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/30935 | [
"Bug"
] | The default token pattern in CountVectorizer breaks Indic sentences into non-sensical tokens
### Describe the bug
The default `token_pattern` in `CountVectorizer` is `r"(?u)\b\w\w+\b"` which tokenizes Indic texts in a wrong way - breaks whitespace tokenized words into multiple chunks and even omits several valid char... | 30,935 |
https://github.com/scikit-learn/scikit-learn/issues/30935 | [
"Bug"
] | The default token pattern in CountVectorizer breaks Indic sentences into non-sensical tokens
### Describe the bug
The default `token_pattern` in `CountVectorizer` is `r"(?u)\b\w\w+\b"` which tokenizes Indic texts in a wrong way - breaks whitespace tokenized words into multiple chunks and even omits several valid char... | 30,935 |
https://github.com/scikit-learn/scikit-learn/issues/30934 | [
"Documentation"
] | DOC Missing doc string in tests present in sklearn/linear_model/_glm/tests/test_glm.py
### Describe the issue related to documentation
The file `sklearn/linear_model/_glm/tests/test_glm.py` has the following tests without any doc string to describe what these functions aim to test.
- test_glm_wrong_y_range
- test_war... | 30,934 |
https://github.com/scikit-learn/scikit-learn/issues/30934 | [
"Documentation"
] | DOC Missing doc string in tests present in sklearn/linear_model/_glm/tests/test_glm.py
### Describe the issue related to documentation
The file `sklearn/linear_model/_glm/tests/test_glm.py` has the following tests without any doc string to describe what these functions aim to test.
- test_glm_wrong_y_range
- test_war... | 30,934 |
https://github.com/scikit-learn/scikit-learn/issues/30934 | [
"Documentation"
] | DOC Missing doc string in tests present in sklearn/linear_model/_glm/tests/test_glm.py
### Describe the issue related to documentation
The file `sklearn/linear_model/_glm/tests/test_glm.py` has the following tests without any doc string to describe what these functions aim to test.
- test_glm_wrong_y_range
- test_war... | 30,934 |
https://github.com/scikit-learn/scikit-learn/issues/30924 | [
"Bug"
] | KBinsDiscretizer uniform strategy bin assignment wrong due to floating point multiplication
### Describe the bug
KBinsDiscretizer uniform strategy uses numpy.linspace to make bin edges.
numpy.linspace works out a delta like: delta = (max - min)/num_bins
Then the bin edges are computed: delta * n
The issue is the... | 30,924 |
https://github.com/scikit-learn/scikit-learn/issues/30924 | [
"Bug"
] | KBinsDiscretizer uniform strategy bin assignment wrong due to floating point multiplication
### Describe the bug
KBinsDiscretizer uniform strategy uses numpy.linspace to make bin edges.
numpy.linspace works out a delta like: delta = (max - min)/num_bins
Then the bin edges are computed: delta * n
The issue is the... | 30,924 |
https://github.com/scikit-learn/scikit-learn/issues/30924 | [
"Bug"
] | KBinsDiscretizer uniform strategy bin assignment wrong due to floating point multiplication
### Describe the bug
KBinsDiscretizer uniform strategy uses numpy.linspace to make bin edges.
numpy.linspace works out a delta like: delta = (max - min)/num_bins
Then the bin edges are computed: delta * n
The issue is the... | 30,924 |
https://github.com/scikit-learn/scikit-learn/issues/30924 | [
"Bug"
] | KBinsDiscretizer uniform strategy bin assignment wrong due to floating point multiplication
### Describe the bug
KBinsDiscretizer uniform strategy uses numpy.linspace to make bin edges.
numpy.linspace works out a delta like: delta = (max - min)/num_bins
Then the bin edges are computed: delta * n
The issue is the... | 30,924 |
https://github.com/scikit-learn/scikit-learn/issues/30924 | [
"Bug"
] | KBinsDiscretizer uniform strategy bin assignment wrong due to floating point multiplication
### Describe the bug
KBinsDiscretizer uniform strategy uses numpy.linspace to make bin edges.
numpy.linspace works out a delta like: delta = (max - min)/num_bins
Then the bin edges are computed: delta * n
The issue is the... | 30,924 |
https://github.com/scikit-learn/scikit-learn/issues/30924 | [
"Bug"
] | KBinsDiscretizer uniform strategy bin assignment wrong due to floating point multiplication
### Describe the bug
KBinsDiscretizer uniform strategy uses numpy.linspace to make bin edges.
numpy.linspace works out a delta like: delta = (max - min)/num_bins
Then the bin edges are computed: delta * n
The issue is the... | 30,924 |
https://github.com/scikit-learn/scikit-learn/issues/30921 | [
"Bug",
"Needs Info"
] | Persistent UserWarning about KMeans Memory Leak on Windows Despite Applying Suggested Fixes
### Describe the bug
Issue Description
When running code involving GaussianMixture (or KMeans), a UserWarning about a known memory leak on Windows with MKL is raised, even after implementing the suggested workaround (OMP_NUM_T... | 30,921 |
https://github.com/scikit-learn/scikit-learn/issues/30921 | [
"Bug",
"Needs Info"
] | Persistent UserWarning about KMeans Memory Leak on Windows Despite Applying Suggested Fixes
### Describe the bug
Issue Description
When running code involving GaussianMixture (or KMeans), a UserWarning about a known memory leak on Windows with MKL is raised, even after implementing the suggested workaround (OMP_NUM_T... | 30,921 |
https://github.com/scikit-learn/scikit-learn/issues/30921 | [
"Bug",
"Needs Info"
] | Persistent UserWarning about KMeans Memory Leak on Windows Despite Applying Suggested Fixes
### Describe the bug
Issue Description
When running code involving GaussianMixture (or KMeans), a UserWarning about a known memory leak on Windows with MKL is raised, even after implementing the suggested workaround (OMP_NUM_T... | 30,921 |
https://github.com/scikit-learn/scikit-learn/issues/30921 | [
"Bug",
"Needs Info"
] | Persistent UserWarning about KMeans Memory Leak on Windows Despite Applying Suggested Fixes
### Describe the bug
Issue Description
When running code involving GaussianMixture (or KMeans), a UserWarning about a known memory leak on Windows with MKL is raised, even after implementing the suggested workaround (OMP_NUM_T... | 30,921 |
https://github.com/scikit-learn/scikit-learn/issues/30921 | [
"Bug",
"Needs Info"
] | Persistent UserWarning about KMeans Memory Leak on Windows Despite Applying Suggested Fixes
### Describe the bug
Issue Description
When running code involving GaussianMixture (or KMeans), a UserWarning about a known memory leak on Windows with MKL is raised, even after implementing the suggested workaround (OMP_NUM_T... | 30,921 |
https://github.com/scikit-learn/scikit-learn/issues/30921 | [
"Bug",
"Needs Info"
] | Persistent UserWarning about KMeans Memory Leak on Windows Despite Applying Suggested Fixes
### Describe the bug
Issue Description
When running code involving GaussianMixture (or KMeans), a UserWarning about a known memory leak on Windows with MKL is raised, even after implementing the suggested workaround (OMP_NUM_T... | 30,921 |
https://github.com/scikit-learn/scikit-learn/issues/30921 | [
"Bug",
"Needs Info"
] | Persistent UserWarning about KMeans Memory Leak on Windows Despite Applying Suggested Fixes
### Describe the bug
Issue Description
When running code involving GaussianMixture (or KMeans), a UserWarning about a known memory leak on Windows with MKL is raised, even after implementing the suggested workaround (OMP_NUM_T... | 30,921 |
https://github.com/scikit-learn/scikit-learn/issues/30921 | [
"Bug",
"Needs Info"
] | Persistent UserWarning about KMeans Memory Leak on Windows Despite Applying Suggested Fixes
### Describe the bug
Issue Description
When running code involving GaussianMixture (or KMeans), a UserWarning about a known memory leak on Windows with MKL is raised, even after implementing the suggested workaround (OMP_NUM_T... | 30,921 |
https://github.com/scikit-learn/scikit-learn/issues/30921 | [
"Bug",
"Needs Info"
] | Persistent UserWarning about KMeans Memory Leak on Windows Despite Applying Suggested Fixes
### Describe the bug
Issue Description
When running code involving GaussianMixture (or KMeans), a UserWarning about a known memory leak on Windows with MKL is raised, even after implementing the suggested workaround (OMP_NUM_T... | 30,921 |
https://github.com/scikit-learn/scikit-learn/issues/30921 | [
"Bug",
"Needs Info"
] | Persistent UserWarning about KMeans Memory Leak on Windows Despite Applying Suggested Fixes
### Describe the bug
Issue Description
When running code involving GaussianMixture (or KMeans), a UserWarning about a known memory leak on Windows with MKL is raised, even after implementing the suggested workaround (OMP_NUM_T... | 30,921 |
https://github.com/scikit-learn/scikit-learn/issues/30921 | [
"Bug",
"Needs Info"
] | Persistent UserWarning about KMeans Memory Leak on Windows Despite Applying Suggested Fixes
### Describe the bug
Issue Description
When running code involving GaussianMixture (or KMeans), a UserWarning about a known memory leak on Windows with MKL is raised, even after implementing the suggested workaround (OMP_NUM_T... | 30,921 |
https://github.com/scikit-learn/scikit-learn/issues/30921 | [
"Bug",
"Needs Info"
] | Persistent UserWarning about KMeans Memory Leak on Windows Despite Applying Suggested Fixes
### Describe the bug
Issue Description
When running code involving GaussianMixture (or KMeans), a UserWarning about a known memory leak on Windows with MKL is raised, even after implementing the suggested workaround (OMP_NUM_T... | 30,921 |
https://github.com/scikit-learn/scikit-learn/issues/30921 | [
"Bug",
"Needs Info"
] | Persistent UserWarning about KMeans Memory Leak on Windows Despite Applying Suggested Fixes
### Describe the bug
Issue Description
When running code involving GaussianMixture (or KMeans), a UserWarning about a known memory leak on Windows with MKL is raised, even after implementing the suggested workaround (OMP_NUM_T... | 30,921 |
https://github.com/scikit-learn/scikit-learn/issues/30921 | [
"Bug",
"Needs Info"
] | Persistent UserWarning about KMeans Memory Leak on Windows Despite Applying Suggested Fixes
### Describe the bug
Issue Description
When running code involving GaussianMixture (or KMeans), a UserWarning about a known memory leak on Windows with MKL is raised, even after implementing the suggested workaround (OMP_NUM_T... | 30,921 |
https://github.com/scikit-learn/scikit-learn/issues/30917 | [
"Bug"
] | DecisionTreeClassifier having unexpected behaviour with 'min_weight_fraction_leaf=0.5'
### Describe the bug
When fitting DecisionTreeClassifier on a duplicated sample set (i.e. each sample repeated by two), the result is not the same as when fitting on the original sample set. This only happens for 'min_weight_fracti... | 30,917 |
https://github.com/scikit-learn/scikit-learn/issues/30917 | [
"Bug"
] | DecisionTreeClassifier having unexpected behaviour with 'min_weight_fraction_leaf=0.5'
### Describe the bug
When fitting DecisionTreeClassifier on a duplicated sample set (i.e. each sample repeated by two), the result is not the same as when fitting on the original sample set. This only happens for 'min_weight_fracti... | 30,917 |
https://github.com/scikit-learn/scikit-learn/issues/30917 | [
"Bug"
] | DecisionTreeClassifier having unexpected behaviour with 'min_weight_fraction_leaf=0.5'
### Describe the bug
When fitting DecisionTreeClassifier on a duplicated sample set (i.e. each sample repeated by two), the result is not the same as when fitting on the original sample set. This only happens for 'min_weight_fracti... | 30,917 |
https://github.com/scikit-learn/scikit-learn/issues/30917 | [
"Bug"
] | DecisionTreeClassifier having unexpected behaviour with 'min_weight_fraction_leaf=0.5'
### Describe the bug
When fitting DecisionTreeClassifier on a duplicated sample set (i.e. each sample repeated by two), the result is not the same as when fitting on the original sample set. This only happens for 'min_weight_fracti... | 30,917 |
https://github.com/scikit-learn/scikit-learn/issues/30917 | [
"Bug"
] | DecisionTreeClassifier having unexpected behaviour with 'min_weight_fraction_leaf=0.5'
### Describe the bug
When fitting DecisionTreeClassifier on a duplicated sample set (i.e. each sample repeated by two), the result is not the same as when fitting on the original sample set. This only happens for 'min_weight_fracti... | 30,917 |
https://github.com/scikit-learn/scikit-learn/issues/30917 | [
"Bug"
] | DecisionTreeClassifier having unexpected behaviour with 'min_weight_fraction_leaf=0.5'
### Describe the bug
When fitting DecisionTreeClassifier on a duplicated sample set (i.e. each sample repeated by two), the result is not the same as when fitting on the original sample set. This only happens for 'min_weight_fracti... | 30,917 |
https://github.com/scikit-learn/scikit-learn/issues/30917 | [
"Bug"
] | DecisionTreeClassifier having unexpected behaviour with 'min_weight_fraction_leaf=0.5'
### Describe the bug
When fitting DecisionTreeClassifier on a duplicated sample set (i.e. each sample repeated by two), the result is not the same as when fitting on the original sample set. This only happens for 'min_weight_fracti... | 30,917 |
https://github.com/scikit-learn/scikit-learn/issues/30913 | [
"Documentation",
"Needs Triage"
] | Typo in _k_means_lloyd.pyx
### Describe the issue linked to the documentation
I noticed that in the lloyd_iter_chunked_sparse function of _k_means_lloyd.pyx, there is a potential typo in the comment for handling an empty array. It reads (starting on line 280):
"An empty array was passed, do nothing and return early ... | 30,913 |
https://github.com/scikit-learn/scikit-learn/issues/30910 | [
"Bug",
"Needs Triage"
] | Wrong result in log_loss when labels and corresponding y_pred columns are not ordered
### Describe the bug
Log loss is not computed correctly when labels (and their corresponding columns in `y_pred`) are not in ascending (for numbers) / lexicographic (for strings) order.
### Steps/Code to Reproduce
```
from sklear... | 30,910 |
https://github.com/scikit-learn/scikit-learn/issues/30909 | [
"RFC"
] | Improve `pos_label` switching for metrics
Supercedes #26758
Switching `pos_label` for metrics, involves some manipulation for `predict_proba` (switch column you pass) and `decision_function` (for binary, multiply by -1) as you must pass the values for the positive class.
In discussions in #26758 we thought of two ... | 30,909 |
https://github.com/scikit-learn/scikit-learn/issues/30909 | [
"RFC"
] | Improve `pos_label` switching for metrics
Supercedes #26758
Switching `pos_label` for metrics, involves some manipulation for `predict_proba` (switch column you pass) and `decision_function` (for binary, multiply by -1) as you must pass the values for the positive class.
In discussions in #26758 we thought of two ... | 30,909 |
https://github.com/scikit-learn/scikit-learn/issues/30909 | [
"RFC"
] | Improve `pos_label` switching for metrics
Supercedes #26758
Switching `pos_label` for metrics, involves some manipulation for `predict_proba` (switch column you pass) and `decision_function` (for binary, multiply by -1) as you must pass the values for the positive class.
In discussions in #26758 we thought of two ... | 30,909 |
https://github.com/scikit-learn/scikit-learn/issues/30909 | [
"RFC"
] | Improve `pos_label` switching for metrics
Supercedes #26758
Switching `pos_label` for metrics, involves some manipulation for `predict_proba` (switch column you pass) and `decision_function` (for binary, multiply by -1) as you must pass the values for the positive class.
In discussions in #26758 we thought of two ... | 30,909 |
https://github.com/scikit-learn/scikit-learn/issues/30909 | [
"RFC"
] | Improve `pos_label` switching for metrics
Supercedes #26758
Switching `pos_label` for metrics, involves some manipulation for `predict_proba` (switch column you pass) and `decision_function` (for binary, multiply by -1) as you must pass the values for the positive class.
In discussions in #26758 we thought of two ... | 30,909 |
https://github.com/scikit-learn/scikit-learn/issues/30907 | [
"Documentation"
] | DOC Update wikipedia article for scikit-learn
### Describe the issue linked to the documentation
The [wikipedia article on scikit-learn](https://en.wikipedia.org/wiki/Scikit-learn) covers its basic history, development, and features, but there are a few areas where additional details could enhance the content
Notice... | 30,907 |
https://github.com/scikit-learn/scikit-learn/issues/30907 | [
"Documentation"
] | DOC Update wikipedia article for scikit-learn
### Describe the issue linked to the documentation
The [wikipedia article on scikit-learn](https://en.wikipedia.org/wiki/Scikit-learn) covers its basic history, development, and features, but there are a few areas where additional details could enhance the content
Notice... | 30,907 |
https://github.com/scikit-learn/scikit-learn/issues/30907 | [
"Documentation"
] | DOC Update wikipedia article for scikit-learn
### Describe the issue linked to the documentation
The [wikipedia article on scikit-learn](https://en.wikipedia.org/wiki/Scikit-learn) covers its basic history, development, and features, but there are a few areas where additional details could enhance the content
Notice... | 30,907 |
https://github.com/scikit-learn/scikit-learn/issues/30907 | [
"Documentation"
] | DOC Update wikipedia article for scikit-learn
### Describe the issue linked to the documentation
The [wikipedia article on scikit-learn](https://en.wikipedia.org/wiki/Scikit-learn) covers its basic history, development, and features, but there are a few areas where additional details could enhance the content
Notice... | 30,907 |
https://github.com/scikit-learn/scikit-learn/issues/30907 | [
"Documentation"
] | DOC Update wikipedia article for scikit-learn
### Describe the issue linked to the documentation
The [wikipedia article on scikit-learn](https://en.wikipedia.org/wiki/Scikit-learn) covers its basic history, development, and features, but there are a few areas where additional details could enhance the content
Notice... | 30,907 |
https://github.com/scikit-learn/scikit-learn/issues/30907 | [
"Documentation"
] | DOC Update wikipedia article for scikit-learn
### Describe the issue linked to the documentation
The [wikipedia article on scikit-learn](https://en.wikipedia.org/wiki/Scikit-learn) covers its basic history, development, and features, but there are a few areas where additional details could enhance the content
Notice... | 30,907 |
https://github.com/scikit-learn/scikit-learn/issues/30907 | [
"Documentation"
] | DOC Update wikipedia article for scikit-learn
### Describe the issue linked to the documentation
The [wikipedia article on scikit-learn](https://en.wikipedia.org/wiki/Scikit-learn) covers its basic history, development, and features, but there are a few areas where additional details could enhance the content
Notice... | 30,907 |
https://github.com/scikit-learn/scikit-learn/issues/30905 | [
"Documentation"
] | Unclear information in Explained variance
### Describe the issue linked to the documentation
Hi, the text in Explained variance page is somewhat unclear, so I want to propose a clearer text. On line 1005, the detail says this:
> "The Explained Variance score is similar to the R^2 score, with the notable difference t... | 30,905 |
https://github.com/scikit-learn/scikit-learn/issues/30905 | [
"Documentation"
] | Unclear information in Explained variance
### Describe the issue linked to the documentation
Hi, the text in Explained variance page is somewhat unclear, so I want to propose a clearer text. On line 1005, the detail says this:
> "The Explained Variance score is similar to the R^2 score, with the notable difference t... | 30,905 |
https://github.com/scikit-learn/scikit-learn/issues/30905 | [
"Documentation"
] | Unclear information in Explained variance
### Describe the issue linked to the documentation
Hi, the text in Explained variance page is somewhat unclear, so I want to propose a clearer text. On line 1005, the detail says this:
> "The Explained Variance score is similar to the R^2 score, with the notable difference t... | 30,905 |
https://github.com/scikit-learn/scikit-learn/issues/30905 | [
"Documentation"
] | Unclear information in Explained variance
### Describe the issue linked to the documentation
Hi, the text in Explained variance page is somewhat unclear, so I want to propose a clearer text. On line 1005, the detail says this:
> "The Explained Variance score is similar to the R^2 score, with the notable difference t... | 30,905 |
https://github.com/scikit-learn/scikit-learn/issues/30905 | [
"Documentation"
] | Unclear information in Explained variance
### Describe the issue linked to the documentation
Hi, the text in Explained variance page is somewhat unclear, so I want to propose a clearer text. On line 1005, the detail says this:
> "The Explained Variance score is similar to the R^2 score, with the notable difference t... | 30,905 |
https://github.com/scikit-learn/scikit-learn/issues/30905 | [
"Documentation"
] | Unclear information in Explained variance
### Describe the issue linked to the documentation
Hi, the text in Explained variance page is somewhat unclear, so I want to propose a clearer text. On line 1005, the detail says this:
> "The Explained Variance score is similar to the R^2 score, with the notable difference t... | 30,905 |
https://github.com/scikit-learn/scikit-learn/issues/30896 | [
"Bug",
"Performance"
] | Kmeans Elkans deteriorates with different cores settings
### Describe the bug
Currently I'm trying to run Kmeans Elkan on a large-scale dataset. I have tried to run it with 2 configuration: 8-thread setting and 16-thread setting. While the former one seems to work normally, the running time for the later surge surpri... | 30,896 |
https://github.com/scikit-learn/scikit-learn/issues/30896 | [
"Bug",
"Performance"
] | Kmeans Elkans deteriorates with different cores settings
### Describe the bug
Currently I'm trying to run Kmeans Elkan on a large-scale dataset. I have tried to run it with 2 configuration: 8-thread setting and 16-thread setting. While the former one seems to work normally, the running time for the later surge surpri... | 30,896 |
https://github.com/scikit-learn/scikit-learn/issues/30896 | [
"Bug",
"Performance"
] | Kmeans Elkans deteriorates with different cores settings
### Describe the bug
Currently I'm trying to run Kmeans Elkan on a large-scale dataset. I have tried to run it with 2 configuration: 8-thread setting and 16-thread setting. While the former one seems to work normally, the running time for the later surge surpri... | 30,896 |
https://github.com/scikit-learn/scikit-learn/issues/30896 | [
"Bug",
"Performance"
] | Kmeans Elkans deteriorates with different cores settings
### Describe the bug
Currently I'm trying to run Kmeans Elkan on a large-scale dataset. I have tried to run it with 2 configuration: 8-thread setting and 16-thread setting. While the former one seems to work normally, the running time for the later surge surpri... | 30,896 |
https://github.com/scikit-learn/scikit-learn/issues/30896 | [
"Bug",
"Performance"
] | Kmeans Elkans deteriorates with different cores settings
### Describe the bug
Currently I'm trying to run Kmeans Elkan on a large-scale dataset. I have tried to run it with 2 configuration: 8-thread setting and 16-thread setting. While the former one seems to work normally, the running time for the later surge surpri... | 30,896 |
https://github.com/scikit-learn/scikit-learn/issues/30896 | [
"Bug",
"Performance"
] | Kmeans Elkans deteriorates with different cores settings
### Describe the bug
Currently I'm trying to run Kmeans Elkan on a large-scale dataset. I have tried to run it with 2 configuration: 8-thread setting and 16-thread setting. While the former one seems to work normally, the running time for the later surge surpri... | 30,896 |
https://github.com/scikit-learn/scikit-learn/issues/30896 | [
"Bug",
"Performance"
] | Kmeans Elkans deteriorates with different cores settings
### Describe the bug
Currently I'm trying to run Kmeans Elkan on a large-scale dataset. I have tried to run it with 2 configuration: 8-thread setting and 16-thread setting. While the former one seems to work normally, the running time for the later surge surpri... | 30,896 |
https://github.com/scikit-learn/scikit-learn/issues/30896 | [
"Bug",
"Performance"
] | Kmeans Elkans deteriorates with different cores settings
### Describe the bug
Currently I'm trying to run Kmeans Elkan on a large-scale dataset. I have tried to run it with 2 configuration: 8-thread setting and 16-thread setting. While the former one seems to work normally, the running time for the later surge surpri... | 30,896 |
https://github.com/scikit-learn/scikit-learn/issues/30896 | [
"Bug",
"Performance"
] | Kmeans Elkans deteriorates with different cores settings
### Describe the bug
Currently I'm trying to run Kmeans Elkan on a large-scale dataset. I have tried to run it with 2 configuration: 8-thread setting and 16-thread setting. While the former one seems to work normally, the running time for the later surge surpri... | 30,896 |
https://github.com/scikit-learn/scikit-learn/issues/30896 | [
"Bug",
"Performance"
] | Kmeans Elkans deteriorates with different cores settings
### Describe the bug
Currently I'm trying to run Kmeans Elkan on a large-scale dataset. I have tried to run it with 2 configuration: 8-thread setting and 16-thread setting. While the former one seems to work normally, the running time for the later surge surpri... | 30,896 |
https://github.com/scikit-learn/scikit-learn/issues/30893 | [
"Documentation"
] | The `alpha` parameter for lasso regression can only be a `float`
### Describe the issue linked to the documentation
https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.Lasso.html#sklearn.linear_model.Lasso
The line "If an array is passed, penalties are assumed to be specific to the targets. Hence ... | 30,893 |
https://github.com/scikit-learn/scikit-learn/issues/30889 | [
"API",
"RFC"
] | RFC Make `n_outputs_` consistent across regressors
The scikit-learn API defines `classes_` as part of the API for classifier.
A similar handy thing for regressor models, IMO, would be to know if it was fit on a single or multioutput target. Currently, some regressors expose the `n_outputs_` parameter, but other not. ... | 30,889 |
https://github.com/scikit-learn/scikit-learn/issues/30889 | [
"API",
"RFC"
] | RFC Make `n_outputs_` consistent across regressors
The scikit-learn API defines `classes_` as part of the API for classifier.
A similar handy thing for regressor models, IMO, would be to know if it was fit on a single or multioutput target. Currently, some regressors expose the `n_outputs_` parameter, but other not. ... | 30,889 |
https://github.com/scikit-learn/scikit-learn/issues/30889 | [
"API",
"RFC"
] | RFC Make `n_outputs_` consistent across regressors
The scikit-learn API defines `classes_` as part of the API for classifier.
A similar handy thing for regressor models, IMO, would be to know if it was fit on a single or multioutput target. Currently, some regressors expose the `n_outputs_` parameter, but other not. ... | 30,889 |
https://github.com/scikit-learn/scikit-learn/issues/30889 | [
"API",
"RFC"
] | RFC Make `n_outputs_` consistent across regressors
The scikit-learn API defines `classes_` as part of the API for classifier.
A similar handy thing for regressor models, IMO, would be to know if it was fit on a single or multioutput target. Currently, some regressors expose the `n_outputs_` parameter, but other not. ... | 30,889 |
https://github.com/scikit-learn/scikit-learn/issues/30889 | [
"API",
"RFC"
] | RFC Make `n_outputs_` consistent across regressors
The scikit-learn API defines `classes_` as part of the API for classifier.
A similar handy thing for regressor models, IMO, would be to know if it was fit on a single or multioutput target. Currently, some regressors expose the `n_outputs_` parameter, but other not. ... | 30,889 |
https://github.com/scikit-learn/scikit-learn/issues/30889 | [
"API",
"RFC"
] | RFC Make `n_outputs_` consistent across regressors
The scikit-learn API defines `classes_` as part of the API for classifier.
A similar handy thing for regressor models, IMO, would be to know if it was fit on a single or multioutput target. Currently, some regressors expose the `n_outputs_` parameter, but other not. ... | 30,889 |
https://github.com/scikit-learn/scikit-learn/issues/30889 | [
"API",
"RFC"
] | RFC Make `n_outputs_` consistent across regressors
The scikit-learn API defines `classes_` as part of the API for classifier.
A similar handy thing for regressor models, IMO, would be to know if it was fit on a single or multioutput target. Currently, some regressors expose the `n_outputs_` parameter, but other not. ... | 30,889 |
https://github.com/scikit-learn/scikit-learn/issues/30889 | [
"API",
"RFC"
] | RFC Make `n_outputs_` consistent across regressors
The scikit-learn API defines `classes_` as part of the API for classifier.
A similar handy thing for regressor models, IMO, would be to know if it was fit on a single or multioutput target. Currently, some regressors expose the `n_outputs_` parameter, but other not. ... | 30,889 |
https://github.com/scikit-learn/scikit-learn/issues/30888 | [
"RFC"
] | RFC Write an explicit rule about bumping our minimum dependencies
Roughly a year ago, [SPEC0](https://scientific-python.org/specs/spec-0000/) was rejected following a vote and we said we would write our own rule, but we did not 😅.
Until now 💪.
This was spurred by a [Discord discussion](https://discord.com/channel... | 30,888 |
https://github.com/scikit-learn/scikit-learn/issues/30888 | [
"RFC"
] | RFC Write an explicit rule about bumping our minimum dependencies
Roughly a year ago, [SPEC0](https://scientific-python.org/specs/spec-0000/) was rejected following a vote and we said we would write our own rule, but we did not 😅.
Until now 💪.
This was spurred by a [Discord discussion](https://discord.com/channel... | 30,888 |
https://github.com/scikit-learn/scikit-learn/issues/30888 | [
"RFC"
] | RFC Write an explicit rule about bumping our minimum dependencies
Roughly a year ago, [SPEC0](https://scientific-python.org/specs/spec-0000/) was rejected following a vote and we said we would write our own rule, but we did not 😅.
Until now 💪.
This was spurred by a [Discord discussion](https://discord.com/channel... | 30,888 |
https://github.com/scikit-learn/scikit-learn/issues/30888 | [
"RFC"
] | RFC Write an explicit rule about bumping our minimum dependencies
Roughly a year ago, [SPEC0](https://scientific-python.org/specs/spec-0000/) was rejected following a vote and we said we would write our own rule, but we did not 😅.
Until now 💪.
This was spurred by a [Discord discussion](https://discord.com/channel... | 30,888 |
https://github.com/scikit-learn/scikit-learn/issues/30888 | [
"RFC"
] | RFC Write an explicit rule about bumping our minimum dependencies
Roughly a year ago, [SPEC0](https://scientific-python.org/specs/spec-0000/) was rejected following a vote and we said we would write our own rule, but we did not 😅.
Until now 💪.
This was spurred by a [Discord discussion](https://discord.com/channel... | 30,888 |
https://github.com/scikit-learn/scikit-learn/issues/30888 | [
"RFC"
] | RFC Write an explicit rule about bumping our minimum dependencies
Roughly a year ago, [SPEC0](https://scientific-python.org/specs/spec-0000/) was rejected following a vote and we said we would write our own rule, but we did not 😅.
Until now 💪.
This was spurred by a [Discord discussion](https://discord.com/channel... | 30,888 |
https://github.com/scikit-learn/scikit-learn/issues/30888 | [
"RFC"
] | RFC Write an explicit rule about bumping our minimum dependencies
Roughly a year ago, [SPEC0](https://scientific-python.org/specs/spec-0000/) was rejected following a vote and we said we would write our own rule, but we did not 😅.
Until now 💪.
This was spurred by a [Discord discussion](https://discord.com/channel... | 30,888 |
https://github.com/scikit-learn/scikit-learn/issues/30888 | [
"RFC"
] | RFC Write an explicit rule about bumping our minimum dependencies
Roughly a year ago, [SPEC0](https://scientific-python.org/specs/spec-0000/) was rejected following a vote and we said we would write our own rule, but we did not 😅.
Until now 💪.
This was spurred by a [Discord discussion](https://discord.com/channel... | 30,888 |
https://github.com/scikit-learn/scikit-learn/issues/30888 | [
"RFC"
] | RFC Write an explicit rule about bumping our minimum dependencies
Roughly a year ago, [SPEC0](https://scientific-python.org/specs/spec-0000/) was rejected following a vote and we said we would write our own rule, but we did not 😅.
Until now 💪.
This was spurred by a [Discord discussion](https://discord.com/channel... | 30,888 |
https://github.com/scikit-learn/scikit-learn/issues/30888 | [
"RFC"
] | RFC Write an explicit rule about bumping our minimum dependencies
Roughly a year ago, [SPEC0](https://scientific-python.org/specs/spec-0000/) was rejected following a vote and we said we would write our own rule, but we did not 😅.
Until now 💪.
This was spurred by a [Discord discussion](https://discord.com/channel... | 30,888 |
https://github.com/scikit-learn/scikit-learn/issues/30888 | [
"RFC"
] | RFC Write an explicit rule about bumping our minimum dependencies
Roughly a year ago, [SPEC0](https://scientific-python.org/specs/spec-0000/) was rejected following a vote and we said we would write our own rule, but we did not 😅.
Until now 💪.
This was spurred by a [Discord discussion](https://discord.com/channel... | 30,888 |
https://github.com/scikit-learn/scikit-learn/issues/30888 | [
"RFC"
] | RFC Write an explicit rule about bumping our minimum dependencies
Roughly a year ago, [SPEC0](https://scientific-python.org/specs/spec-0000/) was rejected following a vote and we said we would write our own rule, but we did not 😅.
Until now 💪.
This was spurred by a [Discord discussion](https://discord.com/channel... | 30,888 |
https://github.com/scikit-learn/scikit-learn/issues/30888 | [
"RFC"
] | RFC Write an explicit rule about bumping our minimum dependencies
Roughly a year ago, [SPEC0](https://scientific-python.org/specs/spec-0000/) was rejected following a vote and we said we would write our own rule, but we did not 😅.
Until now 💪.
This was spurred by a [Discord discussion](https://discord.com/channel... | 30,888 |
https://github.com/scikit-learn/scikit-learn/issues/30888 | [
"RFC"
] | RFC Write an explicit rule about bumping our minimum dependencies
Roughly a year ago, [SPEC0](https://scientific-python.org/specs/spec-0000/) was rejected following a vote and we said we would write our own rule, but we did not 😅.
Until now 💪.
This was spurred by a [Discord discussion](https://discord.com/channel... | 30,888 |
https://github.com/scikit-learn/scikit-learn/issues/30888 | [
"RFC"
] | RFC Write an explicit rule about bumping our minimum dependencies
Roughly a year ago, [SPEC0](https://scientific-python.org/specs/spec-0000/) was rejected following a vote and we said we would write our own rule, but we did not 😅.
Until now 💪.
This was spurred by a [Discord discussion](https://discord.com/channel... | 30,888 |
https://github.com/scikit-learn/scikit-learn/issues/30888 | [
"RFC"
] | RFC Write an explicit rule about bumping our minimum dependencies
Roughly a year ago, [SPEC0](https://scientific-python.org/specs/spec-0000/) was rejected following a vote and we said we would write our own rule, but we did not 😅.
Until now 💪.
This was spurred by a [Discord discussion](https://discord.com/channel... | 30,888 |
https://github.com/scikit-learn/scikit-learn/issues/30888 | [
"RFC"
] | RFC Write an explicit rule about bumping our minimum dependencies
Roughly a year ago, [SPEC0](https://scientific-python.org/specs/spec-0000/) was rejected following a vote and we said we would write our own rule, but we did not 😅.
Until now 💪.
This was spurred by a [Discord discussion](https://discord.com/channel... | 30,888 |
https://github.com/scikit-learn/scikit-learn/issues/30888 | [
"RFC"
] | RFC Write an explicit rule about bumping our minimum dependencies
Roughly a year ago, [SPEC0](https://scientific-python.org/specs/spec-0000/) was rejected following a vote and we said we would write our own rule, but we did not 😅.
Until now 💪.
This was spurred by a [Discord discussion](https://discord.com/channel... | 30,888 |
https://github.com/scikit-learn/scikit-learn/issues/30868 | [
"Bug"
] | Calibration cannot handle different dtype for prediction and sample weight.
### Describe the bug
This is from the comment: https://github.com/scikit-learn/scikit-learn/issues/28245#issuecomment-2106845979 . I did not find a corresponding issue. Please close if this is duplicated.
Aligning the types here https://git... | 30,868 |
https://github.com/scikit-learn/scikit-learn/issues/30854 | [
"Documentation",
"Sprint",
"good first issue",
"Meta-issue"
] | Add `assert_docstring_consistency` checks
The [`assert_docstring_consistency`](https://github.com/scikit-learn/scikit-learn/blob/4ec5f69061a9c37e0f6b9920e296e06c6b4669ac/sklearn/utils/_testing.py#L734) function allows you to check the consistency between docstring parameters/attributes/returns of objects.
In scikit-l... | 30,854 |
https://github.com/scikit-learn/scikit-learn/issues/30854 | [
"Documentation",
"Sprint",
"good first issue",
"Meta-issue"
] | Add `assert_docstring_consistency` checks
The [`assert_docstring_consistency`](https://github.com/scikit-learn/scikit-learn/blob/4ec5f69061a9c37e0f6b9920e296e06c6b4669ac/sklearn/utils/_testing.py#L734) function allows you to check the consistency between docstring parameters/attributes/returns of objects.
In scikit-l... | 30,854 |
https://github.com/scikit-learn/scikit-learn/issues/30854 | [
"Documentation",
"Sprint",
"good first issue",
"Meta-issue"
] | Add `assert_docstring_consistency` checks
The [`assert_docstring_consistency`](https://github.com/scikit-learn/scikit-learn/blob/4ec5f69061a9c37e0f6b9920e296e06c6b4669ac/sklearn/utils/_testing.py#L734) function allows you to check the consistency between docstring parameters/attributes/returns of objects.
In scikit-l... | 30,854 |
https://github.com/scikit-learn/scikit-learn/issues/30854 | [
"Documentation",
"Sprint",
"good first issue",
"Meta-issue"
] | Add `assert_docstring_consistency` checks
The [`assert_docstring_consistency`](https://github.com/scikit-learn/scikit-learn/blob/4ec5f69061a9c37e0f6b9920e296e06c6b4669ac/sklearn/utils/_testing.py#L734) function allows you to check the consistency between docstring parameters/attributes/returns of objects.
In scikit-l... | 30,854 |
https://github.com/scikit-learn/scikit-learn/issues/30854 | [
"Documentation",
"Sprint",
"good first issue",
"Meta-issue"
] | Add `assert_docstring_consistency` checks
The [`assert_docstring_consistency`](https://github.com/scikit-learn/scikit-learn/blob/4ec5f69061a9c37e0f6b9920e296e06c6b4669ac/sklearn/utils/_testing.py#L734) function allows you to check the consistency between docstring parameters/attributes/returns of objects.
In scikit-l... | 30,854 |
https://github.com/scikit-learn/scikit-learn/issues/30854 | [
"Documentation",
"Sprint",
"good first issue",
"Meta-issue"
] | Add `assert_docstring_consistency` checks
The [`assert_docstring_consistency`](https://github.com/scikit-learn/scikit-learn/blob/4ec5f69061a9c37e0f6b9920e296e06c6b4669ac/sklearn/utils/_testing.py#L734) function allows you to check the consistency between docstring parameters/attributes/returns of objects.
In scikit-l... | 30,854 |
https://github.com/scikit-learn/scikit-learn/issues/30854 | [
"Documentation",
"Sprint",
"good first issue",
"Meta-issue"
] | Add `assert_docstring_consistency` checks
The [`assert_docstring_consistency`](https://github.com/scikit-learn/scikit-learn/blob/4ec5f69061a9c37e0f6b9920e296e06c6b4669ac/sklearn/utils/_testing.py#L734) function allows you to check the consistency between docstring parameters/attributes/returns of objects.
In scikit-l... | 30,854 |
https://github.com/scikit-learn/scikit-learn/issues/30854 | [
"Documentation",
"Sprint",
"good first issue",
"Meta-issue"
] | Add `assert_docstring_consistency` checks
The [`assert_docstring_consistency`](https://github.com/scikit-learn/scikit-learn/blob/4ec5f69061a9c37e0f6b9920e296e06c6b4669ac/sklearn/utils/_testing.py#L734) function allows you to check the consistency between docstring parameters/attributes/returns of objects.
In scikit-l... | 30,854 |
https://github.com/scikit-learn/scikit-learn/issues/30854 | [
"Documentation",
"Sprint",
"good first issue",
"Meta-issue"
] | Add `assert_docstring_consistency` checks
The [`assert_docstring_consistency`](https://github.com/scikit-learn/scikit-learn/blob/4ec5f69061a9c37e0f6b9920e296e06c6b4669ac/sklearn/utils/_testing.py#L734) function allows you to check the consistency between docstring parameters/attributes/returns of objects.
In scikit-l... | 30,854 |
https://github.com/scikit-learn/scikit-learn/issues/30852 | [
"New Feature"
] | Add a progress bar to the randomized and grid search
### Describe the workflow you want to enable
When working on a large hyper-parameter set, setting the verbosity of `{Randomized, Grid}SearchCV` doesn't make the CV more informative. The display should help users estimate their waiting time and take a look at their ... | 30,852 |
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