html_url stringlengths 57 57 | labels listlengths 1 6 | text stringlengths 32 258k | issue_number int64 22.4k 33k |
|---|---|---|---|
https://github.com/scikit-learn/scikit-learn/issues/32115 | [
"New Feature",
"module:cluster",
"Needs Decision - Include Feature"
] | [ENH] Adding KModes and KPrototypes clustering algorithms
### Describe the workflow you want to enable
Currently, scikit-learn users working with datasets that contain categorical features (e.g., `country`, `profession`, `product_type`) face a significant hurdle. The standard practice is to use one-hot encoding befor... | 32,115 |
https://github.com/scikit-learn/scikit-learn/issues/32115 | [
"New Feature",
"module:cluster",
"Needs Decision - Include Feature"
] | [ENH] Adding KModes and KPrototypes clustering algorithms
### Describe the workflow you want to enable
Currently, scikit-learn users working with datasets that contain categorical features (e.g., `country`, `profession`, `product_type`) face a significant hurdle. The standard practice is to use one-hot encoding befor... | 32,115 |
https://github.com/scikit-learn/scikit-learn/issues/32115 | [
"New Feature",
"module:cluster",
"Needs Decision - Include Feature"
] | [ENH] Adding KModes and KPrototypes clustering algorithms
### Describe the workflow you want to enable
Currently, scikit-learn users working with datasets that contain categorical features (e.g., `country`, `profession`, `product_type`) face a significant hurdle. The standard practice is to use one-hot encoding befor... | 32,115 |
https://github.com/scikit-learn/scikit-learn/issues/32115 | [
"New Feature",
"module:cluster",
"Needs Decision - Include Feature"
] | [ENH] Adding KModes and KPrototypes clustering algorithms
### Describe the workflow you want to enable
Currently, scikit-learn users working with datasets that contain categorical features (e.g., `country`, `profession`, `product_type`) face a significant hurdle. The standard practice is to use one-hot encoding befor... | 32,115 |
https://github.com/scikit-learn/scikit-learn/issues/32115 | [
"New Feature",
"module:cluster",
"Needs Decision - Include Feature"
] | [ENH] Adding KModes and KPrototypes clustering algorithms
### Describe the workflow you want to enable
Currently, scikit-learn users working with datasets that contain categorical features (e.g., `country`, `profession`, `product_type`) face a significant hurdle. The standard practice is to use one-hot encoding befor... | 32,115 |
https://github.com/scikit-learn/scikit-learn/issues/32115 | [
"New Feature",
"module:cluster",
"Needs Decision - Include Feature"
] | [ENH] Adding KModes and KPrototypes clustering algorithms
### Describe the workflow you want to enable
Currently, scikit-learn users working with datasets that contain categorical features (e.g., `country`, `profession`, `product_type`) face a significant hurdle. The standard practice is to use one-hot encoding befor... | 32,115 |
https://github.com/scikit-learn/scikit-learn/issues/32115 | [
"New Feature",
"module:cluster",
"Needs Decision - Include Feature"
] | [ENH] Adding KModes and KPrototypes clustering algorithms
### Describe the workflow you want to enable
Currently, scikit-learn users working with datasets that contain categorical features (e.g., `country`, `profession`, `product_type`) face a significant hurdle. The standard practice is to use one-hot encoding befor... | 32,115 |
https://github.com/scikit-learn/scikit-learn/issues/32115 | [
"New Feature",
"module:cluster",
"Needs Decision - Include Feature"
] | [ENH] Adding KModes and KPrototypes clustering algorithms
### Describe the workflow you want to enable
Currently, scikit-learn users working with datasets that contain categorical features (e.g., `country`, `profession`, `product_type`) face a significant hurdle. The standard practice is to use one-hot encoding befor... | 32,115 |
https://github.com/scikit-learn/scikit-learn/issues/32115 | [
"New Feature",
"module:cluster",
"Needs Decision - Include Feature"
] | [ENH] Adding KModes and KPrototypes clustering algorithms
### Describe the workflow you want to enable
Currently, scikit-learn users working with datasets that contain categorical features (e.g., `country`, `profession`, `product_type`) face a significant hurdle. The standard practice is to use one-hot encoding befor... | 32,115 |
https://github.com/scikit-learn/scikit-learn/issues/32112 | [
"API",
"RFC",
"module:compose",
"module:pipeline"
] | RFC Deprecate FeatureUnion and make_union
Unless I'm missing something, to me `FeatureUnion` is just a `ColumnTransformer` where all transformers are applied to all features. So it's just a special case of `ColumnTransformer`.
```py
import pandas as pd
from sklearn.pipeline import FeatureUnion
from sklearn.compose im... | 32,112 |
https://github.com/scikit-learn/scikit-learn/issues/32112 | [
"API",
"RFC",
"module:compose",
"module:pipeline"
] | RFC Deprecate FeatureUnion and make_union
Unless I'm missing something, to me `FeatureUnion` is just a `ColumnTransformer` where all transformers are applied to all features. So it's just a special case of `ColumnTransformer`.
```py
import pandas as pd
from sklearn.pipeline import FeatureUnion
from sklearn.compose im... | 32,112 |
https://github.com/scikit-learn/scikit-learn/issues/32112 | [
"API",
"RFC",
"module:compose",
"module:pipeline"
] | RFC Deprecate FeatureUnion and make_union
Unless I'm missing something, to me `FeatureUnion` is just a `ColumnTransformer` where all transformers are applied to all features. So it's just a special case of `ColumnTransformer`.
```py
import pandas as pd
from sklearn.pipeline import FeatureUnion
from sklearn.compose im... | 32,112 |
https://github.com/scikit-learn/scikit-learn/issues/32112 | [
"API",
"RFC",
"module:compose",
"module:pipeline"
] | RFC Deprecate FeatureUnion and make_union
Unless I'm missing something, to me `FeatureUnion` is just a `ColumnTransformer` where all transformers are applied to all features. So it's just a special case of `ColumnTransformer`.
```py
import pandas as pd
from sklearn.pipeline import FeatureUnion
from sklearn.compose im... | 32,112 |
https://github.com/scikit-learn/scikit-learn/issues/32112 | [
"API",
"RFC",
"module:compose",
"module:pipeline"
] | RFC Deprecate FeatureUnion and make_union
Unless I'm missing something, to me `FeatureUnion` is just a `ColumnTransformer` where all transformers are applied to all features. So it's just a special case of `ColumnTransformer`.
```py
import pandas as pd
from sklearn.pipeline import FeatureUnion
from sklearn.compose im... | 32,112 |
https://github.com/scikit-learn/scikit-learn/issues/32112 | [
"API",
"RFC",
"module:compose",
"module:pipeline"
] | RFC Deprecate FeatureUnion and make_union
Unless I'm missing something, to me `FeatureUnion` is just a `ColumnTransformer` where all transformers are applied to all features. So it's just a special case of `ColumnTransformer`.
```py
import pandas as pd
from sklearn.pipeline import FeatureUnion
from sklearn.compose im... | 32,112 |
https://github.com/scikit-learn/scikit-learn/issues/32112 | [
"API",
"RFC",
"module:compose",
"module:pipeline"
] | RFC Deprecate FeatureUnion and make_union
Unless I'm missing something, to me `FeatureUnion` is just a `ColumnTransformer` where all transformers are applied to all features. So it's just a special case of `ColumnTransformer`.
```py
import pandas as pd
from sklearn.pipeline import FeatureUnion
from sklearn.compose im... | 32,112 |
https://github.com/scikit-learn/scikit-learn/issues/32112 | [
"API",
"RFC",
"module:compose",
"module:pipeline"
] | RFC Deprecate FeatureUnion and make_union
Unless I'm missing something, to me `FeatureUnion` is just a `ColumnTransformer` where all transformers are applied to all features. So it's just a special case of `ColumnTransformer`.
```py
import pandas as pd
from sklearn.pipeline import FeatureUnion
from sklearn.compose im... | 32,112 |
https://github.com/scikit-learn/scikit-learn/issues/32112 | [
"API",
"RFC",
"module:compose",
"module:pipeline"
] | RFC Deprecate FeatureUnion and make_union
Unless I'm missing something, to me `FeatureUnion` is just a `ColumnTransformer` where all transformers are applied to all features. So it's just a special case of `ColumnTransformer`.
```py
import pandas as pd
from sklearn.pipeline import FeatureUnion
from sklearn.compose im... | 32,112 |
https://github.com/scikit-learn/scikit-learn/issues/32112 | [
"API",
"RFC",
"module:compose",
"module:pipeline"
] | RFC Deprecate FeatureUnion and make_union
Unless I'm missing something, to me `FeatureUnion` is just a `ColumnTransformer` where all transformers are applied to all features. So it's just a special case of `ColumnTransformer`.
```py
import pandas as pd
from sklearn.pipeline import FeatureUnion
from sklearn.compose im... | 32,112 |
https://github.com/scikit-learn/scikit-learn/issues/32112 | [
"API",
"RFC",
"module:compose",
"module:pipeline"
] | RFC Deprecate FeatureUnion and make_union
Unless I'm missing something, to me `FeatureUnion` is just a `ColumnTransformer` where all transformers are applied to all features. So it's just a special case of `ColumnTransformer`.
```py
import pandas as pd
from sklearn.pipeline import FeatureUnion
from sklearn.compose im... | 32,112 |
https://github.com/scikit-learn/scikit-learn/issues/32112 | [
"API",
"RFC",
"module:compose",
"module:pipeline"
] | RFC Deprecate FeatureUnion and make_union
Unless I'm missing something, to me `FeatureUnion` is just a `ColumnTransformer` where all transformers are applied to all features. So it's just a special case of `ColumnTransformer`.
```py
import pandas as pd
from sklearn.pipeline import FeatureUnion
from sklearn.compose im... | 32,112 |
https://github.com/scikit-learn/scikit-learn/issues/32112 | [
"API",
"RFC",
"module:compose",
"module:pipeline"
] | RFC Deprecate FeatureUnion and make_union
Unless I'm missing something, to me `FeatureUnion` is just a `ColumnTransformer` where all transformers are applied to all features. So it's just a special case of `ColumnTransformer`.
```py
import pandas as pd
from sklearn.pipeline import FeatureUnion
from sklearn.compose im... | 32,112 |
https://github.com/scikit-learn/scikit-learn/issues/32112 | [
"API",
"RFC",
"module:compose",
"module:pipeline"
] | RFC Deprecate FeatureUnion and make_union
Unless I'm missing something, to me `FeatureUnion` is just a `ColumnTransformer` where all transformers are applied to all features. So it's just a special case of `ColumnTransformer`.
```py
import pandas as pd
from sklearn.pipeline import FeatureUnion
from sklearn.compose im... | 32,112 |
https://github.com/scikit-learn/scikit-learn/issues/32110 | [
"Performance",
"Needs Benchmarks",
"module:neural_network"
] | Optimize Performance of SGDOptimizer and AdamOptimizer with Vectorized Operations
### Describe the workflow you want to enable
I aim to enable a more efficient training workflow for Multilayer Perceptrons (MLPs) in scikit-learn by optimizing the performance of the `SGDOptimizer` and `AdamOptimizer` classes. Currently... | 32,110 |
https://github.com/scikit-learn/scikit-learn/issues/32110 | [
"Performance",
"Needs Benchmarks",
"module:neural_network"
] | Optimize Performance of SGDOptimizer and AdamOptimizer with Vectorized Operations
### Describe the workflow you want to enable
I aim to enable a more efficient training workflow for Multilayer Perceptrons (MLPs) in scikit-learn by optimizing the performance of the `SGDOptimizer` and `AdamOptimizer` classes. Currently... | 32,110 |
https://github.com/scikit-learn/scikit-learn/issues/32110 | [
"Performance",
"Needs Benchmarks",
"module:neural_network"
] | Optimize Performance of SGDOptimizer and AdamOptimizer with Vectorized Operations
### Describe the workflow you want to enable
I aim to enable a more efficient training workflow for Multilayer Perceptrons (MLPs) in scikit-learn by optimizing the performance of the `SGDOptimizer` and `AdamOptimizer` classes. Currently... | 32,110 |
https://github.com/scikit-learn/scikit-learn/issues/32110 | [
"Performance",
"Needs Benchmarks",
"module:neural_network"
] | Optimize Performance of SGDOptimizer and AdamOptimizer with Vectorized Operations
### Describe the workflow you want to enable
I aim to enable a more efficient training workflow for Multilayer Perceptrons (MLPs) in scikit-learn by optimizing the performance of the `SGDOptimizer` and `AdamOptimizer` classes. Currently... | 32,110 |
https://github.com/scikit-learn/scikit-learn/issues/32110 | [
"Performance",
"Needs Benchmarks",
"module:neural_network"
] | Optimize Performance of SGDOptimizer and AdamOptimizer with Vectorized Operations
### Describe the workflow you want to enable
I aim to enable a more efficient training workflow for Multilayer Perceptrons (MLPs) in scikit-learn by optimizing the performance of the `SGDOptimizer` and `AdamOptimizer` classes. Currently... | 32,110 |
https://github.com/scikit-learn/scikit-learn/issues/32110 | [
"Performance",
"Needs Benchmarks",
"module:neural_network"
] | Optimize Performance of SGDOptimizer and AdamOptimizer with Vectorized Operations
### Describe the workflow you want to enable
I aim to enable a more efficient training workflow for Multilayer Perceptrons (MLPs) in scikit-learn by optimizing the performance of the `SGDOptimizer` and `AdamOptimizer` classes. Currently... | 32,110 |
https://github.com/scikit-learn/scikit-learn/issues/32110 | [
"Performance",
"Needs Benchmarks",
"module:neural_network"
] | Optimize Performance of SGDOptimizer and AdamOptimizer with Vectorized Operations
### Describe the workflow you want to enable
I aim to enable a more efficient training workflow for Multilayer Perceptrons (MLPs) in scikit-learn by optimizing the performance of the `SGDOptimizer` and `AdamOptimizer` classes. Currently... | 32,110 |
https://github.com/scikit-learn/scikit-learn/issues/32110 | [
"Performance",
"Needs Benchmarks",
"module:neural_network"
] | Optimize Performance of SGDOptimizer and AdamOptimizer with Vectorized Operations
### Describe the workflow you want to enable
I aim to enable a more efficient training workflow for Multilayer Perceptrons (MLPs) in scikit-learn by optimizing the performance of the `SGDOptimizer` and `AdamOptimizer` classes. Currently... | 32,110 |
https://github.com/scikit-learn/scikit-learn/issues/32110 | [
"Performance",
"Needs Benchmarks",
"module:neural_network"
] | Optimize Performance of SGDOptimizer and AdamOptimizer with Vectorized Operations
### Describe the workflow you want to enable
I aim to enable a more efficient training workflow for Multilayer Perceptrons (MLPs) in scikit-learn by optimizing the performance of the `SGDOptimizer` and `AdamOptimizer` classes. Currently... | 32,110 |
https://github.com/scikit-learn/scikit-learn/issues/32110 | [
"Performance",
"Needs Benchmarks",
"module:neural_network"
] | Optimize Performance of SGDOptimizer and AdamOptimizer with Vectorized Operations
### Describe the workflow you want to enable
I aim to enable a more efficient training workflow for Multilayer Perceptrons (MLPs) in scikit-learn by optimizing the performance of the `SGDOptimizer` and `AdamOptimizer` classes. Currently... | 32,110 |
https://github.com/scikit-learn/scikit-learn/issues/32110 | [
"Performance",
"Needs Benchmarks",
"module:neural_network"
] | Optimize Performance of SGDOptimizer and AdamOptimizer with Vectorized Operations
### Describe the workflow you want to enable
I aim to enable a more efficient training workflow for Multilayer Perceptrons (MLPs) in scikit-learn by optimizing the performance of the `SGDOptimizer` and `AdamOptimizer` classes. Currently... | 32,110 |
https://github.com/scikit-learn/scikit-learn/issues/32110 | [
"Performance",
"Needs Benchmarks",
"module:neural_network"
] | Optimize Performance of SGDOptimizer and AdamOptimizer with Vectorized Operations
### Describe the workflow you want to enable
I aim to enable a more efficient training workflow for Multilayer Perceptrons (MLPs) in scikit-learn by optimizing the performance of the `SGDOptimizer` and `AdamOptimizer` classes. Currently... | 32,110 |
https://github.com/scikit-learn/scikit-learn/issues/32109 | [
"Enhancement",
"API",
"Needs Decision",
"module:covariance",
"module:linear_model"
] | Add inner max_iter or a smart automatic setting to Lasso inside graphical lasso
`GraphicalLasso` and `GraphicalLassoCV` expose `enet_tol`. They should also expose `enet_max_iter`.
Currently, the `max_iter` of the *outer iteration* is also used for this inner iteration. This is unfortunate, e.g., if you set a small num... | 32,109 |
https://github.com/scikit-learn/scikit-learn/issues/32109 | [
"Enhancement",
"API",
"Needs Decision",
"module:covariance",
"module:linear_model"
] | Add inner max_iter or a smart automatic setting to Lasso inside graphical lasso
`GraphicalLasso` and `GraphicalLassoCV` expose `enet_tol`. They should also expose `enet_max_iter`.
Currently, the `max_iter` of the *outer iteration* is also used for this inner iteration. This is unfortunate, e.g., if you set a small num... | 32,109 |
https://github.com/scikit-learn/scikit-learn/issues/32109 | [
"Enhancement",
"API",
"Needs Decision",
"module:covariance",
"module:linear_model"
] | Add inner max_iter or a smart automatic setting to Lasso inside graphical lasso
`GraphicalLasso` and `GraphicalLassoCV` expose `enet_tol`. They should also expose `enet_max_iter`.
Currently, the `max_iter` of the *outer iteration* is also used for this inner iteration. This is unfortunate, e.g., if you set a small num... | 32,109 |
https://github.com/scikit-learn/scikit-learn/issues/32104 | [
"Bug"
] | FeatureUnion with polars output can error due to duplicate column names
### Describe the bug
FeatureUnion concatenates outputs of its transformers _before_ the `set_output` wrapper renames columns based on `get_feature_names_out` (adding the transformer name prefix). This works with pandas but not polars which does n... | 32,104 |
https://github.com/scikit-learn/scikit-learn/issues/32104 | [
"Bug"
] | FeatureUnion with polars output can error due to duplicate column names
### Describe the bug
FeatureUnion concatenates outputs of its transformers _before_ the `set_output` wrapper renames columns based on `get_feature_names_out` (adding the transformer name prefix). This works with pandas but not polars which does n... | 32,104 |
https://github.com/scikit-learn/scikit-learn/issues/32104 | [
"Bug"
] | FeatureUnion with polars output can error due to duplicate column names
### Describe the bug
FeatureUnion concatenates outputs of its transformers _before_ the `set_output` wrapper renames columns based on `get_feature_names_out` (adding the transformer name prefix). This works with pandas but not polars which does n... | 32,104 |
https://github.com/scikit-learn/scikit-learn/issues/32104 | [
"Bug"
] | FeatureUnion with polars output can error due to duplicate column names
### Describe the bug
FeatureUnion concatenates outputs of its transformers _before_ the `set_output` wrapper renames columns based on `get_feature_names_out` (adding the transformer name prefix). This works with pandas but not polars which does n... | 32,104 |
https://github.com/scikit-learn/scikit-learn/issues/32104 | [
"Bug"
] | FeatureUnion with polars output can error due to duplicate column names
### Describe the bug
FeatureUnion concatenates outputs of its transformers _before_ the `set_output` wrapper renames columns based on `get_feature_names_out` (adding the transformer name prefix). This works with pandas but not polars which does n... | 32,104 |
https://github.com/scikit-learn/scikit-learn/issues/32104 | [
"Bug"
] | FeatureUnion with polars output can error due to duplicate column names
### Describe the bug
FeatureUnion concatenates outputs of its transformers _before_ the `set_output` wrapper renames columns based on `get_feature_names_out` (adding the transformer name prefix). This works with pandas but not polars which does n... | 32,104 |
https://github.com/scikit-learn/scikit-learn/issues/32099 | [
"Bug"
] | DecisionTreeRegressor with absolute error criterion: non-optimal split
### Describe the bug
While working on fixing the issue https://github.com/scikit-learn/scikit-learn/issues/9626, I noticed that in some cases, the current implementation of `DecisionTreeRegressor(criterion="absolute_error")` doesn't not find the o... | 32,099 |
https://github.com/scikit-learn/scikit-learn/issues/32099 | [
"Bug"
] | DecisionTreeRegressor with absolute error criterion: non-optimal split
### Describe the bug
While working on fixing the issue https://github.com/scikit-learn/scikit-learn/issues/9626, I noticed that in some cases, the current implementation of `DecisionTreeRegressor(criterion="absolute_error")` doesn't not find the o... | 32,099 |
https://github.com/scikit-learn/scikit-learn/issues/32099 | [
"Bug"
] | DecisionTreeRegressor with absolute error criterion: non-optimal split
### Describe the bug
While working on fixing the issue https://github.com/scikit-learn/scikit-learn/issues/9626, I noticed that in some cases, the current implementation of `DecisionTreeRegressor(criterion="absolute_error")` doesn't not find the o... | 32,099 |
https://github.com/scikit-learn/scikit-learn/issues/32099 | [
"Bug"
] | DecisionTreeRegressor with absolute error criterion: non-optimal split
### Describe the bug
While working on fixing the issue https://github.com/scikit-learn/scikit-learn/issues/9626, I noticed that in some cases, the current implementation of `DecisionTreeRegressor(criterion="absolute_error")` doesn't not find the o... | 32,099 |
https://github.com/scikit-learn/scikit-learn/issues/32099 | [
"Bug"
] | DecisionTreeRegressor with absolute error criterion: non-optimal split
### Describe the bug
While working on fixing the issue https://github.com/scikit-learn/scikit-learn/issues/9626, I noticed that in some cases, the current implementation of `DecisionTreeRegressor(criterion="absolute_error")` doesn't not find the o... | 32,099 |
https://github.com/scikit-learn/scikit-learn/issues/32099 | [
"Bug"
] | DecisionTreeRegressor with absolute error criterion: non-optimal split
### Describe the bug
While working on fixing the issue https://github.com/scikit-learn/scikit-learn/issues/9626, I noticed that in some cases, the current implementation of `DecisionTreeRegressor(criterion="absolute_error")` doesn't not find the o... | 32,099 |
https://github.com/scikit-learn/scikit-learn/issues/32095 | [
"Bug"
] | Using `fetch_20newsgroups` with multiple pytest workers leads to race
### Describe the bug
When using `pytest-xdist` with several workers to run a test suite that uses `fetch_20newsgroups` as a fixture (`scope="session"`) the dataset shape is sometimes wrong. For example I just had a run where `X.shape=(5902, 68435) ... | 32,095 |
https://github.com/scikit-learn/scikit-learn/issues/32095 | [
"Bug"
] | Using `fetch_20newsgroups` with multiple pytest workers leads to race
### Describe the bug
When using `pytest-xdist` with several workers to run a test suite that uses `fetch_20newsgroups` as a fixture (`scope="session"`) the dataset shape is sometimes wrong. For example I just had a run where `X.shape=(5902, 68435) ... | 32,095 |
https://github.com/scikit-learn/scikit-learn/issues/32095 | [
"Bug"
] | Using `fetch_20newsgroups` with multiple pytest workers leads to race
### Describe the bug
When using `pytest-xdist` with several workers to run a test suite that uses `fetch_20newsgroups` as a fixture (`scope="session"`) the dataset shape is sometimes wrong. For example I just had a run where `X.shape=(5902, 68435) ... | 32,095 |
https://github.com/scikit-learn/scikit-learn/issues/32090 | [
"Bug",
"Documentation"
] | Unpickling ColumnTransformer fitted in 1.6.1 fails in 1.7.1 with AttributeError: _RemainderColsList
### Describe the bug
**Summary**
A `ColumnTransformer` pickled with **scikit-learn 1.6.1** cannot be unpickled with **1.7.1** (and other versions > 1.6.1). The unpickling fails before any method call with:
```bash
A... | 32,090 |
https://github.com/scikit-learn/scikit-learn/issues/32090 | [
"Bug",
"Documentation"
] | Unpickling ColumnTransformer fitted in 1.6.1 fails in 1.7.1 with AttributeError: _RemainderColsList
### Describe the bug
**Summary**
A `ColumnTransformer` pickled with **scikit-learn 1.6.1** cannot be unpickled with **1.7.1** (and other versions > 1.6.1). The unpickling fails before any method call with:
```bash
A... | 32,090 |
https://github.com/scikit-learn/scikit-learn/issues/32090 | [
"Bug",
"Documentation"
] | Unpickling ColumnTransformer fitted in 1.6.1 fails in 1.7.1 with AttributeError: _RemainderColsList
### Describe the bug
**Summary**
A `ColumnTransformer` pickled with **scikit-learn 1.6.1** cannot be unpickled with **1.7.1** (and other versions > 1.6.1). The unpickling fails before any method call with:
```bash
A... | 32,090 |
https://github.com/scikit-learn/scikit-learn/issues/32090 | [
"Bug",
"Documentation"
] | Unpickling ColumnTransformer fitted in 1.6.1 fails in 1.7.1 with AttributeError: _RemainderColsList
### Describe the bug
**Summary**
A `ColumnTransformer` pickled with **scikit-learn 1.6.1** cannot be unpickled with **1.7.1** (and other versions > 1.6.1). The unpickling fails before any method call with:
```bash
A... | 32,090 |
https://github.com/scikit-learn/scikit-learn/issues/32087 | [
"Bug"
] | ⚠️ CI failed on Linux_free_threaded.pylatest_free_threaded (last failure: Sep 27, 2025) ⚠️
**CI is still failing on [Linux_free_threaded.pylatest_free_threaded](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=80471&view=logs&j=c10228e9-6cf7-5c29-593f-d74f893ca1bd)** (Sep 27, 2025)
- test_get_met... | 32,087 |
https://github.com/scikit-learn/scikit-learn/issues/32087 | [
"Bug"
] | ⚠️ CI failed on Linux_free_threaded.pylatest_free_threaded (last failure: Sep 27, 2025) ⚠️
**CI is still failing on [Linux_free_threaded.pylatest_free_threaded](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=80471&view=logs&j=c10228e9-6cf7-5c29-593f-d74f893ca1bd)** (Sep 27, 2025)
- test_get_met... | 32,087 |
https://github.com/scikit-learn/scikit-learn/issues/32087 | [
"Bug"
] | ⚠️ CI failed on Linux_free_threaded.pylatest_free_threaded (last failure: Sep 27, 2025) ⚠️
**CI is still failing on [Linux_free_threaded.pylatest_free_threaded](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=80471&view=logs&j=c10228e9-6cf7-5c29-593f-d74f893ca1bd)** (Sep 27, 2025)
- test_get_met... | 32,087 |
https://github.com/scikit-learn/scikit-learn/issues/32087 | [
"Bug"
] | ⚠️ CI failed on Linux_free_threaded.pylatest_free_threaded (last failure: Sep 27, 2025) ⚠️
**CI is still failing on [Linux_free_threaded.pylatest_free_threaded](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=80471&view=logs&j=c10228e9-6cf7-5c29-593f-d74f893ca1bd)** (Sep 27, 2025)
- test_get_met... | 32,087 |
https://github.com/scikit-learn/scikit-learn/issues/32086 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_Runs.pylatest_conda_forge_mkl (last failure: Sep 03, 2025) ⚠️
**CI failed on [Linux_Runs.pylatest_conda_forge_mkl](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=79590&view=logs&j=dde5042c-7464-5d47-9507-31bdd2ee0a3a)** (Sep 03, 2025)
- Test Collection Failure
COMMENT:
##... | 32,086 |
https://github.com/scikit-learn/scikit-learn/issues/32083 | [
"Documentation"
] | 1.1.8 LARS Lasso at Mathematical Formulation
### Describe the issue linked to the documentation
Instead of giving a vector result, the LARS solution consists of a curve denoting the solution for each value of the l1 norm of the parameter vector.
* not a curve
* "curve" is not computed at every point
* infinitely man... | 32,083 |
https://github.com/scikit-learn/scikit-learn/issues/32083 | [
"Documentation"
] | 1.1.8 LARS Lasso at Mathematical Formulation
### Describe the issue linked to the documentation
Instead of giving a vector result, the LARS solution consists of a curve denoting the solution for each value of the l1 norm of the parameter vector.
* not a curve
* "curve" is not computed at every point
* infinitely man... | 32,083 |
https://github.com/scikit-learn/scikit-learn/issues/32083 | [
"Documentation"
] | 1.1.8 LARS Lasso at Mathematical Formulation
### Describe the issue linked to the documentation
Instead of giving a vector result, the LARS solution consists of a curve denoting the solution for each value of the l1 norm of the parameter vector.
* not a curve
* "curve" is not computed at every point
* infinitely man... | 32,083 |
https://github.com/scikit-learn/scikit-learn/issues/32083 | [
"Documentation"
] | 1.1.8 LARS Lasso at Mathematical Formulation
### Describe the issue linked to the documentation
Instead of giving a vector result, the LARS solution consists of a curve denoting the solution for each value of the l1 norm of the parameter vector.
* not a curve
* "curve" is not computed at every point
* infinitely man... | 32,083 |
https://github.com/scikit-learn/scikit-learn/issues/32083 | [
"Documentation"
] | 1.1.8 LARS Lasso at Mathematical Formulation
### Describe the issue linked to the documentation
Instead of giving a vector result, the LARS solution consists of a curve denoting the solution for each value of the l1 norm of the parameter vector.
* not a curve
* "curve" is not computed at every point
* infinitely man... | 32,083 |
https://github.com/scikit-learn/scikit-learn/issues/32083 | [
"Documentation"
] | 1.1.8 LARS Lasso at Mathematical Formulation
### Describe the issue linked to the documentation
Instead of giving a vector result, the LARS solution consists of a curve denoting the solution for each value of the l1 norm of the parameter vector.
* not a curve
* "curve" is not computed at every point
* infinitely man... | 32,083 |
https://github.com/scikit-learn/scikit-learn/issues/32076 | [
"Enhancement",
"help wanted"
] | ```TargetEncoder``` should take ```groups``` as an argument
### Describe the workflow you want to enable
The current implementation of TargetEncoder uses ```KFold```-cross-validation to avoid data leakage. In cases of longitudinal or clustered data, it is desirable to ensure that rows belonging to the same group or c... | 32,076 |
https://github.com/scikit-learn/scikit-learn/issues/32076 | [
"Enhancement",
"help wanted"
] | ```TargetEncoder``` should take ```groups``` as an argument
### Describe the workflow you want to enable
The current implementation of TargetEncoder uses ```KFold```-cross-validation to avoid data leakage. In cases of longitudinal or clustered data, it is desirable to ensure that rows belonging to the same group or c... | 32,076 |
https://github.com/scikit-learn/scikit-learn/issues/32076 | [
"Enhancement",
"help wanted"
] | ```TargetEncoder``` should take ```groups``` as an argument
### Describe the workflow you want to enable
The current implementation of TargetEncoder uses ```KFold```-cross-validation to avoid data leakage. In cases of longitudinal or clustered data, it is desirable to ensure that rows belonging to the same group or c... | 32,076 |
https://github.com/scikit-learn/scikit-learn/issues/32076 | [
"Enhancement",
"help wanted"
] | ```TargetEncoder``` should take ```groups``` as an argument
### Describe the workflow you want to enable
The current implementation of TargetEncoder uses ```KFold```-cross-validation to avoid data leakage. In cases of longitudinal or clustered data, it is desirable to ensure that rows belonging to the same group or c... | 32,076 |
https://github.com/scikit-learn/scikit-learn/issues/32076 | [
"Enhancement",
"help wanted"
] | ```TargetEncoder``` should take ```groups``` as an argument
### Describe the workflow you want to enable
The current implementation of TargetEncoder uses ```KFold```-cross-validation to avoid data leakage. In cases of longitudinal or clustered data, it is desirable to ensure that rows belonging to the same group or c... | 32,076 |
https://github.com/scikit-learn/scikit-learn/issues/32076 | [
"Enhancement",
"help wanted"
] | ```TargetEncoder``` should take ```groups``` as an argument
### Describe the workflow you want to enable
The current implementation of TargetEncoder uses ```KFold```-cross-validation to avoid data leakage. In cases of longitudinal or clustered data, it is desirable to ensure that rows belonging to the same group or c... | 32,076 |
https://github.com/scikit-learn/scikit-learn/issues/32076 | [
"Enhancement",
"help wanted"
] | ```TargetEncoder``` should take ```groups``` as an argument
### Describe the workflow you want to enable
The current implementation of TargetEncoder uses ```KFold```-cross-validation to avoid data leakage. In cases of longitudinal or clustered data, it is desirable to ensure that rows belonging to the same group or c... | 32,076 |
https://github.com/scikit-learn/scikit-learn/issues/32076 | [
"Enhancement",
"help wanted"
] | ```TargetEncoder``` should take ```groups``` as an argument
### Describe the workflow you want to enable
The current implementation of TargetEncoder uses ```KFold```-cross-validation to avoid data leakage. In cases of longitudinal or clustered data, it is desirable to ensure that rows belonging to the same group or c... | 32,076 |
https://github.com/scikit-learn/scikit-learn/issues/32076 | [
"Enhancement",
"help wanted"
] | ```TargetEncoder``` should take ```groups``` as an argument
### Describe the workflow you want to enable
The current implementation of TargetEncoder uses ```KFold```-cross-validation to avoid data leakage. In cases of longitudinal or clustered data, it is desirable to ensure that rows belonging to the same group or c... | 32,076 |
https://github.com/scikit-learn/scikit-learn/issues/32076 | [
"Enhancement",
"help wanted"
] | ```TargetEncoder``` should take ```groups``` as an argument
### Describe the workflow you want to enable
The current implementation of TargetEncoder uses ```KFold```-cross-validation to avoid data leakage. In cases of longitudinal or clustered data, it is desirable to ensure that rows belonging to the same group or c... | 32,076 |
https://github.com/scikit-learn/scikit-learn/issues/32076 | [
"Enhancement",
"help wanted"
] | ```TargetEncoder``` should take ```groups``` as an argument
### Describe the workflow you want to enable
The current implementation of TargetEncoder uses ```KFold```-cross-validation to avoid data leakage. In cases of longitudinal or clustered data, it is desirable to ensure that rows belonging to the same group or c... | 32,076 |
https://github.com/scikit-learn/scikit-learn/issues/32076 | [
"Enhancement",
"help wanted"
] | ```TargetEncoder``` should take ```groups``` as an argument
### Describe the workflow you want to enable
The current implementation of TargetEncoder uses ```KFold```-cross-validation to avoid data leakage. In cases of longitudinal or clustered data, it is desirable to ensure that rows belonging to the same group or c... | 32,076 |
https://github.com/scikit-learn/scikit-learn/issues/32075 | [
"RFC"
] | RFC new fitted attributes for LogisticRegressionCV
Contributes to #11865.
### Fitted Attributes
After the removal of `multi_class` and any OvR-logic in `LogisticRegressionCV` in #32073, there are a few fitted attributes that have now (or always had) a strange data format (I neglect l1_ratios in the following for ease... | 32,075 |
https://github.com/scikit-learn/scikit-learn/issues/32075 | [
"RFC"
] | RFC new fitted attributes for LogisticRegressionCV
Contributes to #11865.
### Fitted Attributes
After the removal of `multi_class` and any OvR-logic in `LogisticRegressionCV` in #32073, there are a few fitted attributes that have now (or always had) a strange data format (I neglect l1_ratios in the following for ease... | 32,075 |
https://github.com/scikit-learn/scikit-learn/issues/32072 | [
"Bug",
"Needs Triage"
] | LogisticRegressionCV intercept is wrong
### Describe the bug
The intercept calculated by `LogisticRegressionCV` is wrong.
A bit related to #11865.
### Steps/Code to Reproduce
```python
import numpy as np
from sklearn.datasets import load_iris
from sklearn.linear_model import LogisticRegression, LogisticRegressionCV... | 32,072 |
https://github.com/scikit-learn/scikit-learn/issues/32067 | [
"New Feature",
"Needs Triage"
] | Enhance the warning message for metadata default value change
### Describe the workflow you want to enable
Currently the warning raised for [Deprecation / Default Value Change](https://scikit-learn.org/stable/auto_examples/miscellaneous/plot_metadata_routing.html#deprecation-default-value-change)
is quite generic
```... | 32,067 |
https://github.com/scikit-learn/scikit-learn/issues/32062 | [
"Bug",
"Needs Investigation"
] | Regressor Prediction Makes a Negative Y Offset
### Describe the bug
Hi, I've found a strange situation where regressor prediction makes a negative Y offset. See an orange line on my picture below.
Here is my py file and json data:
[test_scikit.zip](https://github.com/user-attachments/files/22069020/test_scikit.zip)
... | 32,062 |
https://github.com/scikit-learn/scikit-learn/issues/32062 | [
"Bug",
"Needs Investigation"
] | Regressor Prediction Makes a Negative Y Offset
### Describe the bug
Hi, I've found a strange situation where regressor prediction makes a negative Y offset. See an orange line on my picture below.
Here is my py file and json data:
[test_scikit.zip](https://github.com/user-attachments/files/22069020/test_scikit.zip)
... | 32,062 |
https://github.com/scikit-learn/scikit-learn/issues/32062 | [
"Bug",
"Needs Investigation"
] | Regressor Prediction Makes a Negative Y Offset
### Describe the bug
Hi, I've found a strange situation where regressor prediction makes a negative Y offset. See an orange line on my picture below.
Here is my py file and json data:
[test_scikit.zip](https://github.com/user-attachments/files/22069020/test_scikit.zip)
... | 32,062 |
https://github.com/scikit-learn/scikit-learn/issues/32062 | [
"Bug",
"Needs Investigation"
] | Regressor Prediction Makes a Negative Y Offset
### Describe the bug
Hi, I've found a strange situation where regressor prediction makes a negative Y offset. See an orange line on my picture below.
Here is my py file and json data:
[test_scikit.zip](https://github.com/user-attachments/files/22069020/test_scikit.zip)
... | 32,062 |
https://github.com/scikit-learn/scikit-learn/issues/32062 | [
"Bug",
"Needs Investigation"
] | Regressor Prediction Makes a Negative Y Offset
### Describe the bug
Hi, I've found a strange situation where regressor prediction makes a negative Y offset. See an orange line on my picture below.
Here is my py file and json data:
[test_scikit.zip](https://github.com/user-attachments/files/22069020/test_scikit.zip)
... | 32,062 |
https://github.com/scikit-learn/scikit-learn/issues/32062 | [
"Bug",
"Needs Investigation"
] | Regressor Prediction Makes a Negative Y Offset
### Describe the bug
Hi, I've found a strange situation where regressor prediction makes a negative Y offset. See an orange line on my picture below.
Here is my py file and json data:
[test_scikit.zip](https://github.com/user-attachments/files/22069020/test_scikit.zip)
... | 32,062 |
https://github.com/scikit-learn/scikit-learn/issues/32062 | [
"Bug",
"Needs Investigation"
] | Regressor Prediction Makes a Negative Y Offset
### Describe the bug
Hi, I've found a strange situation where regressor prediction makes a negative Y offset. See an orange line on my picture below.
Here is my py file and json data:
[test_scikit.zip](https://github.com/user-attachments/files/22069020/test_scikit.zip)
... | 32,062 |
https://github.com/scikit-learn/scikit-learn/issues/32062 | [
"Bug",
"Needs Investigation"
] | Regressor Prediction Makes a Negative Y Offset
### Describe the bug
Hi, I've found a strange situation where regressor prediction makes a negative Y offset. See an orange line on my picture below.
Here is my py file and json data:
[test_scikit.zip](https://github.com/user-attachments/files/22069020/test_scikit.zip)
... | 32,062 |
https://github.com/scikit-learn/scikit-learn/issues/32062 | [
"Bug",
"Needs Investigation"
] | Regressor Prediction Makes a Negative Y Offset
### Describe the bug
Hi, I've found a strange situation where regressor prediction makes a negative Y offset. See an orange line on my picture below.
Here is my py file and json data:
[test_scikit.zip](https://github.com/user-attachments/files/22069020/test_scikit.zip)
... | 32,062 |
https://github.com/scikit-learn/scikit-learn/issues/32062 | [
"Bug",
"Needs Investigation"
] | Regressor Prediction Makes a Negative Y Offset
### Describe the bug
Hi, I've found a strange situation where regressor prediction makes a negative Y offset. See an orange line on my picture below.
Here is my py file and json data:
[test_scikit.zip](https://github.com/user-attachments/files/22069020/test_scikit.zip)
... | 32,062 |
https://github.com/scikit-learn/scikit-learn/issues/32062 | [
"Bug",
"Needs Investigation"
] | Regressor Prediction Makes a Negative Y Offset
### Describe the bug
Hi, I've found a strange situation where regressor prediction makes a negative Y offset. See an orange line on my picture below.
Here is my py file and json data:
[test_scikit.zip](https://github.com/user-attachments/files/22069020/test_scikit.zip)
... | 32,062 |
https://github.com/scikit-learn/scikit-learn/issues/32049 | [
"Documentation",
"module:metrics"
] | The dcg_score and ndcg_score documentation are hard to understand
### Describe the issue linked to the documentation
The documentation for the `dcg_score` and `ndcg_score` leave much to be desired.
I believe this is also a by-product of competing definitions of the discount cumulative gains (DCG) and normalised DCG ... | 32,049 |
https://github.com/scikit-learn/scikit-learn/issues/32048 | [
"New Feature",
"Needs Decision - Include Feature"
] | Leiden Clustering
### Describe the workflow you want to enable
The "Leiden" Clustering algorithm is considered one of the most powerful clustering algorithms, often outperforming competitors by a wide margin.
The algorithm fulfils the inclusion criteria: its now 6 years old, has some 5200 citations.
Currently, it ... | 32,048 |
https://github.com/scikit-learn/scikit-learn/issues/32048 | [
"New Feature",
"Needs Decision - Include Feature"
] | Leiden Clustering
### Describe the workflow you want to enable
The "Leiden" Clustering algorithm is considered one of the most powerful clustering algorithms, often outperforming competitors by a wide margin.
The algorithm fulfils the inclusion criteria: its now 6 years old, has some 5200 citations.
Currently, it ... | 32,048 |
https://github.com/scikit-learn/scikit-learn/issues/32048 | [
"New Feature",
"Needs Decision - Include Feature"
] | Leiden Clustering
### Describe the workflow you want to enable
The "Leiden" Clustering algorithm is considered one of the most powerful clustering algorithms, often outperforming competitors by a wide margin.
The algorithm fulfils the inclusion criteria: its now 6 years old, has some 5200 citations.
Currently, it ... | 32,048 |
https://github.com/scikit-learn/scikit-learn/issues/32048 | [
"New Feature",
"Needs Decision - Include Feature"
] | Leiden Clustering
### Describe the workflow you want to enable
The "Leiden" Clustering algorithm is considered one of the most powerful clustering algorithms, often outperforming competitors by a wide margin.
The algorithm fulfils the inclusion criteria: its now 6 years old, has some 5200 citations.
Currently, it ... | 32,048 |
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