07d85249fa03c06895043f2d57076b4a1a30b195631e1682b547... | 24,612 | [
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https://github.com/scikit-learn/scikit-learn/issues/24612 | [
"Bug",
"Build / CI",
"Blocker"
] | ⚠️ CI failed on Wheel builder ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/3278795901)** (Oct 19, 2022)
COMMENT:
I opened a new issue for SciPy 1.9.2 here: https://github.com/scipy/scipy/issues/17191. I suspect that SciPy removed `msvcp140.dll` intentionally, w... | 24,612 | [
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0.0436... |
https://github.com/scikit-learn/scikit-learn/issues/24612 | [
"Bug",
"Build / CI",
"Blocker"
] | ⚠️ CI failed on Wheel builder ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/3278795901)** (Oct 19, 2022)
COMMENT:
So the claim in https://github.com/scipy/oldest-supported-numpy/issues/45 is _All versions of Python currently supported should already have `msvcp1... | 24,612 | [
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0.0163020... |
https://github.com/scikit-learn/scikit-learn/issues/24612 | [
"Bug",
"Build / CI",
"Blocker"
] | ⚠️ CI failed on Wheel builder ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/3278795901)** (Oct 19, 2022)
COMMENT:
## CI is no longer failing! ✅
[Successful run](https://github.com/scikit-learn/scikit-learn/actions/runs/3286761573) on Oct 20, 2022 | 24,612 | [
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https://github.com/scikit-learn/scikit-learn/issues/24611 | [
"Documentation"
] | A note about documentation on the logistic regression.
### Describe the issue linked to the documentation
Dear Authors.
First of all, let me express my respect for your hard work and success, acclaimed and used by thousands of ML specialists.
I would like to report a small issue in the documentation, providing a j... | 24,611 | [
0.042990803718566895,
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0.01599... |
https://github.com/scikit-learn/scikit-learn/issues/24611 | [
"Documentation"
] | A note about documentation on the logistic regression.
### Describe the issue linked to the documentation
Dear Authors.
First of all, let me express my respect for your hard work and success, acclaimed and used by thousands of ML specialists.
I would like to report a small issue in the documentation, providing a j... | 24,611 | [
0.042990803718566895,
0.0768813043832779,
0.00616587046533823,
0.0046669067814946175,
0.029479121789336205,
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0.07555917650461197,
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0.002054318320006132,
0.01599... |
https://github.com/scikit-learn/scikit-learn/issues/24611 | [
"Documentation"
] | A note about documentation on the logistic regression.
### Describe the issue linked to the documentation
Dear Authors.
First of all, let me express my respect for your hard work and success, acclaimed and used by thousands of ML specialists.
I would like to report a small issue in the documentation, providing a j... | 24,611 | [
0.042990803718566895,
0.0768813043832779,
0.00616587046533823,
0.0046669067814946175,
0.029479121789336205,
0.029907124117016792,
0.04966277256608009,
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-0.008317399770021439,
0.07555917650461197,
-0.030765289440751076,
0.002054318320006132,
0.01599... |
https://github.com/scikit-learn/scikit-learn/issues/24611 | [
"Documentation"
] | A note about documentation on the logistic regression.
### Describe the issue linked to the documentation
Dear Authors.
First of all, let me express my respect for your hard work and success, acclaimed and used by thousands of ML specialists.
I would like to report a small issue in the documentation, providing a j... | 24,611 | [
0.042990803718566895,
0.0768813043832779,
0.00616587046533823,
0.0046669067814946175,
0.029479121789336205,
0.029907124117016792,
0.04966277256608009,
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-0.008317399770021439,
0.07555917650461197,
-0.030765289440751076,
0.002054318320006132,
0.01599... |
https://github.com/scikit-learn/scikit-learn/issues/24611 | [
"Documentation"
] | A note about documentation on the logistic regression.
### Describe the issue linked to the documentation
Dear Authors.
First of all, let me express my respect for your hard work and success, acclaimed and used by thousands of ML specialists.
I would like to report a small issue in the documentation, providing a j... | 24,611 | [
0.042990803718566895,
0.0768813043832779,
0.00616587046533823,
0.0046669067814946175,
0.029479121789336205,
0.029907124117016792,
0.04966277256608009,
0.02586345188319683,
0.006809113081544638,
-0.008317399770021439,
0.07555917650461197,
-0.030765289440751076,
0.002054318320006132,
0.01599... |
https://github.com/scikit-learn/scikit-learn/issues/24611 | [
"Documentation"
] | A note about documentation on the logistic regression.
### Describe the issue linked to the documentation
Dear Authors.
First of all, let me express my respect for your hard work and success, acclaimed and used by thousands of ML specialists.
I would like to report a small issue in the documentation, providing a j... | 24,611 | [
0.042990803718566895,
0.0768813043832779,
0.00616587046533823,
0.0046669067814946175,
0.029479121789336205,
0.029907124117016792,
0.04966277256608009,
0.02586345188319683,
0.006809113081544638,
-0.008317399770021439,
0.07555917650461197,
-0.030765289440751076,
0.002054318320006132,
0.01599... |
https://github.com/scikit-learn/scikit-learn/issues/24611 | [
"Documentation"
] | A note about documentation on the logistic regression.
### Describe the issue linked to the documentation
Dear Authors.
First of all, let me express my respect for your hard work and success, acclaimed and used by thousands of ML specialists.
I would like to report a small issue in the documentation, providing a j... | 24,611 | [
0.042990803718566895,
0.0768813043832779,
0.00616587046533823,
0.0046669067814946175,
0.029479121789336205,
0.029907124117016792,
0.04966277256608009,
0.02586345188319683,
0.006809113081544638,
-0.008317399770021439,
0.07555917650461197,
-0.030765289440751076,
0.002054318320006132,
0.01599... |
https://github.com/scikit-learn/scikit-learn/issues/24610 | [
"spam"
] | Predicted labels get reversed for HistogramGradientBooostingClassifier
The predicted labels get reversed when a model trained using the sklearn HGBC is applied on the full dataset/new data.
COMMENT:
Please provide a minimal reproducible with the error, otherwise I'm flagging this as spam. | 24,610 | [
0.02645622193813324,
-0.027964942157268524,
0.018695028498768806,
-0.012316235341131687,
0.035661883652210236,
-0.00764980586245656,
-0.008033828809857368,
0.017842553555965424,
0.00906777661293745,
0.04151313006877899,
-0.00042932399082928896,
-0.011262581683695316,
-0.010028895922005177,
... |
https://github.com/scikit-learn/scikit-learn/issues/24606 | [
"Documentation"
] | MiniBatchDictionaryLearning confusion over U,V
### Describe the issue linked to the documentation
https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.MiniBatchDictionaryLearning.html
The optimization problem in the documentation is described as
$$
\arg\min \frac12 \Vert X-UV\Vert_F^2+\alpha... | 24,606 | [
0.028161974623799324,
0.0011692022671923041,
0.006826828233897686,
-0.023220708593726158,
0.008691891096532345,
-0.0074074226431548595,
0.049498338252305984,
0.022032948210835457,
-0.013251455500721931,
-0.057338692247867584,
0.08211895078420639,
-0.03767121583223343,
0.054088134318590164,
... |
https://github.com/scikit-learn/scikit-learn/issues/24606 | [
"Documentation"
] | MiniBatchDictionaryLearning confusion over U,V
### Describe the issue linked to the documentation
https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.MiniBatchDictionaryLearning.html
The optimization problem in the documentation is described as
$$
\arg\min \frac12 \Vert X-UV\Vert_F^2+\alpha... | 24,606 | [
0.028161974623799324,
0.0011692022671923041,
0.006826828233897686,
-0.023220708593726158,
0.008691891096532345,
-0.0074074226431548595,
0.049498338252305984,
0.022032948210835457,
-0.013251455500721931,
-0.057338692247867584,
0.08211895078420639,
-0.03767121583223343,
0.054088134318590164,
... |
https://github.com/scikit-learn/scikit-learn/issues/24606 | [
"Documentation"
] | MiniBatchDictionaryLearning confusion over U,V
### Describe the issue linked to the documentation
https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.MiniBatchDictionaryLearning.html
The optimization problem in the documentation is described as
$$
\arg\min \frac12 \Vert X-UV\Vert_F^2+\alpha... | 24,606 | [
0.028161974623799324,
0.0011692022671923041,
0.006826828233897686,
-0.023220708593726158,
0.008691891096532345,
-0.0074074226431548595,
0.049498338252305984,
0.022032948210835457,
-0.013251455500721931,
-0.057338692247867584,
0.08211895078420639,
-0.03767121583223343,
0.054088134318590164,
... |
https://github.com/scikit-learn/scikit-learn/issues/24604 | [
"Bug"
] | Not able to install on python 3.10 with pip
### Describe the bug
```
Windows 11
Python 3.10.4
pip installed
```
I'm not able to resolve dependencies issue while trying to install scikit-learn below the error output i get:
```bash
(InstallK) C:\Users\XXXXXXX>pip install scikit-learn
Collecting scikit-learn... | 24,604 | [
0.029077112674713135,
-0.03595259040594101,
-0.016492510214447975,
-0.03719840943813324,
0.002411870751529932,
0.03336477652192116,
-0.01569237932562828,
0.029568729922175407,
0.04152166470885277,
-0.012214846909046173,
0.025555118918418884,
0.05602499470114708,
0.0022277014795690775,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24604 | [
"Bug"
] | Not able to install on python 3.10 with pip
### Describe the bug
```
Windows 11
Python 3.10.4
pip installed
```
I'm not able to resolve dependencies issue while trying to install scikit-learn below the error output i get:
```bash
(InstallK) C:\Users\XXXXXXX>pip install scikit-learn
Collecting scikit-learn... | 24,604 | [
0.029077112674713135,
-0.03595259040594101,
-0.016492510214447975,
-0.03719840943813324,
0.002411870751529932,
0.03336477652192116,
-0.01569237932562828,
0.029568729922175407,
0.04152166470885277,
-0.012214846909046173,
0.025555118918418884,
0.05602499470114708,
0.0022277014795690775,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24604 | [
"Bug"
] | Not able to install on python 3.10 with pip
### Describe the bug
```
Windows 11
Python 3.10.4
pip installed
```
I'm not able to resolve dependencies issue while trying to install scikit-learn below the error output i get:
```bash
(InstallK) C:\Users\XXXXXXX>pip install scikit-learn
Collecting scikit-learn... | 24,604 | [
0.029077112674713135,
-0.03595259040594101,
-0.016492510214447975,
-0.03719840943813324,
0.002411870751529932,
0.03336477652192116,
-0.01569237932562828,
0.029568729922175407,
0.04152166470885277,
-0.012214846909046173,
0.025555118918418884,
0.05602499470114708,
0.0022277014795690775,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24604 | [
"Bug"
] | Not able to install on python 3.10 with pip
### Describe the bug
```
Windows 11
Python 3.10.4
pip installed
```
I'm not able to resolve dependencies issue while trying to install scikit-learn below the error output i get:
```bash
(InstallK) C:\Users\XXXXXXX>pip install scikit-learn
Collecting scikit-learn... | 24,604 | [
0.029077112674713135,
-0.03595259040594101,
-0.016492510214447975,
-0.03719840943813324,
0.002411870751529932,
0.03336477652192116,
-0.01569237932562828,
0.029568729922175407,
0.04152166470885277,
-0.012214846909046173,
0.025555118918418884,
0.05602499470114708,
0.0022277014795690775,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24604 | [
"Bug"
] | Not able to install on python 3.10 with pip
### Describe the bug
```
Windows 11
Python 3.10.4
pip installed
```
I'm not able to resolve dependencies issue while trying to install scikit-learn below the error output i get:
```bash
(InstallK) C:\Users\XXXXXXX>pip install scikit-learn
Collecting scikit-learn... | 24,604 | [
0.029077112674713135,
-0.03595259040594101,
-0.016492510214447975,
-0.03719840943813324,
0.002411870751529932,
0.03336477652192116,
-0.01569237932562828,
0.029568729922175407,
0.04152166470885277,
-0.012214846909046173,
0.025555118918418884,
0.05602499470114708,
0.0022277014795690775,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24604 | [
"Bug"
] | Not able to install on python 3.10 with pip
### Describe the bug
```
Windows 11
Python 3.10.4
pip installed
```
I'm not able to resolve dependencies issue while trying to install scikit-learn below the error output i get:
```bash
(InstallK) C:\Users\XXXXXXX>pip install scikit-learn
Collecting scikit-learn... | 24,604 | [
0.029077112674713135,
-0.03595259040594101,
-0.016492510214447975,
-0.03719840943813324,
0.002411870751529932,
0.03336477652192116,
-0.01569237932562828,
0.029568729922175407,
0.04152166470885277,
-0.012214846909046173,
0.025555118918418884,
0.05602499470114708,
0.0022277014795690775,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24604 | [
"Bug"
] | Not able to install on python 3.10 with pip
### Describe the bug
```
Windows 11
Python 3.10.4
pip installed
```
I'm not able to resolve dependencies issue while trying to install scikit-learn below the error output i get:
```bash
(InstallK) C:\Users\XXXXXXX>pip install scikit-learn
Collecting scikit-learn... | 24,604 | [
0.029077112674713135,
-0.03595259040594101,
-0.016492510214447975,
-0.03719840943813324,
0.002411870751529932,
0.03336477652192116,
-0.01569237932562828,
0.029568729922175407,
0.04152166470885277,
-0.012214846909046173,
0.025555118918418884,
0.05602499470114708,
0.0022277014795690775,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24604 | [
"Bug"
] | Not able to install on python 3.10 with pip
### Describe the bug
```
Windows 11
Python 3.10.4
pip installed
```
I'm not able to resolve dependencies issue while trying to install scikit-learn below the error output i get:
```bash
(InstallK) C:\Users\XXXXXXX>pip install scikit-learn
Collecting scikit-learn... | 24,604 | [
0.029077112674713135,
-0.03595259040594101,
-0.016492510214447975,
-0.03719840943813324,
0.002411870751529932,
0.03336477652192116,
-0.01569237932562828,
0.029568729922175407,
0.04152166470885277,
-0.012214846909046173,
0.025555118918418884,
0.05602499470114708,
0.0022277014795690775,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24604 | [
"Bug"
] | Not able to install on python 3.10 with pip
### Describe the bug
```
Windows 11
Python 3.10.4
pip installed
```
I'm not able to resolve dependencies issue while trying to install scikit-learn below the error output i get:
```bash
(InstallK) C:\Users\XXXXXXX>pip install scikit-learn
Collecting scikit-learn... | 24,604 | [
0.029077112674713135,
-0.03595259040594101,
-0.016492510214447975,
-0.03719840943813324,
0.002411870751529932,
0.03336477652192116,
-0.01569237932562828,
0.029568729922175407,
0.04152166470885277,
-0.012214846909046173,
0.025555118918418884,
0.05602499470114708,
0.0022277014795690775,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24604 | [
"Bug"
] | Not able to install on python 3.10 with pip
### Describe the bug
```
Windows 11
Python 3.10.4
pip installed
```
I'm not able to resolve dependencies issue while trying to install scikit-learn below the error output i get:
```bash
(InstallK) C:\Users\XXXXXXX>pip install scikit-learn
Collecting scikit-learn... | 24,604 | [
0.029077112674713135,
-0.03595259040594101,
-0.016492510214447975,
-0.03719840943813324,
0.002411870751529932,
0.03336477652192116,
-0.01569237932562828,
0.029568729922175407,
0.04152166470885277,
-0.012214846909046173,
0.025555118918418884,
0.05602499470114708,
0.0022277014795690775,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24604 | [
"Bug"
] | Not able to install on python 3.10 with pip
### Describe the bug
```
Windows 11
Python 3.10.4
pip installed
```
I'm not able to resolve dependencies issue while trying to install scikit-learn below the error output i get:
```bash
(InstallK) C:\Users\XXXXXXX>pip install scikit-learn
Collecting scikit-learn... | 24,604 | [
0.029077112674713135,
-0.03595259040594101,
-0.016492510214447975,
-0.03719840943813324,
0.002411870751529932,
0.03336477652192116,
-0.01569237932562828,
0.029568729922175407,
0.04152166470885277,
-0.012214846909046173,
0.025555118918418884,
0.05602499470114708,
0.0022277014795690775,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24604 | [
"Bug"
] | Not able to install on python 3.10 with pip
### Describe the bug
```
Windows 11
Python 3.10.4
pip installed
```
I'm not able to resolve dependencies issue while trying to install scikit-learn below the error output i get:
```bash
(InstallK) C:\Users\XXXXXXX>pip install scikit-learn
Collecting scikit-learn... | 24,604 | [
0.029077112674713135,
-0.03595259040594101,
-0.016492510214447975,
-0.03719840943813324,
0.002411870751529932,
0.03336477652192116,
-0.01569237932562828,
0.029568729922175407,
0.04152166470885277,
-0.012214846909046173,
0.025555118918418884,
0.05602499470114708,
0.0022277014795690775,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24601 | [
"New Feature",
"module:linear_model"
] | Add tolerance `tol` to LinearRegression for sparse matrix solver lsqr
===BEGIN EDIT===
## Description
`LinearRegression` should have a parameter `tol` that is passed to the LSQR routine for solving with sparse matrices. This way, it should be (more or less) equal to `Ridge(alpha=0, sol="lsqr", tol=..)`
===END EDIT=... | 24,601 | [
-0.007877988740801811,
0.06199351325631142,
0.036574821919202805,
0.03845161572098732,
0.06122852861881256,
-0.005763284396380186,
0.055005256086587906,
0.10032910108566284,
0.01628662645816803,
-0.007667233236134052,
0.012475602328777313,
0.05708343908190727,
0.006928116083145142,
0.02816... |
https://github.com/scikit-learn/scikit-learn/issues/24601 | [
"New Feature",
"module:linear_model"
] | Add tolerance `tol` to LinearRegression for sparse matrix solver lsqr
===BEGIN EDIT===
## Description
`LinearRegression` should have a parameter `tol` that is passed to the LSQR routine for solving with sparse matrices. This way, it should be (more or less) equal to `Ridge(alpha=0, sol="lsqr", tol=..)`
===END EDIT=... | 24,601 | [
-0.007877988740801811,
0.06199351325631142,
0.036574821919202805,
0.03845161572098732,
0.06122852861881256,
-0.005763284396380186,
0.055005256086587906,
0.10032910108566284,
0.01628662645816803,
-0.007667233236134052,
0.012475602328777313,
0.05708343908190727,
0.006928116083145142,
0.02816... |
https://github.com/scikit-learn/scikit-learn/issues/24601 | [
"New Feature",
"module:linear_model"
] | Add tolerance `tol` to LinearRegression for sparse matrix solver lsqr
===BEGIN EDIT===
## Description
`LinearRegression` should have a parameter `tol` that is passed to the LSQR routine for solving with sparse matrices. This way, it should be (more or less) equal to `Ridge(alpha=0, sol="lsqr", tol=..)`
===END EDIT=... | 24,601 | [
-0.007877988740801811,
0.06199351325631142,
0.036574821919202805,
0.03845161572098732,
0.06122852861881256,
-0.005763284396380186,
0.055005256086587906,
0.10032910108566284,
0.01628662645816803,
-0.007667233236134052,
0.012475602328777313,
0.05708343908190727,
0.006928116083145142,
0.02816... |
https://github.com/scikit-learn/scikit-learn/issues/24597 | [
"module:metrics"
] | Remove `sum_over_features` from `sklearn.metrics.manhattan_distances`
`sklearn.metrics.manhattan_distances` with `sum_over_features=False` does not return distances, looks unused, and is also unlikely used by users.
I think the behavior for `sum_over_features=True` should be the unique one for `manhattan_distances`... | 24,597 | [
-0.01818825863301754,
0.06470363587141037,
0.030551422387361526,
0.010960937477648258,
0.03182827681303024,
0.043822359293699265,
0.05223020911216736,
0.011519022285938263,
0.011249808594584465,
-0.0007616638904437423,
0.038788776844739914,
0.054193783551454544,
0.04840998351573944,
0.0331... |
https://github.com/scikit-learn/scikit-learn/issues/24597 | [
"module:metrics"
] | Remove `sum_over_features` from `sklearn.metrics.manhattan_distances`
`sklearn.metrics.manhattan_distances` with `sum_over_features=False` does not return distances, looks unused, and is also unlikely used by users.
I think the behavior for `sum_over_features=True` should be the unique one for `manhattan_distances`... | 24,597 | [
0.00583435595035553,
0.10013604909181595,
0.02223319001495838,
-0.01450536958873272,
0.034033533185720444,
0.01743246242403984,
0.04111520200967789,
-0.010600308887660503,
0.01849493198096752,
0.004651341121643782,
0.05514654517173767,
0.06964797526597977,
0.032362524420022964,
0.023656638... |
https://github.com/scikit-learn/scikit-learn/issues/24597 | [
"module:metrics"
] | Remove `sum_over_features` from `sklearn.metrics.manhattan_distances`
`sklearn.metrics.manhattan_distances` with `sum_over_features=False` does not return distances, looks unused, and is also unlikely used by users.
I think the behavior for `sum_over_features=True` should be the unique one for `manhattan_distances`... | 24,597 | [
-0.0139267947524786,
0.08955642580986023,
0.027509508654475212,
-0.004508426878601313,
0.02595818042755127,
0.04132740944623947,
0.04483268782496452,
0.0035731664393097162,
0.0071412017568945885,
-0.003798362100496888,
0.047323908656835556,
0.055973220616579056,
0.04614836722612381,
0.0455... |
https://github.com/scikit-learn/scikit-learn/issues/24596 | [
"Bug",
"Needs Triage"
] | `LabelEncoder` is not compatible with `Pipeline`
### Describe the bug
Using the `LabelEncoder` inside a pipeline leads to errors.
The possible solution could be to introduce an auxiliary parameter to the `fit` function, similarly as it was done for `OneHotEncoder`:
https://github.com/scikit-learn/scikit-learn/b... | 24,596 | [
-0.017792556434869766,
0.026796991005539894,
0.0033227845560759306,
-0.020852722227573395,
0.07718342542648315,
-0.010324150323867798,
0.021188056096434593,
0.02314438670873642,
0.01104747410863638,
-0.01337522454559803,
0.042197782546281815,
0.05186018720269203,
0.022899679839611053,
0.06... |
https://github.com/scikit-learn/scikit-learn/issues/24596 | [
"Bug",
"Needs Triage"
] | `LabelEncoder` is not compatible with `Pipeline`
### Describe the bug
Using the `LabelEncoder` inside a pipeline leads to errors.
The possible solution could be to introduce an auxiliary parameter to the `fit` function, similarly as it was done for `OneHotEncoder`:
https://github.com/scikit-learn/scikit-learn/b... | 24,596 | [
-0.017792556434869766,
0.026796991005539894,
0.0033227845560759306,
-0.020852722227573395,
0.07718342542648315,
-0.010324150323867798,
0.021188056096434593,
0.02314438670873642,
0.01104747410863638,
-0.01337522454559803,
0.042197782546281815,
0.05186018720269203,
0.022899679839611053,
0.06... |
https://github.com/scikit-learn/scikit-learn/issues/24593 | [
"Documentation"
] | Erroneous use of chi2 in the documentation
### Describe the issue linked to the documentation
The [documentation page](https://scikit-learn.org/stable/modules/feature_selection.html#univariate-feature-selection) for univariate feature selection suggests that the [`sklearn.feature_selection.chi2`](https://github.com... | 24,593 | [
-0.009248240850865841,
0.027471886947751045,
-0.007270566187798977,
-0.02247435599565506,
-0.02594442293047905,
0.04681713879108429,
0.10583724826574326,
0.0011621060548350215,
0.0011178608983755112,
0.018761876970529556,
0.02401755377650261,
0.020563649013638496,
0.08803927153348923,
0.04... |
https://github.com/scikit-learn/scikit-learn/issues/24580 | [
"Needs Triage"
] | Migrating from LGTM, or removng it
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/24578
<div type='discussions-op-text'>
<sup>Originally posted by **haiatn** October 4, 2022</sup>
Hi,
I read LGTM will shut down and we have all PRs scanned by it,
It could be replaced with Github Cod... | 24,580 | [
0.031548917293548584,
0.06167725473642349,
0.017883524298667908,
-0.0018179736798629165,
-0.03447207063436508,
0.021493420004844666,
0.017298061400651932,
0.01643357053399086,
0.016257578507065773,
-0.026090754196047783,
-0.004321604501456022,
0.04741277918219566,
-0.0317901112139225,
0.03... |
https://github.com/scikit-learn/scikit-learn/issues/24580 | [
"Needs Triage"
] | Migrating from LGTM, or removng it
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/24578
<div type='discussions-op-text'>
<sup>Originally posted by **haiatn** October 4, 2022</sup>
Hi,
I read LGTM will shut down and we have all PRs scanned by it,
It could be replaced with Github Cod... | 24,580 | [
0.01634174771606922,
0.07255002111196518,
0.019989345222711563,
-0.014503474347293377,
-0.010372173972427845,
0.027805887162685394,
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-0.026921002194285393,
0.020077520981431007,
0.05497768148779869,
-0.045866772532463074,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24580 | [
"Needs Triage"
] | Migrating from LGTM, or removng it
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/24578
<div type='discussions-op-text'>
<sup>Originally posted by **haiatn** October 4, 2022</sup>
Hi,
I read LGTM will shut down and we have all PRs scanned by it,
It could be replaced with Github Cod... | 24,580 | [
0.012807408347725868,
0.07069698721170425,
0.01614152453839779,
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0.05285... |
https://github.com/scikit-learn/scikit-learn/issues/24580 | [
"Needs Triage"
] | Migrating from LGTM, or removng it
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/24578
<div type='discussions-op-text'>
<sup>Originally posted by **haiatn** October 4, 2022</sup>
Hi,
I read LGTM will shut down and we have all PRs scanned by it,
It could be replaced with Github Cod... | 24,580 | [
0.029936479404568672,
0.08037403225898743,
0.014077081345021725,
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-0.05668773129582405,
0.0591... |
https://github.com/scikit-learn/scikit-learn/issues/24580 | [
"Needs Triage"
] | Migrating from LGTM, or removng it
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/24578
<div type='discussions-op-text'>
<sup>Originally posted by **haiatn** October 4, 2022</sup>
Hi,
I read LGTM will shut down and we have all PRs scanned by it,
It could be replaced with Github Cod... | 24,580 | [
0.017181694507598877,
0.06964294612407684,
0.010959471575915813,
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0.05595474690198898,
-0.05127158388495445,
0.061... |
https://github.com/scikit-learn/scikit-learn/issues/24580 | [
"Needs Triage"
] | Migrating from LGTM, or removng it
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/24578
<div type='discussions-op-text'>
<sup>Originally posted by **haiatn** October 4, 2022</sup>
Hi,
I read LGTM will shut down and we have all PRs scanned by it,
It could be replaced with Github Cod... | 24,580 | [
0.01187597680836916,
0.07426957786083221,
0.008115557953715324,
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0.054548703134059906,
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0.06315... |
https://github.com/scikit-learn/scikit-learn/issues/24577 | [
"RFC",
"module:ensemble",
"module:tree",
"cython",
"Refactor"
] | [RFC] Modularize 'Criterion' class inside tree submodule to allow 3rd party extensions for data-based criterion
### Summary
There exists other criterions, where additional arguments would need to be passed in. The current `Criterion` class is not actually a generic Criterion class since it explicitly assumes that t... | 24,577 | [
0.014177932403981686,
0.09590549021959305,
0.032109737396240234,
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0.03038860857486725,
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-0.026821041479706764,
0.03395097702741623,
-0.046221714466810226,
-... |
https://github.com/scikit-learn/scikit-learn/issues/24577 | [
"RFC",
"module:ensemble",
"module:tree",
"cython",
"Refactor"
] | [RFC] Modularize 'Criterion' class inside tree submodule to allow 3rd party extensions for data-based criterion
### Summary
There exists other criterions, where additional arguments would need to be passed in. The current `Criterion` class is not actually a generic Criterion class since it explicitly assumes that t... | 24,577 | [
0.014177932403981686,
0.09590549021959305,
0.032109737396240234,
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0.03038860857486725,
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-0.026821041479706764,
0.03395097702741623,
-0.046221714466810226,
-... |
https://github.com/scikit-learn/scikit-learn/issues/24577 | [
"RFC",
"module:ensemble",
"module:tree",
"cython",
"Refactor"
] | [RFC] Modularize 'Criterion' class inside tree submodule to allow 3rd party extensions for data-based criterion
### Summary
There exists other criterions, where additional arguments would need to be passed in. The current `Criterion` class is not actually a generic Criterion class since it explicitly assumes that t... | 24,577 | [
0.014177932403981686,
0.09590549021959305,
0.032109737396240234,
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0.03038860857486725,
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-0.03788566216826439,
-0.026821041479706764,
0.03395097702741623,
-0.046221714466810226,
-... |
https://github.com/scikit-learn/scikit-learn/issues/24577 | [
"RFC",
"module:ensemble",
"module:tree",
"cython",
"Refactor"
] | [RFC] Modularize 'Criterion' class inside tree submodule to allow 3rd party extensions for data-based criterion
### Summary
There exists other criterions, where additional arguments would need to be passed in. The current `Criterion` class is not actually a generic Criterion class since it explicitly assumes that t... | 24,577 | [
0.014177932403981686,
0.09590549021959305,
0.032109737396240234,
-0.015447103418409824,
0.03038860857486725,
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-0.006430755369365215,
-0.0179662574082613,
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-0.03788566216826439,
-0.026821041479706764,
0.03395097702741623,
-0.046221714466810226,
-... |
https://github.com/scikit-learn/scikit-learn/issues/24577 | [
"RFC",
"module:ensemble",
"module:tree",
"cython",
"Refactor"
] | [RFC] Modularize 'Criterion' class inside tree submodule to allow 3rd party extensions for data-based criterion
### Summary
There exists other criterions, where additional arguments would need to be passed in. The current `Criterion` class is not actually a generic Criterion class since it explicitly assumes that t... | 24,577 | [
0.014177932403981686,
0.09590549021959305,
0.032109737396240234,
-0.015447103418409824,
0.03038860857486725,
-0.0030162823386490345,
-0.006430755369365215,
-0.0179662574082613,
-0.015537655912339687,
-0.03788566216826439,
-0.026821041479706764,
0.03395097702741623,
-0.046221714466810226,
-... |
https://github.com/scikit-learn/scikit-learn/issues/24577 | [
"RFC",
"module:ensemble",
"module:tree",
"cython",
"Refactor"
] | [RFC] Modularize 'Criterion' class inside tree submodule to allow 3rd party extensions for data-based criterion
### Summary
There exists other criterions, where additional arguments would need to be passed in. The current `Criterion` class is not actually a generic Criterion class since it explicitly assumes that t... | 24,577 | [
0.014177932403981686,
0.09590549021959305,
0.032109737396240234,
-0.015447103418409824,
0.03038860857486725,
-0.0030162823386490345,
-0.006430755369365215,
-0.0179662574082613,
-0.015537655912339687,
-0.03788566216826439,
-0.026821041479706764,
0.03395097702741623,
-0.046221714466810226,
-... |
https://github.com/scikit-learn/scikit-learn/issues/24577 | [
"RFC",
"module:ensemble",
"module:tree",
"cython",
"Refactor"
] | [RFC] Modularize 'Criterion' class inside tree submodule to allow 3rd party extensions for data-based criterion
### Summary
There exists other criterions, where additional arguments would need to be passed in. The current `Criterion` class is not actually a generic Criterion class since it explicitly assumes that t... | 24,577 | [
0.014177932403981686,
0.09590549021959305,
0.032109737396240234,
-0.015447103418409824,
0.03038860857486725,
-0.0030162823386490345,
-0.006430755369365215,
-0.0179662574082613,
-0.015537655912339687,
-0.03788566216826439,
-0.026821041479706764,
0.03395097702741623,
-0.046221714466810226,
-... |
https://github.com/scikit-learn/scikit-learn/issues/24575 | [
"New Feature",
"Needs Triage"
] | Remove parsar parameter from fetch_openml()
### Describe the workflow you want to enable
data = fetch_openml("mnist_784", as_frame=True, parser="pandas") It cause error while running the
sklearn/benchmarks/bench_mnist.py file
### Describe your proposed solution
data = fetch_openml("mnist_784", as_frame=True) It ... | 24,575 | [
-0.00961832795292139,
0.053043536841869354,
0.009486821480095387,
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0.010039723478257656,
0.03756525740027428,
0.03635735437273979,
0.02441597171127796,
-0.024608517065644264,
-0.018161894753575325,
0.09254390001296997,
0.00019645647262223065,
0.024... |
https://github.com/scikit-learn/scikit-learn/issues/24575 | [
"New Feature",
"Needs Triage"
] | Remove parsar parameter from fetch_openml()
### Describe the workflow you want to enable
data = fetch_openml("mnist_784", as_frame=True, parser="pandas") It cause error while running the
sklearn/benchmarks/bench_mnist.py file
### Describe your proposed solution
data = fetch_openml("mnist_784", as_frame=True) It ... | 24,575 | [
-0.001624297583475709,
0.037730611860752106,
0.008138882927596569,
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0.040951892733573914,
0.03683078661561012,
0.03153752163052559,
-0.024321675300598145,
-0.014551473781466484,
0.090273916721344,
0.0019100779900327325,
0.029476... |
https://github.com/scikit-learn/scikit-learn/issues/24574 | [
"New Feature",
"Needs Decision - Include Feature"
] | KNearestNeighbors dedicated API for unsupervised anomaly detection
### Describe the workflow you want to enable
All unsupervised anomaly detection algorithms share a similar API (e.g., IsolationForest, OneSVM) but not KNearestNeighbors... And yet, KNN is one of the most used and robust method. (https://arxiv.org/pdf... | 24,574 | [
-0.007487054914236069,
-0.005718559492379427,
0.015609050169587135,
0.03394709900021553,
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0.01644797809422016,
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0.021192755550146103,
0.01981934905052185,
0.08401727676391602,
-0.07654158025979996,
0.047903... |
https://github.com/scikit-learn/scikit-learn/issues/24574 | [
"New Feature",
"Needs Decision - Include Feature"
] | KNearestNeighbors dedicated API for unsupervised anomaly detection
### Describe the workflow you want to enable
All unsupervised anomaly detection algorithms share a similar API (e.g., IsolationForest, OneSVM) but not KNearestNeighbors... And yet, KNN is one of the most used and robust method. (https://arxiv.org/pdf... | 24,574 | [
-0.007487054914236069,
-0.005718559492379427,
0.015609050169587135,
0.03394709900021553,
-0.03468086197972298,
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0.05066591128706932,
0.01644797809422016,
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0.021192755550146103,
0.01981934905052185,
0.08401727676391602,
-0.07654158025979996,
0.047903... |
https://github.com/scikit-learn/scikit-learn/issues/24574 | [
"New Feature",
"Needs Decision - Include Feature"
] | KNearestNeighbors dedicated API for unsupervised anomaly detection
### Describe the workflow you want to enable
All unsupervised anomaly detection algorithms share a similar API (e.g., IsolationForest, OneSVM) but not KNearestNeighbors... And yet, KNN is one of the most used and robust method. (https://arxiv.org/pdf... | 24,574 | [
-0.007487054914236069,
-0.005718559492379427,
0.015609050169587135,
0.03394709900021553,
-0.03468086197972298,
0.000608145201113075,
0.05066591128706932,
0.01644797809422016,
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0.021192755550146103,
0.01981934905052185,
0.08401727676391602,
-0.07654158025979996,
0.047903... |
https://github.com/scikit-learn/scikit-learn/issues/24574 | [
"New Feature",
"Needs Decision - Include Feature"
] | KNearestNeighbors dedicated API for unsupervised anomaly detection
### Describe the workflow you want to enable
All unsupervised anomaly detection algorithms share a similar API (e.g., IsolationForest, OneSVM) but not KNearestNeighbors... And yet, KNN is one of the most used and robust method. (https://arxiv.org/pdf... | 24,574 | [
-0.007487054914236069,
-0.005718559492379427,
0.015609050169587135,
0.03394709900021553,
-0.03468086197972298,
0.000608145201113075,
0.05066591128706932,
0.01644797809422016,
0.07133905589580536,
0.021192755550146103,
0.01981934905052185,
0.08401727676391602,
-0.07654158025979996,
0.047903... |
https://github.com/scikit-learn/scikit-learn/issues/24574 | [
"New Feature",
"Needs Decision - Include Feature"
] | KNearestNeighbors dedicated API for unsupervised anomaly detection
### Describe the workflow you want to enable
All unsupervised anomaly detection algorithms share a similar API (e.g., IsolationForest, OneSVM) but not KNearestNeighbors... And yet, KNN is one of the most used and robust method. (https://arxiv.org/pdf... | 24,574 | [
-0.007487054914236069,
-0.005718559492379427,
0.015609050169587135,
0.03394709900021553,
-0.03468086197972298,
0.000608145201113075,
0.05066591128706932,
0.01644797809422016,
0.07133905589580536,
0.021192755550146103,
0.01981934905052185,
0.08401727676391602,
-0.07654158025979996,
0.047903... |
https://github.com/scikit-learn/scikit-learn/issues/24574 | [
"New Feature",
"Needs Decision - Include Feature"
] | KNearestNeighbors dedicated API for unsupervised anomaly detection
### Describe the workflow you want to enable
All unsupervised anomaly detection algorithms share a similar API (e.g., IsolationForest, OneSVM) but not KNearestNeighbors... And yet, KNN is one of the most used and robust method. (https://arxiv.org/pdf... | 24,574 | [
-0.007487054914236069,
-0.005718559492379427,
0.015609050169587135,
0.03394709900021553,
-0.03468086197972298,
0.000608145201113075,
0.05066591128706932,
0.01644797809422016,
0.07133905589580536,
0.021192755550146103,
0.01981934905052185,
0.08401727676391602,
-0.07654158025979996,
0.047903... |
https://github.com/scikit-learn/scikit-learn/issues/24573 | [
"Bug",
"Needs Triage"
] | NaNs and Infs when decomposing EDS
### Describe the bug
### Steps/Code to Reproduce
#... | 24,573 | [
-0.020725097507238388,
-0.03212616592645645,
0.008654221892356873,
0.03894415497779846,
0.11291495710611343,
0.009678084403276443,
-0.002959524979814887,
0.011558550409972668,
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0.025721391662955284,
-0.010220170952379704,
0.04465615376830101,
0.019206251949071884,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24573 | [
"Bug",
"Needs Triage"
] | NaNs and Infs when decomposing EDS
### Describe the bug
### Steps/Code to Reproduce
#... | 24,573 | [
-0.020725097507238388,
-0.03212616592645645,
0.008654221892356873,
0.03894415497779846,
0.11291495710611343,
0.009678084403276443,
-0.002959524979814887,
0.011558550409972668,
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0.025721391662955284,
-0.010220170952379704,
0.04465615376830101,
0.019206251949071884,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24573 | [
"Bug",
"Needs Triage"
] | NaNs and Infs when decomposing EDS
### Describe the bug
### Steps/Code to Reproduce
#... | 24,573 | [
-0.020725097507238388,
-0.03212616592645645,
0.008654221892356873,
0.03894415497779846,
0.11291495710611343,
0.009678084403276443,
-0.002959524979814887,
0.011558550409972668,
-0.061201293021440506,
0.025721391662955284,
-0.010220170952379704,
0.04465615376830101,
0.019206251949071884,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24573 | [
"Bug",
"Needs Triage"
] | NaNs and Infs when decomposing EDS
### Describe the bug
### Steps/Code to Reproduce
#... | 24,573 | [
-0.020725097507238388,
-0.03212616592645645,
0.008654221892356873,
0.03894415497779846,
0.11291495710611343,
0.009678084403276443,
-0.002959524979814887,
0.011558550409972668,
-0.061201293021440506,
0.025721391662955284,
-0.010220170952379704,
0.04465615376830101,
0.019206251949071884,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24573 | [
"Bug",
"Needs Triage"
] | NaNs and Infs when decomposing EDS
### Describe the bug
### Steps/Code to Reproduce
#... | 24,573 | [
-0.020725097507238388,
-0.03212616592645645,
0.008654221892356873,
0.03894415497779846,
0.11291495710611343,
0.009678084403276443,
-0.002959524979814887,
0.011558550409972668,
-0.061201293021440506,
0.025721391662955284,
-0.010220170952379704,
0.04465615376830101,
0.019206251949071884,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24573 | [
"Bug",
"Needs Triage"
] | NaNs and Infs when decomposing EDS
### Describe the bug
### Steps/Code to Reproduce
#... | 24,573 | [
-0.020725097507238388,
-0.03212616592645645,
0.008654221892356873,
0.03894415497779846,
0.11291495710611343,
0.009678084403276443,
-0.002959524979814887,
0.011558550409972668,
-0.061201293021440506,
0.025721391662955284,
-0.010220170952379704,
0.04465615376830101,
0.019206251949071884,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24565 | [
"Performance",
"module:cluster",
"cython"
] | ENH Avoid memoryviews' slicing for `KMeans` Cython implementations
### Summary
Addresses issues raised in https://github.com/scikit-learn/scikit-learn/issues/17299
The proposal is to modify the LOC here: https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/cluster/_k_means_common.pyx#L155-L159. There a... | 24,565 | [
-0.0264718197286129,
-0.011432299390435219,
-0.028884608298540115,
0.02432619035243988,
0.025562820956110954,
-0.00167752243578434,
0.01498220581561327,
-0.001009510480798781,
-0.03350856527686119,
-0.035643916577100754,
0.018176522105932236,
0.023461587727069855,
-0.025148829445242882,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/24565 | [
"Performance",
"module:cluster",
"cython"
] | ENH Avoid memoryviews' slicing for `KMeans` Cython implementations
### Summary
Addresses issues raised in https://github.com/scikit-learn/scikit-learn/issues/17299
The proposal is to modify the LOC here: https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/cluster/_k_means_common.pyx#L155-L159. There a... | 24,565 | [
-0.028069285675883293,
-0.011265377514064312,
-0.028364498168230057,
0.023611007258296013,
0.02728777937591076,
-0.0032927640713751316,
0.011733729392290115,
-0.0012687062844634056,
-0.0392778106033802,
-0.0314348079264164,
0.022548053413629532,
0.02316470444202423,
-0.024713050574064255,
... |
https://github.com/scikit-learn/scikit-learn/issues/24565 | [
"Performance",
"module:cluster",
"cython"
] | ENH Avoid memoryviews' slicing for `KMeans` Cython implementations
### Summary
Addresses issues raised in https://github.com/scikit-learn/scikit-learn/issues/17299
The proposal is to modify the LOC here: https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/cluster/_k_means_common.pyx#L155-L159. There a... | 24,565 | [
-0.028438912704586983,
-0.011940172873437405,
-0.027715682983398438,
0.021958863362669945,
0.02402886562049389,
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0.014588974416255951,
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0.020774250850081444,
0.021775035187602043,
-0.024605199694633484,
... |
https://github.com/scikit-learn/scikit-learn/issues/24565 | [
"Performance",
"module:cluster",
"cython"
] | ENH Avoid memoryviews' slicing for `KMeans` Cython implementations
### Summary
Addresses issues raised in https://github.com/scikit-learn/scikit-learn/issues/17299
The proposal is to modify the LOC here: https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/cluster/_k_means_common.pyx#L155-L159. There a... | 24,565 | [
-0.02689915895462036,
-0.008380504325032234,
-0.02648235484957695,
0.022582441568374634,
0.02449367754161358,
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0.011315042153000832,
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-0.03252563998103142,
0.021570812910795212,
0.02103472128510475,
-0.02430705912411213,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24564 | [
"Bug",
"Needs Triage"
] | convert builtin module import to supported form
### Describe the bug
convert builtin module import to supported form
### Steps/Code to Reproduce
import builtins as builtins
### Expected Results
No error is thrown
### Actual Results
import builtins as builtins
### Versions
```shell
import builtins as builtins
... | 24,564 | [
-0.035716790705919266,
-0.01138139609247446,
-0.02357778139412403,
-0.021027803421020508,
0.005506479647010565,
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0.029367128387093544,
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0.07758861780166626,
-0.022995000705122948,
0.013377198949456215,
0.03927423804998398,
0.03190898895263672,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/24558 | [
"Documentation",
"good first issue"
] | SelfTrainingClassifier: use of warm_start in base_estimator
### Describe the issue linked to the documentation
Hi,
I construct an instance of SelfTrainingClassifier with a base_constructor having warm_start set as True. When calling fit in SelfTrainingClassifier, is the classifier trained incrementally, or at every ... | 24,558 | [
-0.04684028401970863,
-0.0036565486807376146,
0.036659467965364456,
0.011872430332005024,
0.01564008742570877,
0.006592525634914637,
0.03763002157211304,
-0.0208797175437212,
-0.03675506263971329,
-0.018627813085913658,
0.008872662670910358,
0.03557676076889038,
0.021320166066288948,
0.023... |
https://github.com/scikit-learn/scikit-learn/issues/24558 | [
"Documentation",
"good first issue"
] | SelfTrainingClassifier: use of warm_start in base_estimator
### Describe the issue linked to the documentation
Hi,
I construct an instance of SelfTrainingClassifier with a base_constructor having warm_start set as True. When calling fit in SelfTrainingClassifier, is the classifier trained incrementally, or at every ... | 24,558 | [
-0.07031344622373581,
-0.009225927293300629,
0.02860303781926632,
0.022396918386220932,
0.01304103247821331,
0.020682254806160927,
0.023307936266064644,
-0.024057794362306595,
-0.0030307641718536615,
-0.016215208917856216,
0.025530150160193443,
0.013545566238462925,
0.006369309034198523,
0... |
https://github.com/scikit-learn/scikit-learn/issues/24558 | [
"Documentation",
"good first issue"
] | SelfTrainingClassifier: use of warm_start in base_estimator
### Describe the issue linked to the documentation
Hi,
I construct an instance of SelfTrainingClassifier with a base_constructor having warm_start set as True. When calling fit in SelfTrainingClassifier, is the classifier trained incrementally, or at every ... | 24,558 | [
-0.0724203959107399,
-0.0152507983148098,
0.03011286072432995,
0.018641412258148193,
0.015131042338907719,
0.022662270814180374,
0.019351528957486153,
-0.022702403366565704,
-0.002865626709535718,
-0.012079846113920212,
0.025817351415753365,
0.011810079216957092,
0.0074906726367771626,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24558 | [
"Documentation",
"good first issue"
] | SelfTrainingClassifier: use of warm_start in base_estimator
### Describe the issue linked to the documentation
Hi,
I construct an instance of SelfTrainingClassifier with a base_constructor having warm_start set as True. When calling fit in SelfTrainingClassifier, is the classifier trained incrementally, or at every ... | 24,558 | [
-0.07104688882827759,
-0.0204743854701519,
0.03021806851029396,
0.01913558319211006,
0.015256310813128948,
0.023322898894548416,
0.017783483490347862,
-0.02308248169720173,
-0.0034650717861950397,
-0.01307861041277647,
0.02636750414967537,
0.012293619103729725,
0.007774943020194769,
0.0270... |
https://github.com/scikit-learn/scikit-learn/issues/24558 | [
"Documentation",
"good first issue"
] | SelfTrainingClassifier: use of warm_start in base_estimator
### Describe the issue linked to the documentation
Hi,
I construct an instance of SelfTrainingClassifier with a base_constructor having warm_start set as True. When calling fit in SelfTrainingClassifier, is the classifier trained incrementally, or at every ... | 24,558 | [
-0.06454387307167053,
-0.008863761089742184,
0.023862071335315704,
0.018218176439404488,
0.013746635057032108,
0.019105052575469017,
0.023305904120206833,
-0.02257182076573372,
-0.0038943705148994923,
-0.02036099135875702,
0.02867741510272026,
0.01720309816300869,
0.005097470246255398,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24558 | [
"Documentation",
"good first issue"
] | SelfTrainingClassifier: use of warm_start in base_estimator
### Describe the issue linked to the documentation
Hi,
I construct an instance of SelfTrainingClassifier with a base_constructor having warm_start set as True. When calling fit in SelfTrainingClassifier, is the classifier trained incrementally, or at every ... | 24,558 | [
-0.05692533776164055,
-0.01850559003651142,
0.03773929178714752,
0.013837756589055061,
0.018879109993577003,
0.02674543485045433,
0.03125959634780884,
-0.020440993830561638,
0.010102963075041771,
-0.01668773591518402,
0.03469762206077576,
0.02113300934433937,
0.013221110217273235,
0.039283... |
https://github.com/scikit-learn/scikit-learn/issues/24558 | [
"Documentation",
"good first issue"
] | SelfTrainingClassifier: use of warm_start in base_estimator
### Describe the issue linked to the documentation
Hi,
I construct an instance of SelfTrainingClassifier with a base_constructor having warm_start set as True. When calling fit in SelfTrainingClassifier, is the classifier trained incrementally, or at every ... | 24,558 | [
-0.06756047159433365,
-0.008114580065011978,
0.02858647145330906,
0.018125196918845177,
0.012486850842833519,
0.021502433344721794,
0.01957586407661438,
-0.023134581744670868,
-0.007109110709279776,
-0.018866637721657753,
0.028911376371979713,
0.009441830217838287,
0.006393349729478359,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/24558 | [
"Documentation",
"good first issue"
] | SelfTrainingClassifier: use of warm_start in base_estimator
### Describe the issue linked to the documentation
Hi,
I construct an instance of SelfTrainingClassifier with a base_constructor having warm_start set as True. When calling fit in SelfTrainingClassifier, is the classifier trained incrementally, or at every ... | 24,558 | [
-0.07027562707662582,
-0.009762507863342762,
0.028367217630147934,
0.017307037487626076,
0.015076611191034317,
0.021515339612960815,
0.022078895941376686,
-0.022115293890237808,
-0.005429565440863371,
-0.014327067881822586,
0.026705339550971985,
0.012530982494354248,
0.0038345190696418285,
... |
https://github.com/scikit-learn/scikit-learn/issues/24558 | [
"Documentation",
"good first issue"
] | SelfTrainingClassifier: use of warm_start in base_estimator
### Describe the issue linked to the documentation
Hi,
I construct an instance of SelfTrainingClassifier with a base_constructor having warm_start set as True. When calling fit in SelfTrainingClassifier, is the classifier trained incrementally, or at every ... | 24,558 | [
-0.06681567430496216,
-0.008398249745368958,
0.02529899962246418,
0.01851116679608822,
0.014692547731101513,
0.02253086119890213,
0.02643120102584362,
-0.023679738864302635,
-0.006978160236030817,
-0.020406166091561317,
0.030610699206590652,
0.01597071997821331,
0.006584916263818741,
0.037... |
https://github.com/scikit-learn/scikit-learn/issues/24558 | [
"Documentation",
"good first issue"
] | SelfTrainingClassifier: use of warm_start in base_estimator
### Describe the issue linked to the documentation
Hi,
I construct an instance of SelfTrainingClassifier with a base_constructor having warm_start set as True. When calling fit in SelfTrainingClassifier, is the classifier trained incrementally, or at every ... | 24,558 | [
-0.05702538415789604,
-0.01676873490214348,
0.039930470287799835,
0.015306063927710056,
0.016353106126189232,
0.029622811824083328,
0.029642993584275246,
-0.024058006703853607,
0.010356122627854347,
-0.014144948683679104,
0.03176111727952957,
0.020060570910573006,
0.013551960699260235,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24558 | [
"Documentation",
"good first issue"
] | SelfTrainingClassifier: use of warm_start in base_estimator
### Describe the issue linked to the documentation
Hi,
I construct an instance of SelfTrainingClassifier with a base_constructor having warm_start set as True. When calling fit in SelfTrainingClassifier, is the classifier trained incrementally, or at every ... | 24,558 | [
-0.06954091042280197,
-0.011318709701299667,
0.027132390066981316,
0.01696508191525936,
0.015196739695966244,
0.024106916040182114,
0.023404570296406746,
-0.023709872737526894,
-0.007242887280881405,
-0.01643437333405018,
0.026405008509755135,
0.010749727487564087,
0.008098023012280464,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/24552 | [
"New Feature",
"Needs Triage"
] | PolynomialFeatures: allow separate degrees for individual features
### Describe the workflow you want to enable
[PolynomialFeatures](https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.PolynomialFeatures.html#sklearn.preprocessing.PolynomialFeatures) allows a degree parameter, but the same param... | 24,552 | [
-0.03428139537572861,
0.042780499905347824,
0.026903966441750526,
0.01978970132768154,
0.05196688696742058,
0.00833199080079794,
0.03927433490753174,
0.00013983671669848263,
0.060965199023485184,
-0.03924071416258812,
0.0480697862803936,
0.02389623038470745,
-0.017112012952566147,
0.079632... |
https://github.com/scikit-learn/scikit-learn/issues/24549 | [
"Needs Triage"
] | There seems to be an unnecessary operation in _mutual_info.py
Hi,
In file `scikit-learn/sklearn/feature_selection/_mutual_info.py`, there seems to be an unnecessary operation.
At line 140 there is:
`m_all = np.array(m_all) - 1.0
`
But then when m_all is used at line 146
`np.mean(digamma(m_all + 1)
`
1 is ad... | 24,549 | [
0.016474898904561996,
-0.05323176831007004,
0.017400674521923065,
0.023239118978381157,
0.011336719617247581,
0.05466321110725403,
0.051999129354953766,
-0.05597081035375595,
-0.004055758938193321,
-0.0175361055880785,
0.013627254404127598,
0.055701497942209244,
0.04032621160149574,
-0.017... |
https://github.com/scikit-learn/scikit-learn/issues/24545 | [
"Bug"
] | Error when returning embedded transformers in Jupyter notebook
### Describe the bug
When creating a custom transformer object that includes a transformer type as an instance, a `TypeError` is thrown if the object is returned at the end of a Jupyter cell. This does not cause an error in the terminal, but raises an e... | 24,545 | [
0.008263093419373035,
-0.018807420507073402,
0.050946664065122604,
-0.01615101844072342,
0.0791250616312027,
-0.022738639265298843,
0.03379345312714577,
0.02156447246670723,
-0.022948475554585457,
-0.0372542142868042,
-0.009400779381394386,
0.04135395213961601,
0.03211659938097,
0.03257336... |
https://github.com/scikit-learn/scikit-learn/issues/24545 | [
"Bug"
] | Error when returning embedded transformers in Jupyter notebook
### Describe the bug
When creating a custom transformer object that includes a transformer type as an instance, a `TypeError` is thrown if the object is returned at the end of a Jupyter cell. This does not cause an error in the terminal, but raises an e... | 24,545 | [
0.008263093419373035,
-0.018807420507073402,
0.050946664065122604,
-0.01615101844072342,
0.0791250616312027,
-0.022738639265298843,
0.03379345312714577,
0.02156447246670723,
-0.022948475554585457,
-0.0372542142868042,
-0.009400779381394386,
0.04135395213961601,
0.03211659938097,
0.03257336... |
https://github.com/scikit-learn/scikit-learn/issues/24545 | [
"Bug"
] | Error when returning embedded transformers in Jupyter notebook
### Describe the bug
When creating a custom transformer object that includes a transformer type as an instance, a `TypeError` is thrown if the object is returned at the end of a Jupyter cell. This does not cause an error in the terminal, but raises an e... | 24,545 | [
0.008263093419373035,
-0.018807420507073402,
0.050946664065122604,
-0.01615101844072342,
0.0791250616312027,
-0.022738639265298843,
0.03379345312714577,
0.02156447246670723,
-0.022948475554585457,
-0.0372542142868042,
-0.009400779381394386,
0.04135395213961601,
0.03211659938097,
0.03257336... |
https://github.com/scikit-learn/scikit-learn/issues/24545 | [
"Bug"
] | Error when returning embedded transformers in Jupyter notebook
### Describe the bug
When creating a custom transformer object that includes a transformer type as an instance, a `TypeError` is thrown if the object is returned at the end of a Jupyter cell. This does not cause an error in the terminal, but raises an e... | 24,545 | [
0.008263093419373035,
-0.018807420507073402,
0.050946664065122604,
-0.01615101844072342,
0.0791250616312027,
-0.022738639265298843,
0.03379345312714577,
0.02156447246670723,
-0.022948475554585457,
-0.0372542142868042,
-0.009400779381394386,
0.04135395213961601,
0.03211659938097,
0.03257336... |
https://github.com/scikit-learn/scikit-learn/issues/24545 | [
"Bug"
] | Error when returning embedded transformers in Jupyter notebook
### Describe the bug
When creating a custom transformer object that includes a transformer type as an instance, a `TypeError` is thrown if the object is returned at the end of a Jupyter cell. This does not cause an error in the terminal, but raises an e... | 24,545 | [
0.008263093419373035,
-0.018807420507073402,
0.050946664065122604,
-0.01615101844072342,
0.0791250616312027,
-0.022738639265298843,
0.03379345312714577,
0.02156447246670723,
-0.022948475554585457,
-0.0372542142868042,
-0.009400779381394386,
0.04135395213961601,
0.03211659938097,
0.03257336... |
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