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|---|---|---|---|---|
https://github.com/scikit-learn/scikit-learn/issues/24228 | [
"module:neighbors",
"Needs Investigation"
] | Balltree's node_data radii seems to be incorrect
### Describe the bug
The node data from constructing a BallTree seems to be incorrect. Each parent node's radius should always be greater than or equal to both its child's radiuses, since the radius is that of the smallest hypersphere containing all the points within... | 24,228 | [
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https://github.com/scikit-learn/scikit-learn/issues/24228 | [
"module:neighbors",
"Needs Investigation"
] | Balltree's node_data radii seems to be incorrect
### Describe the bug
The node data from constructing a BallTree seems to be incorrect. Each parent node's radius should always be greater than or equal to both its child's radiuses, since the radius is that of the smallest hypersphere containing all the points within... | 24,228 | [
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https://github.com/scikit-learn/scikit-learn/issues/24221 | [
"Build / CI"
] | ⚠️ CI failed on Linux_nogil.pylatest_pip_nogil ⚠️
**CI failed on [Linux_nogil.pylatest_pip_nogil](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=45748&view=logs&j=67fbb25f-e417-50be-be55-3b1e9637fce5)** (Aug 22, 2022)
- test_kernel_gradient[kernel11]
COMMENT:
I can not reproduce this one local... | 24,221 | [
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https://github.com/scikit-learn/scikit-learn/issues/24221 | [
"Build / CI"
] | ⚠️ CI failed on Linux_nogil.pylatest_pip_nogil ⚠️
**CI failed on [Linux_nogil.pylatest_pip_nogil](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=45748&view=logs&j=67fbb25f-e417-50be-be55-3b1e9637fce5)** (Aug 22, 2022)
- test_kernel_gradient[kernel11]
COMMENT:
Note that this test also has `@fai... | 24,221 | [
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https://github.com/scikit-learn/scikit-learn/issues/24221 | [
"Build / CI"
] | ⚠️ CI failed on Linux_nogil.pylatest_pip_nogil ⚠️
**CI failed on [Linux_nogil.pylatest_pip_nogil](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=45748&view=logs&j=67fbb25f-e417-50be-be55-3b1e9637fce5)** (Aug 22, 2022)
- test_kernel_gradient[kernel11]
COMMENT:
I will manually retrigger this CI ... | 24,221 | [
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https://github.com/scikit-learn/scikit-learn/issues/24221 | [
"Build / CI"
] | ⚠️ CI failed on Linux_nogil.pylatest_pip_nogil ⚠️
**CI failed on [Linux_nogil.pylatest_pip_nogil](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=45748&view=logs&j=67fbb25f-e417-50be-be55-3b1e9637fce5)** (Aug 22, 2022)
- test_kernel_gradient[kernel11]
COMMENT:
## CI is no longer failing! ✅
[Su... | 24,221 | [
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https://github.com/scikit-learn/scikit-learn/issues/24221 | [
"Build / CI"
] | ⚠️ CI failed on Linux_nogil.pylatest_pip_nogil ⚠️
**CI failed on [Linux_nogil.pylatest_pip_nogil](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=45748&view=logs&j=67fbb25f-e417-50be-be55-3b1e9637fce5)** (Aug 22, 2022)
- test_kernel_gradient[kernel11]
COMMENT:
Ok, so apparently this not determi... | 24,221 | [
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https://github.com/scikit-learn/scikit-learn/issues/24221 | [
"Build / CI"
] | ⚠️ CI failed on Linux_nogil.pylatest_pip_nogil ⚠️
**CI failed on [Linux_nogil.pylatest_pip_nogil](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=45748&view=logs&j=67fbb25f-e417-50be-be55-3b1e9637fce5)** (Aug 22, 2022)
- test_kernel_gradient[kernel11]
COMMENT:
I looked a bit more into this one,... | 24,221 | [
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https://github.com/scikit-learn/scikit-learn/issues/24221 | [
"Build / CI"
] | ⚠️ CI failed on Linux_nogil.pylatest_pip_nogil ⚠️
**CI failed on [Linux_nogil.pylatest_pip_nogil](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=45748&view=logs&j=67fbb25f-e417-50be-be55-3b1e9637fce5)** (Aug 22, 2022)
- test_kernel_gradient[kernel11]
COMMENT:
Opened #24245 to fix the problem f... | 24,221 | [
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https://github.com/scikit-learn/scikit-learn/issues/24208 | [
"Bug",
"Needs Triage"
] | SequentialFeatureSelector html repr throws an exception
### Describe the bug
SequentialFeatureSelector html repr throws an exception. (Non-html repr is OK)
### Steps/Code to Reproduce
```python
sklearn.feature_selection.SequentialFeatureSelector(sklearn.linear_model.LinearRegression)
```
into ipython or ju... | 24,208 | [
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https://github.com/scikit-learn/scikit-learn/issues/24207 | [
"Bug",
"Needs Triage"
] | Unable to import scikit-learn modules
### Describe the bug
Multiple imports unable to be imported within the imblearn and scikit-learn package. Since there is no imblearn github repo, posting here. Using scikit-learn version 1.1.2 and imbalanced-learn 0.9.1
Error:
ImportError Trace... | 24,207 | [
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https://github.com/scikit-learn/scikit-learn/issues/24205 | [
"Bug",
"module:decomposition",
"Needs Reproducible Code"
] | explained_variance_ratio_ > 1.0
### Describe the bug
`PCA.explained_variance_ratio_` is larger than 1.0
### Steps/Code to Reproduce
```python
import sklearn.decomposition
pca = 64
_pca = sklearn.decomposition.PCA(pca)
vectors = _pca.fit_transform(vectors)
print(f"Explained variance ratio: {_pca.explain... | 24,205 | [
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https://github.com/scikit-learn/scikit-learn/issues/24205 | [
"Bug",
"module:decomposition",
"Needs Reproducible Code"
] | explained_variance_ratio_ > 1.0
### Describe the bug
`PCA.explained_variance_ratio_` is larger than 1.0
### Steps/Code to Reproduce
```python
import sklearn.decomposition
pca = 64
_pca = sklearn.decomposition.PCA(pca)
vectors = _pca.fit_transform(vectors)
print(f"Explained variance ratio: {_pca.explain... | 24,205 | [
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https://github.com/scikit-learn/scikit-learn/issues/24204 | [
"Needs Triage"
] | Upload a Python wheel for sklearn package
As you know a number of people install scikit-learn via `pip install sklearn` (or specify `sklearn` in their dependencies) which works due to the [`sklearn`](https://pypi.org/project/sklearn/#files) package alias. So far we still have no solution to let users know they shouldn... | 24,204 | [
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https://github.com/scikit-learn/scikit-learn/issues/24204 | [
"Needs Triage"
] | Upload a Python wheel for sklearn package
As you know a number of people install scikit-learn via `pip install sklearn` (or specify `sklearn` in their dependencies) which works due to the [`sklearn`](https://pypi.org/project/sklearn/#files) package alias. So far we still have no solution to let users know they shouldn... | 24,204 | [
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https://github.com/scikit-learn/scikit-learn/issues/24204 | [
"Needs Triage"
] | Upload a Python wheel for sklearn package
As you know a number of people install scikit-learn via `pip install sklearn` (or specify `sklearn` in their dependencies) which works due to the [`sklearn`](https://pypi.org/project/sklearn/#files) package alias. So far we still have no solution to let users know they shouldn... | 24,204 | [
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https://github.com/scikit-learn/scikit-learn/issues/24199 | [
"New Feature",
"module:preprocessing",
"Needs Decision - Include Feature"
] | Allow X in func or transformer in TransformedTargetRegressor
### Describe the workflow you want to enable
I would like to enable target transformation based on X in data.
This will come in handy when predicting a quantity that has a natural dependency on a feature. E.g. target value is summed salary of a househ... | 24,199 | [
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0.04456884413957596,
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0.07128283... |
https://github.com/scikit-learn/scikit-learn/issues/24199 | [
"New Feature",
"module:preprocessing",
"Needs Decision - Include Feature"
] | Allow X in func or transformer in TransformedTargetRegressor
### Describe the workflow you want to enable
I would like to enable target transformation based on X in data.
This will come in handy when predicting a quantity that has a natural dependency on a feature. E.g. target value is summed salary of a househ... | 24,199 | [
0.010151177644729614,
0.07361943274736404,
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0.04456884413957596,
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0.07128283... |
https://github.com/scikit-learn/scikit-learn/issues/24199 | [
"New Feature",
"module:preprocessing",
"Needs Decision - Include Feature"
] | Allow X in func or transformer in TransformedTargetRegressor
### Describe the workflow you want to enable
I would like to enable target transformation based on X in data.
This will come in handy when predicting a quantity that has a natural dependency on a feature. E.g. target value is summed salary of a househ... | 24,199 | [
0.010151177644729614,
0.07361943274736404,
0.03890360891819,
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0.03785942867398262,
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0.01843344233930111,
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0.012680628336966038,
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0.04456884413957596,
-0.024256981909275055,
0.07128283... |
https://github.com/scikit-learn/scikit-learn/issues/24199 | [
"New Feature",
"module:preprocessing",
"Needs Decision - Include Feature"
] | Allow X in func or transformer in TransformedTargetRegressor
### Describe the workflow you want to enable
I would like to enable target transformation based on X in data.
This will come in handy when predicting a quantity that has a natural dependency on a feature. E.g. target value is summed salary of a househ... | 24,199 | [
0.010151177644729614,
0.07361943274736404,
0.03890360891819,
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0.03785942867398262,
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0.01843344233930111,
0.014670327305793762,
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0.012680628336966038,
-0.006759194191545248,
0.04456884413957596,
-0.024256981909275055,
0.07128283... |
https://github.com/scikit-learn/scikit-learn/issues/24199 | [
"New Feature",
"module:preprocessing",
"Needs Decision - Include Feature"
] | Allow X in func or transformer in TransformedTargetRegressor
### Describe the workflow you want to enable
I would like to enable target transformation based on X in data.
This will come in handy when predicting a quantity that has a natural dependency on a feature. E.g. target value is summed salary of a househ... | 24,199 | [
0.010151177644729614,
0.07361943274736404,
0.03890360891819,
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0.012680628336966038,
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0.04456884413957596,
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0.07128283... |
https://github.com/scikit-learn/scikit-learn/issues/24199 | [
"New Feature",
"module:preprocessing",
"Needs Decision - Include Feature"
] | Allow X in func or transformer in TransformedTargetRegressor
### Describe the workflow you want to enable
I would like to enable target transformation based on X in data.
This will come in handy when predicting a quantity that has a natural dependency on a feature. E.g. target value is summed salary of a househ... | 24,199 | [
0.010151177644729614,
0.07361943274736404,
0.03890360891819,
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0.01843344233930111,
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0.012680628336966038,
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0.04456884413957596,
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0.07128283... |
https://github.com/scikit-learn/scikit-learn/issues/24199 | [
"New Feature",
"module:preprocessing",
"Needs Decision - Include Feature"
] | Allow X in func or transformer in TransformedTargetRegressor
### Describe the workflow you want to enable
I would like to enable target transformation based on X in data.
This will come in handy when predicting a quantity that has a natural dependency on a feature. E.g. target value is summed salary of a househ... | 24,199 | [
0.010151177644729614,
0.07361943274736404,
0.03890360891819,
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0.03785942867398262,
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0.01843344233930111,
0.014670327305793762,
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0.012680628336966038,
-0.006759194191545248,
0.04456884413957596,
-0.024256981909275055,
0.07128283... |
https://github.com/scikit-learn/scikit-learn/issues/24199 | [
"New Feature",
"module:preprocessing",
"Needs Decision - Include Feature"
] | Allow X in func or transformer in TransformedTargetRegressor
### Describe the workflow you want to enable
I would like to enable target transformation based on X in data.
This will come in handy when predicting a quantity that has a natural dependency on a feature. E.g. target value is summed salary of a househ... | 24,199 | [
0.010151177644729614,
0.07361943274736404,
0.03890360891819,
-0.06605789810419083,
0.03785942867398262,
-0.03973272442817688,
0.01843344233930111,
0.014670327305793762,
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0.012680628336966038,
-0.006759194191545248,
0.04456884413957596,
-0.024256981909275055,
0.07128283... |
https://github.com/scikit-learn/scikit-learn/issues/24199 | [
"New Feature",
"module:preprocessing",
"Needs Decision - Include Feature"
] | Allow X in func or transformer in TransformedTargetRegressor
### Describe the workflow you want to enable
I would like to enable target transformation based on X in data.
This will come in handy when predicting a quantity that has a natural dependency on a feature. E.g. target value is summed salary of a househ... | 24,199 | [
0.010151177644729614,
0.07361943274736404,
0.03890360891819,
-0.06605789810419083,
0.03785942867398262,
-0.03973272442817688,
0.01843344233930111,
0.014670327305793762,
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0.012680628336966038,
-0.006759194191545248,
0.04456884413957596,
-0.024256981909275055,
0.07128283... |
https://github.com/scikit-learn/scikit-learn/issues/24196 | [
"New Feature",
"module:linear_model",
"Needs Triage"
] | sklearn implementation of the square-root LASSO
### Describe the workflow you want to enable
The unconstrained LASSO is currently implemented in `lasso_path`. However, the parameter for unconstrained LASSO is sensitive to the measurement noise. Instead, the square-root LASSO has objective norm(Ax-b) + alpha * norm(x,... | 24,196 | [
-0.024018120020627975,
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0.002803013427183032,
0.04116740822792053,
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0.013433613814413548,
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0... |
https://github.com/scikit-learn/scikit-learn/issues/24196 | [
"New Feature",
"module:linear_model",
"Needs Triage"
] | sklearn implementation of the square-root LASSO
### Describe the workflow you want to enable
The unconstrained LASSO is currently implemented in `lasso_path`. However, the parameter for unconstrained LASSO is sensitive to the measurement noise. Instead, the square-root LASSO has objective norm(Ax-b) + alpha * norm(x,... | 24,196 | [
-0.024018120020627975,
0.056453533470630646,
0.026790529489517212,
-0.018212096765637398,
0.047155290842056274,
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0.002803013427183032,
0.04116740822792053,
0.020877905189990997,
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0.013433613814413548,
0.04096781089901924,
-0.04591168090701103,
0... |
https://github.com/scikit-learn/scikit-learn/issues/24196 | [
"New Feature",
"module:linear_model",
"Needs Triage"
] | sklearn implementation of the square-root LASSO
### Describe the workflow you want to enable
The unconstrained LASSO is currently implemented in `lasso_path`. However, the parameter for unconstrained LASSO is sensitive to the measurement noise. Instead, the square-root LASSO has objective norm(Ax-b) + alpha * norm(x,... | 24,196 | [
-0.024018120020627975,
0.056453533470630646,
0.026790529489517212,
-0.018212096765637398,
0.047155290842056274,
-0.029150469228625298,
0.002803013427183032,
0.04116740822792053,
0.020877905189990997,
-0.0004039299092255533,
0.013433613814413548,
0.04096781089901924,
-0.04591168090701103,
0... |
https://github.com/scikit-learn/scikit-learn/issues/24196 | [
"New Feature",
"module:linear_model",
"Needs Triage"
] | sklearn implementation of the square-root LASSO
### Describe the workflow you want to enable
The unconstrained LASSO is currently implemented in `lasso_path`. However, the parameter for unconstrained LASSO is sensitive to the measurement noise. Instead, the square-root LASSO has objective norm(Ax-b) + alpha * norm(x,... | 24,196 | [
-0.024018120020627975,
0.056453533470630646,
0.026790529489517212,
-0.018212096765637398,
0.047155290842056274,
-0.029150469228625298,
0.002803013427183032,
0.04116740822792053,
0.020877905189990997,
-0.0004039299092255533,
0.013433613814413548,
0.04096781089901924,
-0.04591168090701103,
0... |
https://github.com/scikit-learn/scikit-learn/issues/24187 | [
"New Feature"
] | Incremental versions of Existing Clustering Indices (metrics)
### Describe the workflow you want to enable
There currently exists 3 CVIs (cluster validity indices) in the main branch. These metrics are very useful for indicating performance of unsupervised clustering methods and add value to the module. However, th... | 24,187 | [
-0.04087691381573677,
0.039688825607299805,
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0.03311456739902496,
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0.02085048146545887,
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0.02534455806016922,
-0.008699862286448479,
0.055... |
https://github.com/scikit-learn/scikit-learn/issues/24186 | [
"New Feature",
"Needs Triage"
] | Reverse Transform and a intelligent skip non existent columns for transformer and pipelines
### Describe the workflow you want to enable
I have almost implemented a wizard that will preprocess the data a user puts in. Than the training of Tensorflow networks will be done and also a integration REST API flow comes o... | 24,186 | [
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0.07284890860319138,
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0.005809806752949953,
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https://github.com/scikit-learn/scikit-learn/issues/24182 | [
"Documentation",
"module:compose"
] | sklearn.compose.ColumnTransformer do not keep transformers` desired dtype of output
Hi,
We are using ColumnTransformer as our unified preprocessor to transform the data. We have the following transformers:
```python
from sklearn.impute import SimpleImputer
from sklearn.pipeline import Pipeline
from sklearn.pr... | 24,182 | [
-0.040995508432388306,
0.016808755695819855,
0.019216082990169525,
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0.040409255772829056,
0.006828530691564083,
0.028698788955807686,
0.034... |
https://github.com/scikit-learn/scikit-learn/issues/24182 | [
"Documentation",
"module:compose"
] | sklearn.compose.ColumnTransformer do not keep transformers` desired dtype of output
Hi,
We are using ColumnTransformer as our unified preprocessor to transform the data. We have the following transformers:
```python
from sklearn.impute import SimpleImputer
from sklearn.pipeline import Pipeline
from sklearn.pr... | 24,182 | [
-0.040995508432388306,
0.016808755695819855,
0.019216082990169525,
-0.03380870819091797,
0.07858610153198242,
0.004869147669523954,
0.014731061644852161,
0.02082613669335842,
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-0.02189350686967373,
0.040409255772829056,
0.006828530691564083,
0.028698788955807686,
0.034... |
https://github.com/scikit-learn/scikit-learn/issues/24182 | [
"Documentation",
"module:compose"
] | sklearn.compose.ColumnTransformer do not keep transformers` desired dtype of output
Hi,
We are using ColumnTransformer as our unified preprocessor to transform the data. We have the following transformers:
```python
from sklearn.impute import SimpleImputer
from sklearn.pipeline import Pipeline
from sklearn.pr... | 24,182 | [
-0.040995508432388306,
0.016808755695819855,
0.019216082990169525,
-0.03380870819091797,
0.07858610153198242,
0.004869147669523954,
0.014731061644852161,
0.02082613669335842,
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-0.02189350686967373,
0.040409255772829056,
0.006828530691564083,
0.028698788955807686,
0.034... |
https://github.com/scikit-learn/scikit-learn/issues/24182 | [
"Documentation",
"module:compose"
] | sklearn.compose.ColumnTransformer do not keep transformers` desired dtype of output
Hi,
We are using ColumnTransformer as our unified preprocessor to transform the data. We have the following transformers:
```python
from sklearn.impute import SimpleImputer
from sklearn.pipeline import Pipeline
from sklearn.pr... | 24,182 | [
-0.040995508432388306,
0.016808755695819855,
0.019216082990169525,
-0.03380870819091797,
0.07858610153198242,
0.004869147669523954,
0.014731061644852161,
0.02082613669335842,
-0.04602273181080818,
-0.02189350686967373,
0.040409255772829056,
0.006828530691564083,
0.028698788955807686,
0.034... |
https://github.com/scikit-learn/scikit-learn/issues/24182 | [
"Documentation",
"module:compose"
] | sklearn.compose.ColumnTransformer do not keep transformers` desired dtype of output
Hi,
We are using ColumnTransformer as our unified preprocessor to transform the data. We have the following transformers:
```python
from sklearn.impute import SimpleImputer
from sklearn.pipeline import Pipeline
from sklearn.pr... | 24,182 | [
-0.040995508432388306,
0.016808755695819855,
0.019216082990169525,
-0.03380870819091797,
0.07858610153198242,
0.004869147669523954,
0.014731061644852161,
0.02082613669335842,
-0.04602273181080818,
-0.02189350686967373,
0.040409255772829056,
0.006828530691564083,
0.028698788955807686,
0.034... |
https://github.com/scikit-learn/scikit-learn/issues/24182 | [
"Documentation",
"module:compose"
] | sklearn.compose.ColumnTransformer do not keep transformers` desired dtype of output
Hi,
We are using ColumnTransformer as our unified preprocessor to transform the data. We have the following transformers:
```python
from sklearn.impute import SimpleImputer
from sklearn.pipeline import Pipeline
from sklearn.pr... | 24,182 | [
-0.040995508432388306,
0.016808755695819855,
0.019216082990169525,
-0.03380870819091797,
0.07858610153198242,
0.004869147669523954,
0.014731061644852161,
0.02082613669335842,
-0.04602273181080818,
-0.02189350686967373,
0.040409255772829056,
0.006828530691564083,
0.028698788955807686,
0.034... |
https://github.com/scikit-learn/scikit-learn/issues/24182 | [
"Documentation",
"module:compose"
] | sklearn.compose.ColumnTransformer do not keep transformers` desired dtype of output
Hi,
We are using ColumnTransformer as our unified preprocessor to transform the data. We have the following transformers:
```python
from sklearn.impute import SimpleImputer
from sklearn.pipeline import Pipeline
from sklearn.pr... | 24,182 | [
-0.040995508432388306,
0.016808755695819855,
0.019216082990169525,
-0.03380870819091797,
0.07858610153198242,
0.004869147669523954,
0.014731061644852161,
0.02082613669335842,
-0.04602273181080818,
-0.02189350686967373,
0.040409255772829056,
0.006828530691564083,
0.028698788955807686,
0.034... |
https://github.com/scikit-learn/scikit-learn/issues/24176 | [
"Documentation",
"help wanted",
"module:cluster"
] | AgglomerativeClustering's distance_threshold is misleading
### Describe the issue linked to the documentation
According to the [documentation regarding `AgglomerativeClustering`](https://scikit-learn.org/stable/modules/generated/sklearn.cluster.AgglomerativeClustering.html#sklearn.cluster.AgglomerativeClustering), th... | 24,176 | [
-0.02220107801258564,
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-0.00871967151761055,
-0.0029446249827742577,
0.0077039445750415325,
0.01154754962772131,
0.051973141729831696,
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0.05898226797580719,
-0.0005899987882003188,
0.056664980947971344,
0.02875177375972271,
0.020414000377058983,
0... |
https://github.com/scikit-learn/scikit-learn/issues/24176 | [
"Documentation",
"help wanted",
"module:cluster"
] | AgglomerativeClustering's distance_threshold is misleading
### Describe the issue linked to the documentation
According to the [documentation regarding `AgglomerativeClustering`](https://scikit-learn.org/stable/modules/generated/sklearn.cluster.AgglomerativeClustering.html#sklearn.cluster.AgglomerativeClustering), th... | 24,176 | [
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0.028484471142292023,
0.003026... |
https://github.com/scikit-learn/scikit-learn/issues/24172 | [
"Documentation",
"module:linear_model"
] | SGDClassifier initial lr undocumented
### Describe the issue linked to the documentation
The [documentation for SGDClassifier](https://scikit-learn.org/stable/modules/sgd.html#sgd) says that with `learning_rate='optimal'` the initial learning rate `t0` is chosen with a heuristic proposed by Léon Bottou that "can be f... | 24,172 | [
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0.... |
https://github.com/scikit-learn/scikit-learn/issues/24172 | [
"Documentation",
"module:linear_model"
] | SGDClassifier initial lr undocumented
### Describe the issue linked to the documentation
The [documentation for SGDClassifier](https://scikit-learn.org/stable/modules/sgd.html#sgd) says that with `learning_rate='optimal'` the initial learning rate `t0` is chosen with a heuristic proposed by Léon Bottou that "can be f... | 24,172 | [
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0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24172 | [
"Documentation",
"module:linear_model"
] | SGDClassifier initial lr undocumented
### Describe the issue linked to the documentation
The [documentation for SGDClassifier](https://scikit-learn.org/stable/modules/sgd.html#sgd) says that with `learning_rate='optimal'` the initial learning rate `t0` is chosen with a heuristic proposed by Léon Bottou that "can be f... | 24,172 | [
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0.06437446177005768,
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0.027... |
https://github.com/scikit-learn/scikit-learn/issues/24172 | [
"Documentation",
"module:linear_model"
] | SGDClassifier initial lr undocumented
### Describe the issue linked to the documentation
The [documentation for SGDClassifier](https://scikit-learn.org/stable/modules/sgd.html#sgd) says that with `learning_rate='optimal'` the initial learning rate `t0` is chosen with a heuristic proposed by Léon Bottou that "can be f... | 24,172 | [
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0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24172 | [
"Documentation",
"module:linear_model"
] | SGDClassifier initial lr undocumented
### Describe the issue linked to the documentation
The [documentation for SGDClassifier](https://scikit-learn.org/stable/modules/sgd.html#sgd) says that with `learning_rate='optimal'` the initial learning rate `t0` is chosen with a heuristic proposed by Léon Bottou that "can be f... | 24,172 | [
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... |
https://github.com/scikit-learn/scikit-learn/issues/24172 | [
"Documentation",
"module:linear_model"
] | SGDClassifier initial lr undocumented
### Describe the issue linked to the documentation
The [documentation for SGDClassifier](https://scikit-learn.org/stable/modules/sgd.html#sgd) says that with `learning_rate='optimal'` the initial learning rate `t0` is chosen with a heuristic proposed by Léon Bottou that "can be f... | 24,172 | [
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0... |
https://github.com/scikit-learn/scikit-learn/issues/24172 | [
"Documentation",
"module:linear_model"
] | SGDClassifier initial lr undocumented
### Describe the issue linked to the documentation
The [documentation for SGDClassifier](https://scikit-learn.org/stable/modules/sgd.html#sgd) says that with `learning_rate='optimal'` the initial learning rate `t0` is chosen with a heuristic proposed by Léon Bottou that "can be f... | 24,172 | [
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https://github.com/scikit-learn/scikit-learn/issues/24172 | [
"Documentation",
"module:linear_model"
] | SGDClassifier initial lr undocumented
### Describe the issue linked to the documentation
The [documentation for SGDClassifier](https://scikit-learn.org/stable/modules/sgd.html#sgd) says that with `learning_rate='optimal'` the initial learning rate `t0` is chosen with a heuristic proposed by Léon Bottou that "can be f... | 24,172 | [
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https://github.com/scikit-learn/scikit-learn/issues/24160 | [
"Needs Triage"
] | ⚠️ CI failed on Wheel builder ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/2837268478)** (Aug 11, 2022)
COMMENT:
`test_estimators[SpectralEmbedding()-check_pipeline_consistency]` fails on Windows, maybe related to https://github.com/scikit-learn/scikit-learn/is... | 24,160 | [
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0.052600156515836716,
0.012914326041936874,
0.0576... |
https://github.com/scikit-learn/scikit-learn/issues/24160 | [
"Needs Triage"
] | ⚠️ CI failed on Wheel builder ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/2837268478)** (Aug 11, 2022)
COMMENT:
## CI is no longer failing! ✅
[Successful run](https://github.com/scikit-learn/scikit-learn/actions/runs/2844366471) on Aug 12, 2022 | 24,160 | [
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0.07287... |
https://github.com/scikit-learn/scikit-learn/issues/24155 | [
"New Feature",
"module:linear_model",
"Needs Decision - Include Feature"
] | LogisticRegression doesn't have an offset option
### Describe the workflow you want to enable
Like in R, can we add an option of offset in sklearn so that we can fix the value of some coefficients for logistic regression?
For those who don't know offset, offset is defined as a fixed feature with coefficient being ... | 24,155 | [
0.018623702228069305,
0.09785355627536774,
0.028094742447137833,
0.00037855328992009163,
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0.08283059298992157,
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0.08513007313013077,
0.006778730545192957,
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0.... |
https://github.com/scikit-learn/scikit-learn/issues/24155 | [
"New Feature",
"module:linear_model",
"Needs Decision - Include Feature"
] | LogisticRegression doesn't have an offset option
### Describe the workflow you want to enable
Like in R, can we add an option of offset in sklearn so that we can fix the value of some coefficients for logistic regression?
For those who don't know offset, offset is defined as a fixed feature with coefficient being ... | 24,155 | [
0.017525233328342438,
0.09833713620901108,
0.02735118381679058,
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0.02156219258904457,
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0.0815022736787796,
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0.08619028329849243,
0.008621737360954285,
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0.088... |
https://github.com/scikit-learn/scikit-learn/issues/24155 | [
"New Feature",
"module:linear_model",
"Needs Decision - Include Feature"
] | LogisticRegression doesn't have an offset option
### Describe the workflow you want to enable
Like in R, can we add an option of offset in sklearn so that we can fix the value of some coefficients for logistic regression?
For those who don't know offset, offset is defined as a fixed feature with coefficient being ... | 24,155 | [
0.01705516315996647,
0.10062568634748459,
0.02707436867058277,
0.0038203124422580004,
0.021328233182430267,
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0.08131055533885956,
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0.08357850462198257,
0.008243607357144356,
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0.084628... |
https://github.com/scikit-learn/scikit-learn/issues/24154 | [
"Enhancement",
"Build / CI"
] | joblib and threadpoolctl dependencies are missing in setup.py and pyproject.toml
### Describe the bug
README.rst lists them as dependencies, but they aren't in setup.py and pyproject.toml
### Steps/Code to Reproduce
n/a
### Expected Results
n/a
### Actual Results
n/a
### Versions
```shell
n/a
```
COMMENT:
Th... | 24,154 | [
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0.04720506817102432,
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0.0036747704725712538,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/24154 | [
"Enhancement",
"Build / CI"
] | joblib and threadpoolctl dependencies are missing in setup.py and pyproject.toml
### Describe the bug
README.rst lists them as dependencies, but they aren't in setup.py and pyproject.toml
### Steps/Code to Reproduce
n/a
### Expected Results
n/a
### Actual Results
n/a
### Versions
```shell
n/a
```
COMMENT:
I ... | 24,154 | [
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0.04697415232658386,
0.038566622883081436,
0.01195811852812767,
-0.009... |
https://github.com/scikit-learn/scikit-learn/issues/24154 | [
"Enhancement",
"Build / CI"
] | joblib and threadpoolctl dependencies are missing in setup.py and pyproject.toml
### Describe the bug
README.rst lists them as dependencies, but they aren't in setup.py and pyproject.toml
### Steps/Code to Reproduce
n/a
### Expected Results
n/a
### Actual Results
n/a
### Versions
```shell
n/a
```
COMMENT:
Be... | 24,154 | [
0.008630474098026752,
0.02437361516058445,
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0.008050894364714622,
0.043496157974004745,
0.06457223743200302,
0.016092641279101372,
0.010... |
https://github.com/scikit-learn/scikit-learn/issues/24154 | [
"Enhancement",
"Build / CI"
] | joblib and threadpoolctl dependencies are missing in setup.py and pyproject.toml
### Describe the bug
README.rst lists them as dependencies, but they aren't in setup.py and pyproject.toml
### Steps/Code to Reproduce
n/a
### Expected Results
n/a
### Actual Results
n/a
### Versions
```shell
n/a
```
COMMENT:
> ... | 24,154 | [
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0.04965949431061745,
0.047557294368743896,
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-0.... |
https://github.com/scikit-learn/scikit-learn/issues/24154 | [
"Enhancement",
"Build / CI"
] | joblib and threadpoolctl dependencies are missing in setup.py and pyproject.toml
### Describe the bug
README.rst lists them as dependencies, but they aren't in setup.py and pyproject.toml
### Steps/Code to Reproduce
n/a
### Expected Results
n/a
### Actual Results
n/a
### Versions
```shell
n/a
```
COMMENT:
> ... | 24,154 | [
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0.04758704453706741,
0.029062772169709206,
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0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24154 | [
"Enhancement",
"Build / CI"
] | joblib and threadpoolctl dependencies are missing in setup.py and pyproject.toml
### Describe the bug
README.rst lists them as dependencies, but they aren't in setup.py and pyproject.toml
### Steps/Code to Reproduce
n/a
### Expected Results
n/a
### Actual Results
n/a
### Versions
```shell
n/a
```
COMMENT:
> ... | 24,154 | [
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0.019608039408922195,
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0.04149971157312393,
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0.020311232656240463,
0.05511816591024399,
0.06866875290870667,
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-0.... |
https://github.com/scikit-learn/scikit-learn/issues/24154 | [
"Enhancement",
"Build / CI"
] | joblib and threadpoolctl dependencies are missing in setup.py and pyproject.toml
### Describe the bug
README.rst lists them as dependencies, but they aren't in setup.py and pyproject.toml
### Steps/Code to Reproduce
n/a
### Expected Results
n/a
### Actual Results
n/a
### Versions
```shell
n/a
```
COMMENT:
> ... | 24,154 | [
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0.023255713284015656,
0.05923832580447197,
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0.01707187294960022,
0.0645371749997139,
0.037280090153217316,
0.012800714932382107,
-0.023... |
https://github.com/scikit-learn/scikit-learn/issues/24151 | [
"Bug"
] | joblib Object is not serializable
### Describe the bug
When I add these code
```
from sklearnex import patch_sklearn
patch_sklearn()
```
And when used with joblib.dump or pickle.dump, an error will occur
### Steps/Code to Reproduce
```python
from sklearnex import patch_sklearn
import joblib
import p... | 24,151 | [
-0.007786240428686142,
0.06571006029844284,
0.03187716752290726,
0.007265896536409855,
0.06018014997243881,
0.041198987513780594,
0.015869373455643654,
0.028961310163140297,
-0.020080910995602608,
-0.008577768690884113,
0.05013388767838478,
0.08166688680648804,
-0.008556586690247059,
0.066... |
https://github.com/scikit-learn/scikit-learn/issues/24151 | [
"Bug"
] | joblib Object is not serializable
### Describe the bug
When I add these code
```
from sklearnex import patch_sklearn
patch_sklearn()
```
And when used with joblib.dump or pickle.dump, an error will occur
### Steps/Code to Reproduce
```python
from sklearnex import patch_sklearn
import joblib
import p... | 24,151 | [
-0.007786240428686142,
0.06571006029844284,
0.03187716752290726,
0.007265896536409855,
0.06018014997243881,
0.041198987513780594,
0.015869373455643654,
0.028961310163140297,
-0.020080910995602608,
-0.008577768690884113,
0.05013388767838478,
0.08166688680648804,
-0.008556586690247059,
0.066... |
https://github.com/scikit-learn/scikit-learn/issues/24151 | [
"Bug"
] | joblib Object is not serializable
### Describe the bug
When I add these code
```
from sklearnex import patch_sklearn
patch_sklearn()
```
And when used with joblib.dump or pickle.dump, an error will occur
### Steps/Code to Reproduce
```python
from sklearnex import patch_sklearn
import joblib
import p... | 24,151 | [
-0.007786240428686142,
0.06571006029844284,
0.03187716752290726,
0.007265896536409855,
0.06018014997243881,
0.041198987513780594,
0.015869373455643654,
0.028961310163140297,
-0.020080910995602608,
-0.008577768690884113,
0.05013388767838478,
0.08166688680648804,
-0.008556586690247059,
0.066... |
https://github.com/scikit-learn/scikit-learn/issues/24148 | [
"Documentation",
"module:model_selection"
] | DOC LeaveOneGroupOut description confusing
### Describe the issue linked to the documentation
The description for [`LeaveOneGroupOut`](https://scikit-learn.org/stable/modules/cross_validation.html#leave-one-group-out) in the user guide:
> :class:`LeaveOneGroupOut` is a cross-validation scheme which holds out
the ... | 24,148 | [
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0.019542302936315536,
0.15068142116069794,
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0.002283241832628846,
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0.013761084526777267,
... |
https://github.com/scikit-learn/scikit-learn/issues/24138 | [
"Bug",
"module:svm",
"Needs Investigation"
] | sklearn.svm.SVR use more RAM memory on newer versions
### Describe the bug
Hi, I've previously reported a bug that [RandomForestClassifier](https://github.com/scikit-learn/scikit-learn/issues/24124) consumes more memory on newer versions, and I've also noticed that the svm API also consumes more memory on newer versi... | 24,138 | [
0.03582947328686714,
-0.015904976055026054,
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0.07315985858440399,
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0.028961321339011192,
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0.011785345152020454,
0.050666529685258865,
0.051587481051683426,
-0.005255361087620258,
... |
https://github.com/scikit-learn/scikit-learn/issues/24138 | [
"Bug",
"module:svm",
"Needs Investigation"
] | sklearn.svm.SVR use more RAM memory on newer versions
### Describe the bug
Hi, I've previously reported a bug that [RandomForestClassifier](https://github.com/scikit-learn/scikit-learn/issues/24124) consumes more memory on newer versions, and I've also noticed that the svm API also consumes more memory on newer versi... | 24,138 | [
0.03582947328686714,
-0.015904976055026054,
-0.003117556683719158,
-0.0063250865787267685,
0.07315985858440399,
-0.019808132201433182,
-0.021859893575310707,
0.028961321339011192,
-0.02222229726612568,
0.011785345152020454,
0.050666529685258865,
0.051587481051683426,
-0.005255361087620258,
... |
https://github.com/scikit-learn/scikit-learn/issues/24138 | [
"Bug",
"module:svm",
"Needs Investigation"
] | sklearn.svm.SVR use more RAM memory on newer versions
### Describe the bug
Hi, I've previously reported a bug that [RandomForestClassifier](https://github.com/scikit-learn/scikit-learn/issues/24124) consumes more memory on newer versions, and I've also noticed that the svm API also consumes more memory on newer versi... | 24,138 | [
0.03582947328686714,
-0.015904976055026054,
-0.003117556683719158,
-0.0063250865787267685,
0.07315985858440399,
-0.019808132201433182,
-0.021859893575310707,
0.028961321339011192,
-0.02222229726612568,
0.011785345152020454,
0.050666529685258865,
0.051587481051683426,
-0.005255361087620258,
... |
https://github.com/scikit-learn/scikit-learn/issues/24133 | [
"New Feature",
"module:linear_model",
"Needs Decision - Include Feature"
] | Add Hannan-Quinn IC to LassoLarsIC
### Describe the workflow you want to enable
Hannan–Quinn information criterion was originally described to be an alternative model selection criterion for autoregressive models, but it could be used in other cases too. Unlike AIC it also penalizes model's number of parameters, bu... | 24,133 | [
-0.019595611840486526,
0.12089215964078903,
0.013494077138602734,
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0.018113525584340096,
0.027075495570898056,
0.022889669984579086,
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0.0006344892899505794,
0.02925937995314598,
0.00027491713990457356,
-0.027059586718678474,
... |
https://github.com/scikit-learn/scikit-learn/issues/24133 | [
"New Feature",
"module:linear_model",
"Needs Decision - Include Feature"
] | Add Hannan-Quinn IC to LassoLarsIC
### Describe the workflow you want to enable
Hannan–Quinn information criterion was originally described to be an alternative model selection criterion for autoregressive models, but it could be used in other cases too. Unlike AIC it also penalizes model's number of parameters, bu... | 24,133 | [
-0.01721097342669964,
0.12786664068698883,
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0.004602556116878986,
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-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24133 | [
"New Feature",
"module:linear_model",
"Needs Decision - Include Feature"
] | Add Hannan-Quinn IC to LassoLarsIC
### Describe the workflow you want to enable
Hannan–Quinn information criterion was originally described to be an alternative model selection criterion for autoregressive models, but it could be used in other cases too. Unlike AIC it also penalizes model's number of parameters, bu... | 24,133 | [
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0.011692875996232033,
0.016419565305113792,
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-0... |
https://github.com/scikit-learn/scikit-learn/issues/24133 | [
"New Feature",
"module:linear_model",
"Needs Decision - Include Feature"
] | Add Hannan-Quinn IC to LassoLarsIC
### Describe the workflow you want to enable
Hannan–Quinn information criterion was originally described to be an alternative model selection criterion for autoregressive models, but it could be used in other cases too. Unlike AIC it also penalizes model's number of parameters, bu... | 24,133 | [
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0.0015667321858927608,
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-0.02... |
https://github.com/scikit-learn/scikit-learn/issues/24133 | [
"New Feature",
"module:linear_model",
"Needs Decision - Include Feature"
] | Add Hannan-Quinn IC to LassoLarsIC
### Describe the workflow you want to enable
Hannan–Quinn information criterion was originally described to be an alternative model selection criterion for autoregressive models, but it could be used in other cases too. Unlike AIC it also penalizes model's number of parameters, bu... | 24,133 | [
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https://github.com/scikit-learn/scikit-learn/issues/24131 | [
"Build / CI"
] | ⚠️ CI failed on Linux.ubuntu_atlas ⚠️
**CI is still failing on [Linux.ubuntu_atlas](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=46059&view=logs&j=0a287ed6-22f4-5cb4-88b1-d5fcdc4d8b7e)** (Aug 30, 2022)
- Test Collection Failure
COMMENT:
## CI is no longer failing! ✅
[Successful run](https:/... | 24,131 | [
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0.002532842569053173,
0.065... |
https://github.com/scikit-learn/scikit-learn/issues/24131 | [
"Build / CI"
] | ⚠️ CI failed on Linux.ubuntu_atlas ⚠️
**CI is still failing on [Linux.ubuntu_atlas](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=46059&view=logs&j=0a287ed6-22f4-5cb4-88b1-d5fcdc4d8b7e)** (Aug 30, 2022)
- Test Collection Failure
COMMENT:
Seems like a real issue for global_random_seed=20. On m... | 24,131 | [
-0.022655095905065536,
0.01843107119202614,
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0.0122... |
https://github.com/scikit-learn/scikit-learn/issues/24131 | [
"Build / CI"
] | ⚠️ CI failed on Linux.ubuntu_atlas ⚠️
**CI is still failing on [Linux.ubuntu_atlas](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=46059&view=logs&j=0a287ed6-22f4-5cb4-88b1-d5fcdc4d8b7e)** (Aug 30, 2022)
- Test Collection Failure
COMMENT:
**Edit**: should be fixed by #24168
Hmmm the latest... | 24,131 | [
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https://github.com/scikit-learn/scikit-learn/issues/24131 | [
"Build / CI"
] | ⚠️ CI failed on Linux.ubuntu_atlas ⚠️
**CI is still failing on [Linux.ubuntu_atlas](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=46059&view=logs&j=0a287ed6-22f4-5cb4-88b1-d5fcdc4d8b7e)** (Aug 30, 2022)
- Test Collection Failure
COMMENT:
As noted in https://github.com/scikit-learn/scikit-lear... | 24,131 | [
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0.0421... |
https://github.com/scikit-learn/scikit-learn/issues/24131 | [
"Build / CI"
] | ⚠️ CI failed on Linux.ubuntu_atlas ⚠️
**CI is still failing on [Linux.ubuntu_atlas](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=46059&view=logs&j=0a287ed6-22f4-5cb4-88b1-d5fcdc4d8b7e)** (Aug 30, 2022)
- Test Collection Failure
COMMENT:
:thinking: there were two separate issues here. The pai... | 24,131 | [
-0.023021815344691277,
0.05306416004896164,
-0.03313041105866432,
0.004914331249892712,
0.009764129295945168,
0.01898910291492939,
0.08377332985401154,
0.024440106004476547,
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0.004064857494086027,
0.052705734968185425,
-0.014372273348271847,
0.0078384168446064,
0.03933... |
https://github.com/scikit-learn/scikit-learn/issues/24131 | [
"Build / CI"
] | ⚠️ CI failed on Linux.ubuntu_atlas ⚠️
**CI is still failing on [Linux.ubuntu_atlas](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=46059&view=logs&j=0a287ed6-22f4-5cb4-88b1-d5fcdc4d8b7e)** (Aug 30, 2022)
- Test Collection Failure
COMMENT:
Ah I see, there are two issues. I'm okay with keeping t... | 24,131 | [
-0.013478375971317291,
0.04889409989118576,
-0.017679335549473763,
-0.04529505968093872,
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0.025242358446121216,
0.05361805483698845,
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0.006056788843125105,
0.030226821079850197,
0.04758739471435547,
0.022938789799809456,
-0.0004264505987521261,
0.057... |
https://github.com/scikit-learn/scikit-learn/issues/24131 | [
"Build / CI"
] | ⚠️ CI failed on Linux.ubuntu_atlas ⚠️
**CI is still failing on [Linux.ubuntu_atlas](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=46059&view=logs&j=0a287ed6-22f4-5cb4-88b1-d5fcdc4d8b7e)** (Aug 30, 2022)
- Test Collection Failure
COMMENT:
@jjerphan to help understand the nature of the failures... | 24,131 | [
-0.015423876233398914,
-0.0023839178029447794,
-0.01443659421056509,
-0.015063741244375706,
0.02619302272796631,
0.027492059394717216,
0.029725048691034317,
0.036461036652326584,
-0.016726717352867126,
0.02914522774517536,
0.04043332487344742,
0.01891898550093174,
0.016808660700917244,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24131 | [
"Build / CI"
] | ⚠️ CI failed on Linux.ubuntu_atlas ⚠️
**CI is still failing on [Linux.ubuntu_atlas](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=46059&view=logs&j=0a287ed6-22f4-5cb4-88b1-d5fcdc4d8b7e)** (Aug 30, 2022)
- Test Collection Failure
COMMENT:
> @jjerphan to help understand the nature of the failur... | 24,131 | [
-0.016701510176062584,
0.009979212656617165,
-0.010670931078493595,
-0.003949221223592758,
0.026807794347405434,
0.03223716467618942,
0.017546307295560837,
0.04224470257759094,
-0.013000452890992165,
0.020968297496438026,
0.048018500208854675,
0.017919404432177544,
0.010875565931200981,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/24131 | [
"Build / CI"
] | ⚠️ CI failed on Linux.ubuntu_atlas ⚠️
**CI is still failing on [Linux.ubuntu_atlas](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=46059&view=logs&j=0a287ed6-22f4-5cb4-88b1-d5fcdc4d8b7e)** (Aug 30, 2022)
- Test Collection Failure
COMMENT:
Closing since #24198 has been merged it should not happ... | 24,131 | [
-0.008910024538636208,
0.035468559712171555,
-0.014964837580919266,
-0.05852888897061348,
0.03609009087085724,
0.029583940282464027,
0.05295894667506218,
0.026344383135437965,
0.009804746136069298,
0.03688705712556839,
0.039027370512485504,
0.023061266168951988,
0.011765189468860626,
0.051... |
https://github.com/scikit-learn/scikit-learn/issues/24127 | [
"Bug",
"Documentation"
] | The documentation search is broken.
### Describe the issue linked to the documentation
When searching for methods, it gives an empty page in response to any request
### Suggest a potential alternative/fix
_No response_
COMMENT:
Thank you for the bug report. I am working on a fix in #24128. | 24,127 | [
0.05178970843553543,
0.02999136969447136,
0.010466286912560463,
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0.02578876167535782,
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0.08012191951274872,
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-0.010719840414822102,
-0.03646549955010414,
0.018218792974948883,
0.026097727939486504,
-0.09... |
https://github.com/scikit-learn/scikit-learn/issues/24127 | [
"Bug",
"Documentation"
] | The documentation search is broken.
### Describe the issue linked to the documentation
When searching for methods, it gives an empty page in response to any request
### Suggest a potential alternative/fix
_No response_
COMMENT:
The documentation search is broken again for a few days (as far as I can tell). | 24,127 | [
0.05522853508591652,
0.03684999793767929,
0.013169541023671627,
-0.008578700944781303,
0.04074878990650177,
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0.08397164195775986,
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0.01872900128364563,
0.02637290582060814,
-0.0879... |
https://github.com/scikit-learn/scikit-learn/issues/24127 | [
"Bug",
"Documentation"
] | The documentation search is broken.
### Describe the issue linked to the documentation
When searching for methods, it gives an empty page in response to any request
### Suggest a potential alternative/fix
_No response_
COMMENT:
Thanks for the report, this will likely be fixed by https://github.com/scikit-learn/sci... | 24,127 | [
0.05212970823049545,
0.005244486965239048,
0.012150133959949017,
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0.03100866638123989,
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0.030202118679881096,
0.056471213698387146,
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-0.029588403180241585,
-0.00679877121001482,
0.04239622876048088,
0.03371104598045349,
-0.040... |
https://github.com/scikit-learn/scikit-learn/issues/24124 | [
"module:ensemble",
"Needs Investigation"
] | RandomForestClassifier RAM memory increase on newer versions
### Describe the bug
I tested the performance of my program on different sklearn versions. I found that the program uses more memory when sklearn is on the latest version compared to older versions.
```shell
1.0.1 1449MB
0.24.2 1338MB
0.23.2 144... | 24,124 | [
0.04438629001379013,
0.00852646492421627,
0.003558884374797344,
0.014447127468883991,
0.05151335895061493,
-0.01283920556306839,
-0.019610030576586723,
0.04533301666378975,
0.008252706378698349,
-0.004094717092812061,
0.05343203619122505,
0.0252212006598711,
0.004227910656481981,
-0.016360... |
https://github.com/scikit-learn/scikit-learn/issues/24124 | [
"module:ensemble",
"Needs Investigation"
] | RandomForestClassifier RAM memory increase on newer versions
### Describe the bug
I tested the performance of my program on different sklearn versions. I found that the program uses more memory when sklearn is on the latest version compared to older versions.
```shell
1.0.1 1449MB
0.24.2 1338MB
0.23.2 144... | 24,124 | [
0.04438629001379013,
0.00852646492421627,
0.003558884374797344,
0.014447127468883991,
0.05151335895061493,
-0.01283920556306839,
-0.019610030576586723,
0.04533301666378975,
0.008252706378698349,
-0.004094717092812061,
0.05343203619122505,
0.0252212006598711,
0.004227910656481981,
-0.016360... |
https://github.com/scikit-learn/scikit-learn/issues/24124 | [
"module:ensemble",
"Needs Investigation"
] | RandomForestClassifier RAM memory increase on newer versions
### Describe the bug
I tested the performance of my program on different sklearn versions. I found that the program uses more memory when sklearn is on the latest version compared to older versions.
```shell
1.0.1 1449MB
0.24.2 1338MB
0.23.2 144... | 24,124 | [
0.04438629001379013,
0.00852646492421627,
0.003558884374797344,
0.014447127468883991,
0.05151335895061493,
-0.01283920556306839,
-0.019610030576586723,
0.04533301666378975,
0.008252706378698349,
-0.004094717092812061,
0.05343203619122505,
0.0252212006598711,
0.004227910656481981,
-0.016360... |
https://github.com/scikit-learn/scikit-learn/issues/24124 | [
"module:ensemble",
"Needs Investigation"
] | RandomForestClassifier RAM memory increase on newer versions
### Describe the bug
I tested the performance of my program on different sklearn versions. I found that the program uses more memory when sklearn is on the latest version compared to older versions.
```shell
1.0.1 1449MB
0.24.2 1338MB
0.23.2 144... | 24,124 | [
0.04438629001379013,
0.00852646492421627,
0.003558884374797344,
0.014447127468883991,
0.05151335895061493,
-0.01283920556306839,
-0.019610030576586723,
0.04533301666378975,
0.008252706378698349,
-0.004094717092812061,
0.05343203619122505,
0.0252212006598711,
0.004227910656481981,
-0.016360... |
https://github.com/scikit-learn/scikit-learn/issues/24124 | [
"module:ensemble",
"Needs Investigation"
] | RandomForestClassifier RAM memory increase on newer versions
### Describe the bug
I tested the performance of my program on different sklearn versions. I found that the program uses more memory when sklearn is on the latest version compared to older versions.
```shell
1.0.1 1449MB
0.24.2 1338MB
0.23.2 144... | 24,124 | [
0.04438629001379013,
0.00852646492421627,
0.003558884374797344,
0.014447127468883991,
0.05151335895061493,
-0.01283920556306839,
-0.019610030576586723,
0.04533301666378975,
0.008252706378698349,
-0.004094717092812061,
0.05343203619122505,
0.0252212006598711,
0.004227910656481981,
-0.016360... |
https://github.com/scikit-learn/scikit-learn/issues/24113 | [
"Bug",
"Needs Triage"
] | Installation fails on MacOS 10.11 El Capitan with Python 3.10
### Describe the bug
There is a **scikit_learn-1.1.1-cp310-cp310-macosx_10_13_x86_64.whl** Wheel available on PyPi, but nothing compatible with earlier versions of MacOS running Python 3.10
As a result, pip attempts to compile from source. This fails as... | 24,113 | [
0.03465498611330986,
0.00247286562807858,
-0.02024693228304386,
-0.04958207160234451,
0.003922886215150356,
0.024831654503941536,
-0.005550280679017305,
0.02686075121164322,
-0.025723673403263092,
-0.00475975451990962,
-0.0013027156237512827,
0.09282152354717255,
-0.012011023238301277,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/24107 | [
"Bug",
"module:gaussian_process",
"Needs Investigation"
] | Gaussian Process regression get_params set_params does not yield same predictor?
### Describe the bug
This is on version 1.1.1
I *think* the example below is the correct way of setting GPR params saved from a previous .fit() tuning via the optimizer. Reading through the code I don't yet understand why the parame... | 24,107 | [
0.025258369743824005,
0.02981380559504032,
0.03425191342830658,
0.055206675082445145,
0.05463723465800285,
-0.05478290095925331,
0.030952585861086845,
-0.017972372472286224,
-0.0330938883125782,
0.013399243354797363,
0.02678031101822853,
0.03674031049013138,
0.04185058921575546,
0.00747490... |
https://github.com/scikit-learn/scikit-learn/issues/24107 | [
"Bug",
"module:gaussian_process",
"Needs Investigation"
] | Gaussian Process regression get_params set_params does not yield same predictor?
### Describe the bug
This is on version 1.1.1
I *think* the example below is the correct way of setting GPR params saved from a previous .fit() tuning via the optimizer. Reading through the code I don't yet understand why the parame... | 24,107 | [
0.025258369743824005,
0.02981380559504032,
0.03425191342830658,
0.055206675082445145,
0.05463723465800285,
-0.05478290095925331,
0.030952585861086845,
-0.017972372472286224,
-0.0330938883125782,
0.013399243354797363,
0.02678031101822853,
0.03674031049013138,
0.04185058921575546,
0.00747490... |
https://github.com/scikit-learn/scikit-learn/issues/24107 | [
"Bug",
"module:gaussian_process",
"Needs Investigation"
] | Gaussian Process regression get_params set_params does not yield same predictor?
### Describe the bug
This is on version 1.1.1
I *think* the example below is the correct way of setting GPR params saved from a previous .fit() tuning via the optimizer. Reading through the code I don't yet understand why the parame... | 24,107 | [
0.025258369743824005,
0.02981380559504032,
0.03425191342830658,
0.055206675082445145,
0.05463723465800285,
-0.05478290095925331,
0.030952585861086845,
-0.017972372472286224,
-0.0330938883125782,
0.013399243354797363,
0.02678031101822853,
0.03674031049013138,
0.04185058921575546,
0.00747490... |
https://github.com/scikit-learn/scikit-learn/issues/24107 | [
"Bug",
"module:gaussian_process",
"Needs Investigation"
] | Gaussian Process regression get_params set_params does not yield same predictor?
### Describe the bug
This is on version 1.1.1
I *think* the example below is the correct way of setting GPR params saved from a previous .fit() tuning via the optimizer. Reading through the code I don't yet understand why the parame... | 24,107 | [
0.025258369743824005,
0.02981380559504032,
0.03425191342830658,
0.055206675082445145,
0.05463723465800285,
-0.05478290095925331,
0.030952585861086845,
-0.017972372472286224,
-0.0330938883125782,
0.013399243354797363,
0.02678031101822853,
0.03674031049013138,
0.04185058921575546,
0.00747490... |
https://github.com/scikit-learn/scikit-learn/issues/24107 | [
"Bug",
"module:gaussian_process",
"Needs Investigation"
] | Gaussian Process regression get_params set_params does not yield same predictor?
### Describe the bug
This is on version 1.1.1
I *think* the example below is the correct way of setting GPR params saved from a previous .fit() tuning via the optimizer. Reading through the code I don't yet understand why the parame... | 24,107 | [
0.025258369743824005,
0.02981380559504032,
0.03425191342830658,
0.055206675082445145,
0.05463723465800285,
-0.05478290095925331,
0.030952585861086845,
-0.017972372472286224,
-0.0330938883125782,
0.013399243354797363,
0.02678031101822853,
0.03674031049013138,
0.04185058921575546,
0.00747490... |
https://github.com/scikit-learn/scikit-learn/issues/24107 | [
"Bug",
"module:gaussian_process",
"Needs Investigation"
] | Gaussian Process regression get_params set_params does not yield same predictor?
### Describe the bug
This is on version 1.1.1
I *think* the example below is the correct way of setting GPR params saved from a previous .fit() tuning via the optimizer. Reading through the code I don't yet understand why the parame... | 24,107 | [
0.025258369743824005,
0.02981380559504032,
0.03425191342830658,
0.055206675082445145,
0.05463723465800285,
-0.05478290095925331,
0.030952585861086845,
-0.017972372472286224,
-0.0330938883125782,
0.013399243354797363,
0.02678031101822853,
0.03674031049013138,
0.04185058921575546,
0.00747490... |
https://github.com/scikit-learn/scikit-learn/issues/24105 | [
"Needs Triage"
] | ⚠️ CI failed on Wheel builder ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/2801198918)** (Aug 05, 2022)
COMMENT:
For the failing test `SpectralEmbedding()-check_pipeline_consistency`, it looks like the columns are flipped:
```
E AssertionError:
... | 24,105 | [
-0.044317588210105896,
-0.04033153876662254,
-0.030010659247636795,
0.03195241838693619,
0.024053793400526047,
0.014062527567148209,
-0.008384425193071365,
0.033897265791893005,
-0.02323376201093197,
0.03419011831283569,
0.04797926917672157,
0.05289428308606148,
-0.0049078334122896194,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24105 | [
"Needs Triage"
] | ⚠️ CI failed on Wheel builder ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/2801198918)** (Aug 05, 2022)
COMMENT:
Uhm. Could we have a non-deterministic change of components or something like that. | 24,105 | [
-0.029964732006192207,
0.032090362161397934,
-0.020676931366324425,
-0.029678476974368095,
0.013257893733680248,
0.0222614873200655,
0.012864244170486927,
0.015173579566180706,
-0.05615415424108505,
0.016026228666305542,
0.10540671646595001,
0.04645729437470436,
-0.0074341134168207645,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/24105 | [
"Needs Triage"
] | ⚠️ CI failed on Wheel builder ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/2801198918)** (Aug 05, 2022)
COMMENT:
## CI is no longer failing! ✅
[Successful run](https://github.com/scikit-learn/scikit-learn/actions/runs/2807530133) on Aug 06, 2022 | 24,105 | [
-0.044259458780288696,
0.033622052520513535,
-0.02387252077460289,
-0.013387392275035381,
0.010081635788083076,
0.013491015881299973,
0.00991519633680582,
0.04175176844000816,
-0.051544759422540665,
0.027795035392045975,
0.08450601994991302,
0.04239574819803238,
-0.015844663605093956,
0.07... |
https://github.com/scikit-learn/scikit-learn/issues/24102 | [
"Needs Triage"
] | Pb in example for spectral coclustering
I think there is a missing final transposition missing in the example demo for spectral coclustering here :
https://scikit-learn.org/stable/auto_examples/bicluster/plot_spectral_coclustering.html
It should be :
```
fit_data = data[np.argsort(model.row_labels_)]
fit_... | 24,102 | [
0.0030142497271299362,
-0.040910761803388596,
0.0074469889514148235,
0.05535305663943291,
-0.010601925663650036,
-0.01175857987254858,
0.045923832803964615,
-0.025088349357247353,
0.008007628843188286,
-0.006158119533210993,
-0.038070324808359146,
-0.008717240765690804,
0.030421871691942215,... |
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