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/27441 | [
"Documentation",
"help wanted"
] | partial_dependence() with method recursion computes conditional partial dependence for trees
### Describe the bug
For the case of correlated predictors (clearly highly common) the `sklearn.inspection.partial_dependence()` function gives different answers for `method` = "recursion" and `method` = "brute", see my [po... | 27,441 |
https://github.com/scikit-learn/scikit-learn/issues/27441 | [
"Documentation",
"help wanted"
] | partial_dependence() with method recursion computes conditional partial dependence for trees
### Describe the bug
For the case of correlated predictors (clearly highly common) the `sklearn.inspection.partial_dependence()` function gives different answers for `method` = "recursion" and `method` = "brute", see my [po... | 27,441 |
https://github.com/scikit-learn/scikit-learn/issues/27441 | [
"Documentation",
"help wanted"
] | partial_dependence() with method recursion computes conditional partial dependence for trees
### Describe the bug
For the case of correlated predictors (clearly highly common) the `sklearn.inspection.partial_dependence()` function gives different answers for `method` = "recursion" and `method` = "brute", see my [po... | 27,441 |
https://github.com/scikit-learn/scikit-learn/issues/27441 | [
"Documentation",
"help wanted"
] | partial_dependence() with method recursion computes conditional partial dependence for trees
### Describe the bug
For the case of correlated predictors (clearly highly common) the `sklearn.inspection.partial_dependence()` function gives different answers for `method` = "recursion" and `method` = "brute", see my [po... | 27,441 |
https://github.com/scikit-learn/scikit-learn/issues/27441 | [
"Documentation",
"help wanted"
] | partial_dependence() with method recursion computes conditional partial dependence for trees
### Describe the bug
For the case of correlated predictors (clearly highly common) the `sklearn.inspection.partial_dependence()` function gives different answers for `method` = "recursion" and `method` = "brute", see my [po... | 27,441 |
https://github.com/scikit-learn/scikit-learn/issues/27441 | [
"Documentation",
"help wanted"
] | partial_dependence() with method recursion computes conditional partial dependence for trees
### Describe the bug
For the case of correlated predictors (clearly highly common) the `sklearn.inspection.partial_dependence()` function gives different answers for `method` = "recursion" and `method` = "brute", see my [po... | 27,441 |
https://github.com/scikit-learn/scikit-learn/issues/27441 | [
"Documentation",
"help wanted"
] | partial_dependence() with method recursion computes conditional partial dependence for trees
### Describe the bug
For the case of correlated predictors (clearly highly common) the `sklearn.inspection.partial_dependence()` function gives different answers for `method` = "recursion" and `method` = "brute", see my [po... | 27,441 |
https://github.com/scikit-learn/scikit-learn/issues/27441 | [
"Documentation",
"help wanted"
] | partial_dependence() with method recursion computes conditional partial dependence for trees
### Describe the bug
For the case of correlated predictors (clearly highly common) the `sklearn.inspection.partial_dependence()` function gives different answers for `method` = "recursion" and `method` = "brute", see my [po... | 27,441 |
https://github.com/scikit-learn/scikit-learn/issues/27441 | [
"Documentation",
"help wanted"
] | partial_dependence() with method recursion computes conditional partial dependence for trees
### Describe the bug
For the case of correlated predictors (clearly highly common) the `sklearn.inspection.partial_dependence()` function gives different answers for `method` = "recursion" and `method` = "brute", see my [po... | 27,441 |
https://github.com/scikit-learn/scikit-learn/issues/27439 | [
"API",
"Needs Decision"
] | _safe_indexing being the only *private* thing listed in classes.rst
`_safe_indexing` is the only _private_ tool we have listed in `classes.rst`.
`_safe_indexing` was also mentioned in https://github.com/scikit-learn/scikit-learn/issues/15801, but this issue is to have the discussion about this very limited scope.
... | 27,439 |
https://github.com/scikit-learn/scikit-learn/issues/27439 | [
"API",
"Needs Decision"
] | _safe_indexing being the only *private* thing listed in classes.rst
`_safe_indexing` is the only _private_ tool we have listed in `classes.rst`.
`_safe_indexing` was also mentioned in https://github.com/scikit-learn/scikit-learn/issues/15801, but this issue is to have the discussion about this very limited scope.
... | 27,439 |
https://github.com/scikit-learn/scikit-learn/issues/27439 | [
"API",
"Needs Decision"
] | _safe_indexing being the only *private* thing listed in classes.rst
`_safe_indexing` is the only _private_ tool we have listed in `classes.rst`.
`_safe_indexing` was also mentioned in https://github.com/scikit-learn/scikit-learn/issues/15801, but this issue is to have the discussion about this very limited scope.
... | 27,439 |
https://github.com/scikit-learn/scikit-learn/issues/27439 | [
"API",
"Needs Decision"
] | _safe_indexing being the only *private* thing listed in classes.rst
`_safe_indexing` is the only _private_ tool we have listed in `classes.rst`.
`_safe_indexing` was also mentioned in https://github.com/scikit-learn/scikit-learn/issues/15801, but this issue is to have the discussion about this very limited scope.
... | 27,439 |
https://github.com/scikit-learn/scikit-learn/issues/27439 | [
"API",
"Needs Decision"
] | _safe_indexing being the only *private* thing listed in classes.rst
`_safe_indexing` is the only _private_ tool we have listed in `classes.rst`.
`_safe_indexing` was also mentioned in https://github.com/scikit-learn/scikit-learn/issues/15801, but this issue is to have the discussion about this very limited scope.
... | 27,439 |
https://github.com/scikit-learn/scikit-learn/issues/27439 | [
"API",
"Needs Decision"
] | _safe_indexing being the only *private* thing listed in classes.rst
`_safe_indexing` is the only _private_ tool we have listed in `classes.rst`.
`_safe_indexing` was also mentioned in https://github.com/scikit-learn/scikit-learn/issues/15801, but this issue is to have the discussion about this very limited scope.
... | 27,439 |
https://github.com/scikit-learn/scikit-learn/issues/27436 | [
"Enhancement"
] | Misleading error message for HDBSCAN exception
### Describe the bug
Before computing the minimum spanning tree, HDBSCAN checks if the number of connected components in the mutual-reachability graph is greater than 1. Here is the snippet -
https://github.com/scikit-learn/scikit-learn/blob/55a65a2fa5653257225d7e184... | 27,436 |
https://github.com/scikit-learn/scikit-learn/issues/27436 | [
"Enhancement"
] | Misleading error message for HDBSCAN exception
### Describe the bug
Before computing the minimum spanning tree, HDBSCAN checks if the number of connected components in the mutual-reachability graph is greater than 1. Here is the snippet -
https://github.com/scikit-learn/scikit-learn/blob/55a65a2fa5653257225d7e184... | 27,436 |
https://github.com/scikit-learn/scikit-learn/issues/27436 | [
"Enhancement"
] | Misleading error message for HDBSCAN exception
### Describe the bug
Before computing the minimum spanning tree, HDBSCAN checks if the number of connected components in the mutual-reachability graph is greater than 1. Here is the snippet -
https://github.com/scikit-learn/scikit-learn/blob/55a65a2fa5653257225d7e184... | 27,436 |
https://github.com/scikit-learn/scikit-learn/issues/27435 | [
"New Feature",
"Needs Decision"
] | Enable `drop='constant'` in OneHotEncoder
### Describe the workflow you want to enable
Currently the `drop` parameter in `OneHotEncoder` objects support `{‘first’, ‘if_binary’, <array-of-features>, None}` as potential choices, with a strong encouragement to use `None` to allow proper use of regularized linear model... | 27,435 |
https://github.com/scikit-learn/scikit-learn/issues/27435 | [
"New Feature",
"Needs Decision"
] | Enable `drop='constant'` in OneHotEncoder
### Describe the workflow you want to enable
Currently the `drop` parameter in `OneHotEncoder` objects support `{‘first’, ‘if_binary’, <array-of-features>, None}` as potential choices, with a strong encouragement to use `None` to allow proper use of regularized linear model... | 27,435 |
https://github.com/scikit-learn/scikit-learn/issues/27435 | [
"New Feature",
"Needs Decision"
] | Enable `drop='constant'` in OneHotEncoder
### Describe the workflow you want to enable
Currently the `drop` parameter in `OneHotEncoder` objects support `{‘first’, ‘if_binary’, <array-of-features>, None}` as potential choices, with a strong encouragement to use `None` to allow proper use of regularized linear model... | 27,435 |
https://github.com/scikit-learn/scikit-learn/issues/27435 | [
"New Feature",
"Needs Decision"
] | Enable `drop='constant'` in OneHotEncoder
### Describe the workflow you want to enable
Currently the `drop` parameter in `OneHotEncoder` objects support `{‘first’, ‘if_binary’, <array-of-features>, None}` as potential choices, with a strong encouragement to use `None` to allow proper use of regularized linear model... | 27,435 |
https://github.com/scikit-learn/scikit-learn/issues/27435 | [
"New Feature",
"Needs Decision"
] | Enable `drop='constant'` in OneHotEncoder
### Describe the workflow you want to enable
Currently the `drop` parameter in `OneHotEncoder` objects support `{‘first’, ‘if_binary’, <array-of-features>, None}` as potential choices, with a strong encouragement to use `None` to allow proper use of regularized linear model... | 27,435 |
https://github.com/scikit-learn/scikit-learn/issues/27435 | [
"New Feature",
"Needs Decision"
] | Enable `drop='constant'` in OneHotEncoder
### Describe the workflow you want to enable
Currently the `drop` parameter in `OneHotEncoder` objects support `{‘first’, ‘if_binary’, <array-of-features>, None}` as potential choices, with a strong encouragement to use `None` to allow proper use of regularized linear model... | 27,435 |
https://github.com/scikit-learn/scikit-learn/issues/27434 | [
"Bug",
"Needs Triage"
] | `distance_threshold` Behavior with Cosine Metric in AgglomerativeClustering
### Describe the bug
In the documentation for AgglomerativeClustering, the distance_threshold parameter is described as:
> The linkage distance threshold at or above which clusters will not be merged. If not None, n_clusters must be None a... | 27,434 |
https://github.com/scikit-learn/scikit-learn/issues/27433 | [
"New Feature",
"Moderate"
] | Implement `make_sparse_spd_matrix` using a sparse memory layout from the start
### Describe the workflow you want to enable
As discussed in #27359, `make_sparse_spd_matrix` actually returns a dense numpy array (with many zero values).
I think it should be possible to rewrite this code to compose operations on sp... | 27,433 |
https://github.com/scikit-learn/scikit-learn/issues/27433 | [
"New Feature",
"Moderate"
] | Implement `make_sparse_spd_matrix` using a sparse memory layout from the start
### Describe the workflow you want to enable
As discussed in #27359, `make_sparse_spd_matrix` actually returns a dense numpy array (with many zero values).
I think it should be possible to rewrite this code to compose operations on sp... | 27,433 |
https://github.com/scikit-learn/scikit-learn/issues/27433 | [
"New Feature",
"Moderate"
] | Implement `make_sparse_spd_matrix` using a sparse memory layout from the start
### Describe the workflow you want to enable
As discussed in #27359, `make_sparse_spd_matrix` actually returns a dense numpy array (with many zero values).
I think it should be possible to rewrite this code to compose operations on sp... | 27,433 |
https://github.com/scikit-learn/scikit-learn/issues/27433 | [
"New Feature",
"Moderate"
] | Implement `make_sparse_spd_matrix` using a sparse memory layout from the start
### Describe the workflow you want to enable
As discussed in #27359, `make_sparse_spd_matrix` actually returns a dense numpy array (with many zero values).
I think it should be possible to rewrite this code to compose operations on sp... | 27,433 |
https://github.com/scikit-learn/scikit-learn/issues/27433 | [
"New Feature",
"Moderate"
] | Implement `make_sparse_spd_matrix` using a sparse memory layout from the start
### Describe the workflow you want to enable
As discussed in #27359, `make_sparse_spd_matrix` actually returns a dense numpy array (with many zero values).
I think it should be possible to rewrite this code to compose operations on sp... | 27,433 |
https://github.com/scikit-learn/scikit-learn/issues/27433 | [
"New Feature",
"Moderate"
] | Implement `make_sparse_spd_matrix` using a sparse memory layout from the start
### Describe the workflow you want to enable
As discussed in #27359, `make_sparse_spd_matrix` actually returns a dense numpy array (with many zero values).
I think it should be possible to rewrite this code to compose operations on sp... | 27,433 |
https://github.com/scikit-learn/scikit-learn/issues/27433 | [
"New Feature",
"Moderate"
] | Implement `make_sparse_spd_matrix` using a sparse memory layout from the start
### Describe the workflow you want to enable
As discussed in #27359, `make_sparse_spd_matrix` actually returns a dense numpy array (with many zero values).
I think it should be possible to rewrite this code to compose operations on sp... | 27,433 |
https://github.com/scikit-learn/scikit-learn/issues/27433 | [
"New Feature",
"Moderate"
] | Implement `make_sparse_spd_matrix` using a sparse memory layout from the start
### Describe the workflow you want to enable
As discussed in #27359, `make_sparse_spd_matrix` actually returns a dense numpy array (with many zero values).
I think it should be possible to rewrite this code to compose operations on sp... | 27,433 |
https://github.com/scikit-learn/scikit-learn/issues/27433 | [
"New Feature",
"Moderate"
] | Implement `make_sparse_spd_matrix` using a sparse memory layout from the start
### Describe the workflow you want to enable
As discussed in #27359, `make_sparse_spd_matrix` actually returns a dense numpy array (with many zero values).
I think it should be possible to rewrite this code to compose operations on sp... | 27,433 |
https://github.com/scikit-learn/scikit-learn/issues/27430 | [
"Build / CI"
] | Catching deprecation warnings from examples
Up-to-now, we never check deprecation warnings that are raised when executing our examples.
I assume that we could scrap the RST generated file to find such warning:
```python
from pathlib import Path
from pprint import pprint
from sklearn.utils.fixes import Visible... | 27,430 |
https://github.com/scikit-learn/scikit-learn/issues/27430 | [
"Build / CI"
] | Catching deprecation warnings from examples
Up-to-now, we never check deprecation warnings that are raised when executing our examples.
I assume that we could scrap the RST generated file to find such warning:
```python
from pathlib import Path
from pprint import pprint
from sklearn.utils.fixes import Visible... | 27,430 |
https://github.com/scikit-learn/scikit-learn/issues/27430 | [
"Build / CI"
] | Catching deprecation warnings from examples
Up-to-now, we never check deprecation warnings that are raised when executing our examples.
I assume that we could scrap the RST generated file to find such warning:
```python
from pathlib import Path
from pprint import pprint
from sklearn.utils.fixes import Visible... | 27,430 |
https://github.com/scikit-learn/scikit-learn/issues/27430 | [
"Build / CI"
] | Catching deprecation warnings from examples
Up-to-now, we never check deprecation warnings that are raised when executing our examples.
I assume that we could scrap the RST generated file to find such warning:
```python
from pathlib import Path
from pprint import pprint
from sklearn.utils.fixes import Visible... | 27,430 |
https://github.com/scikit-learn/scikit-learn/issues/27430 | [
"Build / CI"
] | Catching deprecation warnings from examples
Up-to-now, we never check deprecation warnings that are raised when executing our examples.
I assume that we could scrap the RST generated file to find such warning:
```python
from pathlib import Path
from pprint import pprint
from sklearn.utils.fixes import Visible... | 27,430 |
https://github.com/scikit-learn/scikit-learn/issues/27430 | [
"Build / CI"
] | Catching deprecation warnings from examples
Up-to-now, we never check deprecation warnings that are raised when executing our examples.
I assume that we could scrap the RST generated file to find such warning:
```python
from pathlib import Path
from pprint import pprint
from sklearn.utils.fixes import Visible... | 27,430 |
https://github.com/scikit-learn/scikit-learn/issues/27430 | [
"Build / CI"
] | Catching deprecation warnings from examples
Up-to-now, we never check deprecation warnings that are raised when executing our examples.
I assume that we could scrap the RST generated file to find such warning:
```python
from pathlib import Path
from pprint import pprint
from sklearn.utils.fixes import Visible... | 27,430 |
https://github.com/scikit-learn/scikit-learn/issues/27430 | [
"Build / CI"
] | Catching deprecation warnings from examples
Up-to-now, we never check deprecation warnings that are raised when executing our examples.
I assume that we could scrap the RST generated file to find such warning:
```python
from pathlib import Path
from pprint import pprint
from sklearn.utils.fixes import Visible... | 27,430 |
https://github.com/scikit-learn/scikit-learn/issues/27429 | [
"Documentation"
] | Sphinx cross-referencing error "reference target not found" in nilearn doc build with sklearn 1.3.1
### Describe the issue linked to the documentation
The same Sphinx cross-referencing issue as https://github.com/scikit-learn/scikit-learn/issues/26761 (fixed in https://github.com/scikit-learn/scikit-learn/pull/26770)... | 27,429 |
https://github.com/scikit-learn/scikit-learn/issues/27427 | [
"Bug",
"Array API"
] | [Array API] `stable_cumsum` uses `np.float64` rather than `xp.float64`
### Describe the bug
[stable_cumsum](https://github.com/scikit-learn/scikit-learn/blob/ba7d86956da03aa4fd230b1bbe8df57b63cf2dc0/sklearn/utils/extmath.py#L1188-L1227) has been adapted for Array API support, but when provided a pytorch array, fail... | 27,427 |
https://github.com/scikit-learn/scikit-learn/issues/27426 | [
"Performance",
"Regression"
] | PERF Regression in HistGradientBoostingClassifier with cython 3
Related to https://github.com/scikit-learn/scikit-learn/issues/27086 but specialized to the regression observed in `HistGradientBoostingClassifier` for better tracking.
With cython 3, it looks that the speed of 2 parts has changed.
- the initial binni... | 27,426 |
https://github.com/scikit-learn/scikit-learn/issues/27426 | [
"Performance",
"Regression"
] | PERF Regression in HistGradientBoostingClassifier with cython 3
Related to https://github.com/scikit-learn/scikit-learn/issues/27086 but specialized to the regression observed in `HistGradientBoostingClassifier` for better tracking.
With cython 3, it looks that the speed of 2 parts has changed.
- the initial binni... | 27,426 |
https://github.com/scikit-learn/scikit-learn/issues/27426 | [
"Performance",
"Regression"
] | PERF Regression in HistGradientBoostingClassifier with cython 3
Related to https://github.com/scikit-learn/scikit-learn/issues/27086 but specialized to the regression observed in `HistGradientBoostingClassifier` for better tracking.
With cython 3, it looks that the speed of 2 parts has changed.
- the initial binni... | 27,426 |
https://github.com/scikit-learn/scikit-learn/issues/27426 | [
"Performance",
"Regression"
] | PERF Regression in HistGradientBoostingClassifier with cython 3
Related to https://github.com/scikit-learn/scikit-learn/issues/27086 but specialized to the regression observed in `HistGradientBoostingClassifier` for better tracking.
With cython 3, it looks that the speed of 2 parts has changed.
- the initial binni... | 27,426 |
https://github.com/scikit-learn/scikit-learn/issues/27426 | [
"Performance",
"Regression"
] | PERF Regression in HistGradientBoostingClassifier with cython 3
Related to https://github.com/scikit-learn/scikit-learn/issues/27086 but specialized to the regression observed in `HistGradientBoostingClassifier` for better tracking.
With cython 3, it looks that the speed of 2 parts has changed.
- the initial binni... | 27,426 |
https://github.com/scikit-learn/scikit-learn/issues/27426 | [
"Performance",
"Regression"
] | PERF Regression in HistGradientBoostingClassifier with cython 3
Related to https://github.com/scikit-learn/scikit-learn/issues/27086 but specialized to the regression observed in `HistGradientBoostingClassifier` for better tracking.
With cython 3, it looks that the speed of 2 parts has changed.
- the initial binni... | 27,426 |
https://github.com/scikit-learn/scikit-learn/issues/27426 | [
"Performance",
"Regression"
] | PERF Regression in HistGradientBoostingClassifier with cython 3
Related to https://github.com/scikit-learn/scikit-learn/issues/27086 but specialized to the regression observed in `HistGradientBoostingClassifier` for better tracking.
With cython 3, it looks that the speed of 2 parts has changed.
- the initial binni... | 27,426 |
https://github.com/scikit-learn/scikit-learn/issues/27426 | [
"Performance",
"Regression"
] | PERF Regression in HistGradientBoostingClassifier with cython 3
Related to https://github.com/scikit-learn/scikit-learn/issues/27086 but specialized to the regression observed in `HistGradientBoostingClassifier` for better tracking.
With cython 3, it looks that the speed of 2 parts has changed.
- the initial binni... | 27,426 |
https://github.com/scikit-learn/scikit-learn/issues/27426 | [
"Performance",
"Regression"
] | PERF Regression in HistGradientBoostingClassifier with cython 3
Related to https://github.com/scikit-learn/scikit-learn/issues/27086 but specialized to the regression observed in `HistGradientBoostingClassifier` for better tracking.
With cython 3, it looks that the speed of 2 parts has changed.
- the initial binni... | 27,426 |
https://github.com/scikit-learn/scikit-learn/issues/27426 | [
"Performance",
"Regression"
] | PERF Regression in HistGradientBoostingClassifier with cython 3
Related to https://github.com/scikit-learn/scikit-learn/issues/27086 but specialized to the regression observed in `HistGradientBoostingClassifier` for better tracking.
With cython 3, it looks that the speed of 2 parts has changed.
- the initial binni... | 27,426 |
https://github.com/scikit-learn/scikit-learn/issues/27426 | [
"Performance",
"Regression"
] | PERF Regression in HistGradientBoostingClassifier with cython 3
Related to https://github.com/scikit-learn/scikit-learn/issues/27086 but specialized to the regression observed in `HistGradientBoostingClassifier` for better tracking.
With cython 3, it looks that the speed of 2 parts has changed.
- the initial binni... | 27,426 |
https://github.com/scikit-learn/scikit-learn/issues/27426 | [
"Performance",
"Regression"
] | PERF Regression in HistGradientBoostingClassifier with cython 3
Related to https://github.com/scikit-learn/scikit-learn/issues/27086 but specialized to the regression observed in `HistGradientBoostingClassifier` for better tracking.
With cython 3, it looks that the speed of 2 parts has changed.
- the initial binni... | 27,426 |
https://github.com/scikit-learn/scikit-learn/issues/27426 | [
"Performance",
"Regression"
] | PERF Regression in HistGradientBoostingClassifier with cython 3
Related to https://github.com/scikit-learn/scikit-learn/issues/27086 but specialized to the regression observed in `HistGradientBoostingClassifier` for better tracking.
With cython 3, it looks that the speed of 2 parts has changed.
- the initial binni... | 27,426 |
https://github.com/scikit-learn/scikit-learn/issues/27422 | [
"Needs Decision"
] | HalvingGridSearchCV giving non-optimal results with min_resources='exhaust'
### Describe the bug
I am using `HalvingGridSearchCV` with 160 combinations and 1050 samples. When I use `min_resources` with `'exhaust'`, I get 6 iterations with the last iteration including 5 candidates and 640 samples. The process starts... | 27,422 |
https://github.com/scikit-learn/scikit-learn/issues/27422 | [
"Needs Decision"
] | HalvingGridSearchCV giving non-optimal results with min_resources='exhaust'
### Describe the bug
I am using `HalvingGridSearchCV` with 160 combinations and 1050 samples. When I use `min_resources` with `'exhaust'`, I get 6 iterations with the last iteration including 5 candidates and 640 samples. The process starts... | 27,422 |
https://github.com/scikit-learn/scikit-learn/issues/27422 | [
"Needs Decision"
] | HalvingGridSearchCV giving non-optimal results with min_resources='exhaust'
### Describe the bug
I am using `HalvingGridSearchCV` with 160 combinations and 1050 samples. When I use `min_resources` with `'exhaust'`, I get 6 iterations with the last iteration including 5 candidates and 640 samples. The process starts... | 27,422 |
https://github.com/scikit-learn/scikit-learn/issues/27422 | [
"Needs Decision"
] | HalvingGridSearchCV giving non-optimal results with min_resources='exhaust'
### Describe the bug
I am using `HalvingGridSearchCV` with 160 combinations and 1050 samples. When I use `min_resources` with `'exhaust'`, I get 6 iterations with the last iteration including 5 candidates and 640 samples. The process starts... | 27,422 |
https://github.com/scikit-learn/scikit-learn/issues/27422 | [
"Needs Decision"
] | HalvingGridSearchCV giving non-optimal results with min_resources='exhaust'
### Describe the bug
I am using `HalvingGridSearchCV` with 160 combinations and 1050 samples. When I use `min_resources` with `'exhaust'`, I get 6 iterations with the last iteration including 5 candidates and 640 samples. The process starts... | 27,422 |
https://github.com/scikit-learn/scikit-learn/issues/27422 | [
"Needs Decision"
] | HalvingGridSearchCV giving non-optimal results with min_resources='exhaust'
### Describe the bug
I am using `HalvingGridSearchCV` with 160 combinations and 1050 samples. When I use `min_resources` with `'exhaust'`, I get 6 iterations with the last iteration including 5 candidates and 640 samples. The process starts... | 27,422 |
https://github.com/scikit-learn/scikit-learn/issues/27422 | [
"Needs Decision"
] | HalvingGridSearchCV giving non-optimal results with min_resources='exhaust'
### Describe the bug
I am using `HalvingGridSearchCV` with 160 combinations and 1050 samples. When I use `min_resources` with `'exhaust'`, I get 6 iterations with the last iteration including 5 candidates and 640 samples. The process starts... | 27,422 |
https://github.com/scikit-learn/scikit-learn/issues/27422 | [
"Needs Decision"
] | HalvingGridSearchCV giving non-optimal results with min_resources='exhaust'
### Describe the bug
I am using `HalvingGridSearchCV` with 160 combinations and 1050 samples. When I use `min_resources` with `'exhaust'`, I get 6 iterations with the last iteration including 5 candidates and 640 samples. The process starts... | 27,422 |
https://github.com/scikit-learn/scikit-learn/issues/27422 | [
"Needs Decision"
] | HalvingGridSearchCV giving non-optimal results with min_resources='exhaust'
### Describe the bug
I am using `HalvingGridSearchCV` with 160 combinations and 1050 samples. When I use `min_resources` with `'exhaust'`, I get 6 iterations with the last iteration including 5 candidates and 640 samples. The process starts... | 27,422 |
https://github.com/scikit-learn/scikit-learn/issues/27422 | [
"Needs Decision"
] | HalvingGridSearchCV giving non-optimal results with min_resources='exhaust'
### Describe the bug
I am using `HalvingGridSearchCV` with 160 combinations and 1050 samples. When I use `min_resources` with `'exhaust'`, I get 6 iterations with the last iteration including 5 candidates and 640 samples. The process starts... | 27,422 |
https://github.com/scikit-learn/scikit-learn/issues/27422 | [
"Needs Decision"
] | HalvingGridSearchCV giving non-optimal results with min_resources='exhaust'
### Describe the bug
I am using `HalvingGridSearchCV` with 160 combinations and 1050 samples. When I use `min_resources` with `'exhaust'`, I get 6 iterations with the last iteration including 5 candidates and 640 samples. The process starts... | 27,422 |
https://github.com/scikit-learn/scikit-learn/issues/27422 | [
"Needs Decision"
] | HalvingGridSearchCV giving non-optimal results with min_resources='exhaust'
### Describe the bug
I am using `HalvingGridSearchCV` with 160 combinations and 1050 samples. When I use `min_resources` with `'exhaust'`, I get 6 iterations with the last iteration including 5 candidates and 640 samples. The process starts... | 27,422 |
https://github.com/scikit-learn/scikit-learn/issues/27422 | [
"Needs Decision"
] | HalvingGridSearchCV giving non-optimal results with min_resources='exhaust'
### Describe the bug
I am using `HalvingGridSearchCV` with 160 combinations and 1050 samples. When I use `min_resources` with `'exhaust'`, I get 6 iterations with the last iteration including 5 candidates and 640 samples. The process starts... | 27,422 |
https://github.com/scikit-learn/scikit-learn/issues/27422 | [
"Needs Decision"
] | HalvingGridSearchCV giving non-optimal results with min_resources='exhaust'
### Describe the bug
I am using `HalvingGridSearchCV` with 160 combinations and 1050 samples. When I use `min_resources` with `'exhaust'`, I get 6 iterations with the last iteration including 5 candidates and 640 samples. The process starts... | 27,422 |
https://github.com/scikit-learn/scikit-learn/issues/27422 | [
"Needs Decision"
] | HalvingGridSearchCV giving non-optimal results with min_resources='exhaust'
### Describe the bug
I am using `HalvingGridSearchCV` with 160 combinations and 1050 samples. When I use `min_resources` with `'exhaust'`, I get 6 iterations with the last iteration including 5 candidates and 640 samples. The process starts... | 27,422 |
https://github.com/scikit-learn/scikit-learn/issues/27422 | [
"Needs Decision"
] | HalvingGridSearchCV giving non-optimal results with min_resources='exhaust'
### Describe the bug
I am using `HalvingGridSearchCV` with 160 combinations and 1050 samples. When I use `min_resources` with `'exhaust'`, I get 6 iterations with the last iteration including 5 candidates and 640 samples. The process starts... | 27,422 |
https://github.com/scikit-learn/scikit-learn/issues/27422 | [
"Needs Decision"
] | HalvingGridSearchCV giving non-optimal results with min_resources='exhaust'
### Describe the bug
I am using `HalvingGridSearchCV` with 160 combinations and 1050 samples. When I use `min_resources` with `'exhaust'`, I get 6 iterations with the last iteration including 5 candidates and 640 samples. The process starts... | 27,422 |
https://github.com/scikit-learn/scikit-learn/issues/27422 | [
"Needs Decision"
] | HalvingGridSearchCV giving non-optimal results with min_resources='exhaust'
### Describe the bug
I am using `HalvingGridSearchCV` with 160 combinations and 1050 samples. When I use `min_resources` with `'exhaust'`, I get 6 iterations with the last iteration including 5 candidates and 640 samples. The process starts... | 27,422 |
https://github.com/scikit-learn/scikit-learn/issues/27416 | [
"Build / CI",
"pypy",
"cython",
"Needs Investigation"
] | ⚠️ CI failed on Linux_Nightly_PyPy.pypy3 ⚠️
**CI is still failing on [Linux_Nightly_PyPy.pypy3](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=60231&view=logs&j=0b16f832-29d6-5b92-1c23-eb006f606a66)** (Oct 21, 2023)
Unable to find junit file. Please see link for details.
COMMENT:
There is a cr... | 27,416 |
https://github.com/scikit-learn/scikit-learn/issues/27416 | [
"Build / CI",
"pypy",
"cython",
"Needs Investigation"
] | ⚠️ CI failed on Linux_Nightly_PyPy.pypy3 ⚠️
**CI is still failing on [Linux_Nightly_PyPy.pypy3](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=60231&view=logs&j=0b16f832-29d6-5b92-1c23-eb006f606a66)** (Oct 21, 2023)
Unable to find junit file. Please see link for details.
COMMENT:
Maybe @mattip... | 27,416 |
https://github.com/scikit-learn/scikit-learn/issues/27416 | [
"Build / CI",
"pypy",
"cython",
"Needs Investigation"
] | ⚠️ CI failed on Linux_Nightly_PyPy.pypy3 ⚠️
**CI is still failing on [Linux_Nightly_PyPy.pypy3](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=60231&view=logs&j=0b16f832-29d6-5b92-1c23-eb006f606a66)** (Oct 21, 2023)
Unable to find junit file. Please see link for details.
COMMENT:
This is a pro... | 27,416 |
https://github.com/scikit-learn/scikit-learn/issues/27416 | [
"Build / CI",
"pypy",
"cython",
"Needs Investigation"
] | ⚠️ CI failed on Linux_Nightly_PyPy.pypy3 ⚠️
**CI is still failing on [Linux_Nightly_PyPy.pypy3](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=60231&view=logs&j=0b16f832-29d6-5b92-1c23-eb006f606a66)** (Oct 21, 2023)
Unable to find junit file. Please see link for details.
COMMENT:
Thanks very m... | 27,416 |
https://github.com/scikit-learn/scikit-learn/issues/27416 | [
"Build / CI",
"pypy",
"cython",
"Needs Investigation"
] | ⚠️ CI failed on Linux_Nightly_PyPy.pypy3 ⚠️
**CI is still failing on [Linux_Nightly_PyPy.pypy3](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=60231&view=logs&j=0b16f832-29d6-5b92-1c23-eb006f606a66)** (Oct 21, 2023)
Unable to find junit file. Please see link for details.
COMMENT:
Same error wi... | 27,416 |
https://github.com/scikit-learn/scikit-learn/issues/27416 | [
"Build / CI",
"pypy",
"cython",
"Needs Investigation"
] | ⚠️ CI failed on Linux_Nightly_PyPy.pypy3 ⚠️
**CI is still failing on [Linux_Nightly_PyPy.pypy3](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=60231&view=logs&j=0b16f832-29d6-5b92-1c23-eb006f606a66)** (Oct 21, 2023)
Unable to find junit file. Please see link for details.
COMMENT:
This is a bug... | 27,416 |
https://github.com/scikit-learn/scikit-learn/issues/27416 | [
"Build / CI",
"pypy",
"cython",
"Needs Investigation"
] | ⚠️ CI failed on Linux_Nightly_PyPy.pypy3 ⚠️
**CI is still failing on [Linux_Nightly_PyPy.pypy3](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=60231&view=logs&j=0b16f832-29d6-5b92-1c23-eb006f606a66)** (Oct 21, 2023)
Unable to find junit file. Please see link for details.
COMMENT:
Could you rer... | 27,416 |
https://github.com/scikit-learn/scikit-learn/issues/27416 | [
"Build / CI",
"pypy",
"cython",
"Needs Investigation"
] | ⚠️ CI failed on Linux_Nightly_PyPy.pypy3 ⚠️
**CI is still failing on [Linux_Nightly_PyPy.pypy3](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=60231&view=logs&j=0b16f832-29d6-5b92-1c23-eb006f606a66)** (Oct 21, 2023)
Unable to find junit file. Please see link for details.
COMMENT:
Voila!
Its w... | 27,416 |
https://github.com/scikit-learn/scikit-learn/issues/27416 | [
"Build / CI",
"pypy",
"cython",
"Needs Investigation"
] | ⚠️ CI failed on Linux_Nightly_PyPy.pypy3 ⚠️
**CI is still failing on [Linux_Nightly_PyPy.pypy3](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=60231&view=logs&j=0b16f832-29d6-5b92-1c23-eb006f606a66)** (Oct 21, 2023)
Unable to find junit file. Please see link for details.
COMMENT:
Sorry for the... | 27,416 |
https://github.com/scikit-learn/scikit-learn/issues/27416 | [
"Build / CI",
"pypy",
"cython",
"Needs Investigation"
] | ⚠️ CI failed on Linux_Nightly_PyPy.pypy3 ⚠️
**CI is still failing on [Linux_Nightly_PyPy.pypy3](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=60231&view=logs&j=0b16f832-29d6-5b92-1c23-eb006f606a66)** (Oct 21, 2023)
Unable to find junit file. Please see link for details.
COMMENT:
Can this be c... | 27,416 |
https://github.com/scikit-learn/scikit-learn/issues/27416 | [
"Build / CI",
"pypy",
"cython",
"Needs Investigation"
] | ⚠️ CI failed on Linux_Nightly_PyPy.pypy3 ⚠️
**CI is still failing on [Linux_Nightly_PyPy.pypy3](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=60231&view=logs&j=0b16f832-29d6-5b92-1c23-eb006f606a66)** (Oct 21, 2023)
Unable to find junit file. Please see link for details.
COMMENT:
Yes, it can b... | 27,416 |
https://github.com/scikit-learn/scikit-learn/issues/27416 | [
"Build / CI",
"pypy",
"cython",
"Needs Investigation"
] | ⚠️ CI failed on Linux_Nightly_PyPy.pypy3 ⚠️
**CI is still failing on [Linux_Nightly_PyPy.pypy3](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=60231&view=logs&j=0b16f832-29d6-5b92-1c23-eb006f606a66)** (Oct 21, 2023)
Unable to find junit file. Please see link for details.
COMMENT:
The `TypeErro... | 27,416 |
https://github.com/scikit-learn/scikit-learn/issues/27395 | [
"Needs Triage"
] | ⚠️ CI failed on Wheel builder ⚠️
**CI failed on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/6211387188)** (Sep 17, 2023)
COMMENT:
## CI is no longer failing! ✅
[Successful run](https://github.com/scikit-learn/scikit-learn/actions/runs/6217941758) on Sep 18, 2023 | 27,395 |
https://github.com/scikit-learn/scikit-learn/issues/27394 | [
"Needs Triage"
] | ⚠️ 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=59257&view=logs&j=67fbb25f-e417-50be-be55-3b1e9637fce5)** (Sep 17, 2023)
- test_pairwise_distances_argkmin[52-csr_matrix-float32-parallel_on_X-braycur... | 27,394 |
https://github.com/scikit-learn/scikit-learn/issues/27394 | [
"Needs Triage"
] | ⚠️ 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=59257&view=logs&j=67fbb25f-e417-50be-be55-3b1e9637fce5)** (Sep 17, 2023)
- test_pairwise_distances_argkmin[52-csr_matrix-float32-parallel_on_X-braycur... | 27,394 |
https://github.com/scikit-learn/scikit-learn/issues/27391 | [
"Bug",
"Needs Triage"
] | k_means clustering: AttributeError: 'NoneType' object has no attribute 'split'
### Describe the bug
k_means is broken and systematically throws an ```AttributeError: 'NoneType' object has no attribute 'split'``` no matter what kind of input I give. I have Python 3.10, numpy 1.24.3 scikit-learn 1.2.1 and threadpoolctl... | 27,391 |
https://github.com/scikit-learn/scikit-learn/issues/27379 | [
"Bug",
"Needs Triage"
] | In certain cases, the results of fit_transform and transform are not identical.
### Describe the bug
`sklearn.feature_extraction.text.TfidfVectorizer`'s fit_transform and transform methods yield different results in specific scenarios when processing the same text data.
### Steps/Code to Reproduce
In this case, bot... | 27,379 |
https://github.com/scikit-learn/scikit-learn/issues/27375 | [
"Documentation"
] | Adding documentation about related library: Concrete ML, for privacy preserving ML
### Describe the issue linked to the documentation
We would like to add Concrete ML in the documentation. Concrete ML is an open-source package, providing privacy-preserving ML, thanks to so-called fully homomorphic encryption. Concr... | 27,375 |
https://github.com/scikit-learn/scikit-learn/issues/27375 | [
"Documentation"
] | Adding documentation about related library: Concrete ML, for privacy preserving ML
### Describe the issue linked to the documentation
We would like to add Concrete ML in the documentation. Concrete ML is an open-source package, providing privacy-preserving ML, thanks to so-called fully homomorphic encryption. Concr... | 27,375 |
https://github.com/scikit-learn/scikit-learn/issues/27375 | [
"Documentation"
] | Adding documentation about related library: Concrete ML, for privacy preserving ML
### Describe the issue linked to the documentation
We would like to add Concrete ML in the documentation. Concrete ML is an open-source package, providing privacy-preserving ML, thanks to so-called fully homomorphic encryption. Concr... | 27,375 |
https://github.com/scikit-learn/scikit-learn/issues/27373 | [
"Enhancement"
] | QuantileTransformer's default subsampling introduces artefacts for unbounded distributions
### Describe the bug
The default behaviour of subsampling in the QuantileTransformer introduces artefacts when the input data originates from an unbounded distribution and the transformed dataset is (significantly) larger than ... | 27,373 |
https://github.com/scikit-learn/scikit-learn/issues/27373 | [
"Enhancement"
] | QuantileTransformer's default subsampling introduces artefacts for unbounded distributions
### Describe the bug
The default behaviour of subsampling in the QuantileTransformer introduces artefacts when the input data originates from an unbounded distribution and the transformed dataset is (significantly) larger than ... | 27,373 |
https://github.com/scikit-learn/scikit-learn/issues/27373 | [
"Enhancement"
] | QuantileTransformer's default subsampling introduces artefacts for unbounded distributions
### Describe the bug
The default behaviour of subsampling in the QuantileTransformer introduces artefacts when the input data originates from an unbounded distribution and the transformed dataset is (significantly) larger than ... | 27,373 |
https://github.com/scikit-learn/scikit-learn/issues/27373 | [
"Enhancement"
] | QuantileTransformer's default subsampling introduces artefacts for unbounded distributions
### Describe the bug
The default behaviour of subsampling in the QuantileTransformer introduces artefacts when the input data originates from an unbounded distribution and the transformed dataset is (significantly) larger than ... | 27,373 |
https://github.com/scikit-learn/scikit-learn/issues/27373 | [
"Enhancement"
] | QuantileTransformer's default subsampling introduces artefacts for unbounded distributions
### Describe the bug
The default behaviour of subsampling in the QuantileTransformer introduces artefacts when the input data originates from an unbounded distribution and the transformed dataset is (significantly) larger than ... | 27,373 |
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