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/25628 | [
"Question"
] | TypeError: '<=' not supported between instances of 'str' and 'int' when using fit_predict
I am trying to utilize silhouette analysis on KMeans clustering in order to determine how to choose the optimal number of clusters in a given dataset.
I tried the example code provided on [scikit-learn](https://scikit-learn.org/... | 25,628 |
https://github.com/scikit-learn/scikit-learn/issues/25628 | [
"Question"
] | TypeError: '<=' not supported between instances of 'str' and 'int' when using fit_predict
I am trying to utilize silhouette analysis on KMeans clustering in order to determine how to choose the optimal number of clusters in a given dataset.
I tried the example code provided on [scikit-learn](https://scikit-learn.org/... | 25,628 |
https://github.com/scikit-learn/scikit-learn/issues/25628 | [
"Question"
] | TypeError: '<=' not supported between instances of 'str' and 'int' when using fit_predict
I am trying to utilize silhouette analysis on KMeans clustering in order to determine how to choose the optimal number of clusters in a given dataset.
I tried the example code provided on [scikit-learn](https://scikit-learn.org/... | 25,628 |
https://github.com/scikit-learn/scikit-learn/issues/25628 | [
"Question"
] | TypeError: '<=' not supported between instances of 'str' and 'int' when using fit_predict
I am trying to utilize silhouette analysis on KMeans clustering in order to determine how to choose the optimal number of clusters in a given dataset.
I tried the example code provided on [scikit-learn](https://scikit-learn.org/... | 25,628 |
https://github.com/scikit-learn/scikit-learn/issues/25627 | [
"Bug",
"module:ensemble"
] | OrdinalEncoder does not work with HistGradientBoostingClassifier when there are NULLs
### Describe the bug
If you use the ordinal encoder when there is NULLS you need to put them to a Negative Value otherwise you get. The following error
_The used value for unknown_value is one of the values already used for en... | 25,627 |
https://github.com/scikit-learn/scikit-learn/issues/25627 | [
"Bug",
"module:ensemble"
] | OrdinalEncoder does not work with HistGradientBoostingClassifier when there are NULLs
### Describe the bug
If you use the ordinal encoder when there is NULLS you need to put them to a Negative Value otherwise you get. The following error
_The used value for unknown_value is one of the values already used for en... | 25,627 |
https://github.com/scikit-learn/scikit-learn/issues/25627 | [
"Bug",
"module:ensemble"
] | OrdinalEncoder does not work with HistGradientBoostingClassifier when there are NULLs
### Describe the bug
If you use the ordinal encoder when there is NULLS you need to put them to a Negative Value otherwise you get. The following error
_The used value for unknown_value is one of the values already used for en... | 25,627 |
https://github.com/scikit-learn/scikit-learn/issues/25627 | [
"Bug",
"module:ensemble"
] | OrdinalEncoder does not work with HistGradientBoostingClassifier when there are NULLs
### Describe the bug
If you use the ordinal encoder when there is NULLS you need to put them to a Negative Value otherwise you get. The following error
_The used value for unknown_value is one of the values already used for en... | 25,627 |
https://github.com/scikit-learn/scikit-learn/issues/25627 | [
"Bug",
"module:ensemble"
] | OrdinalEncoder does not work with HistGradientBoostingClassifier when there are NULLs
### Describe the bug
If you use the ordinal encoder when there is NULLS you need to put them to a Negative Value otherwise you get. The following error
_The used value for unknown_value is one of the values already used for en... | 25,627 |
https://github.com/scikit-learn/scikit-learn/issues/25626 | [
"Needs Triage"
] | ValueError: dimension mismatch for Logistic Regression.
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/25625
<div type='discussions-op-text'>
<sup>Originally posted by **samarthpatel1289** February 16, 2023</sup>
I was looking for solution to this. Followed the sklearn documentaion no... | 25,626 |
https://github.com/scikit-learn/scikit-learn/issues/25623 | [
"Bug",
"module:neighbors"
] | KernelDensity incorrect handling of bandwidth
### Describe the bug
I was using kernel density estimator
https://scikit-learn.org/stable/modules/generated/sklearn.neighbors.KernelDensity.html
using 'silverman' or 'scott' as the bandwidth argument. Then I found that the bandwidth automatically adjusted by the algor... | 25,623 |
https://github.com/scikit-learn/scikit-learn/issues/25623 | [
"Bug",
"module:neighbors"
] | KernelDensity incorrect handling of bandwidth
### Describe the bug
I was using kernel density estimator
https://scikit-learn.org/stable/modules/generated/sklearn.neighbors.KernelDensity.html
using 'silverman' or 'scott' as the bandwidth argument. Then I found that the bandwidth automatically adjusted by the algor... | 25,623 |
https://github.com/scikit-learn/scikit-learn/issues/25623 | [
"Bug",
"module:neighbors"
] | KernelDensity incorrect handling of bandwidth
### Describe the bug
I was using kernel density estimator
https://scikit-learn.org/stable/modules/generated/sklearn.neighbors.KernelDensity.html
using 'silverman' or 'scott' as the bandwidth argument. Then I found that the bandwidth automatically adjusted by the algor... | 25,623 |
https://github.com/scikit-learn/scikit-learn/issues/25623 | [
"Bug",
"module:neighbors"
] | KernelDensity incorrect handling of bandwidth
### Describe the bug
I was using kernel density estimator
https://scikit-learn.org/stable/modules/generated/sklearn.neighbors.KernelDensity.html
using 'silverman' or 'scott' as the bandwidth argument. Then I found that the bandwidth automatically adjusted by the algor... | 25,623 |
https://github.com/scikit-learn/scikit-learn/issues/25623 | [
"Bug",
"module:neighbors"
] | KernelDensity incorrect handling of bandwidth
### Describe the bug
I was using kernel density estimator
https://scikit-learn.org/stable/modules/generated/sklearn.neighbors.KernelDensity.html
using 'silverman' or 'scott' as the bandwidth argument. Then I found that the bandwidth automatically adjusted by the algor... | 25,623 |
https://github.com/scikit-learn/scikit-learn/issues/25623 | [
"Bug",
"module:neighbors"
] | KernelDensity incorrect handling of bandwidth
### Describe the bug
I was using kernel density estimator
https://scikit-learn.org/stable/modules/generated/sklearn.neighbors.KernelDensity.html
using 'silverman' or 'scott' as the bandwidth argument. Then I found that the bandwidth automatically adjusted by the algor... | 25,623 |
https://github.com/scikit-learn/scikit-learn/issues/25616 | [
"Bug",
"Needs Triage"
] | Standard Deviation with GPR always between 0 and 1
### Describe the bug
I have been trying to fit a gpr interpolation to a set of data, but I keep finding that the standard deviation is always between 0 and 1. I have tried a 1-dimensional example which uses a sin graph and that produces std with a much greater rang... | 25,616 |
https://github.com/scikit-learn/scikit-learn/issues/25616 | [
"Bug",
"Needs Triage"
] | Standard Deviation with GPR always between 0 and 1
### Describe the bug
I have been trying to fit a gpr interpolation to a set of data, but I keep finding that the standard deviation is always between 0 and 1. I have tried a 1-dimensional example which uses a sin graph and that produces std with a much greater rang... | 25,616 |
https://github.com/scikit-learn/scikit-learn/issues/25612 | [
"New Feature",
"module:tree",
"Needs Investigation"
] | Simplify decision tree removing redundant decisions
### Describe the workflow you want to enable
Description: Add a new method simplify() to the decision tree Class that returns a simplified version of the decision tree by pruning redundant leaves that do not add new decision paths. This simplification method will cr... | 25,612 |
https://github.com/scikit-learn/scikit-learn/issues/25612 | [
"New Feature",
"module:tree",
"Needs Investigation"
] | Simplify decision tree removing redundant decisions
### Describe the workflow you want to enable
Description: Add a new method simplify() to the decision tree Class that returns a simplified version of the decision tree by pruning redundant leaves that do not add new decision paths. This simplification method will cr... | 25,612 |
https://github.com/scikit-learn/scikit-learn/issues/25611 | [
"Documentation"
] | Improve the visibility of the projects governance
### Describe the issue linked to the documentation
When I navigate to https://scikit-learn.org/stable/governance.html#governance, I first got to scikit-learn.org -> More -> About Us, and then there is a link to the governance. This should be improved!
### Suggest a p... | 25,611 |
https://github.com/scikit-learn/scikit-learn/issues/25609 | [
"cython"
] | [MAINT, Cython] Implicit `noexcept` is deprecated in Cython 3.0
Hi,
I was trying some stuff out on Cython 3.0, and I saw a bunch of errors of the form:
```
...
warning: sklearn/metrics/_pairwise_distances_reduction/_radius_neighbors.pyx:954:49: Implicit noexcept declaration is deprecated. Function declaratio... | 25,609 |
https://github.com/scikit-learn/scikit-learn/issues/25609 | [
"cython"
] | [MAINT, Cython] Implicit `noexcept` is deprecated in Cython 3.0
Hi,
I was trying some stuff out on Cython 3.0, and I saw a bunch of errors of the form:
```
...
warning: sklearn/metrics/_pairwise_distances_reduction/_radius_neighbors.pyx:954:49: Implicit noexcept declaration is deprecated. Function declaratio... | 25,609 |
https://github.com/scikit-learn/scikit-learn/issues/25609 | [
"cython"
] | [MAINT, Cython] Implicit `noexcept` is deprecated in Cython 3.0
Hi,
I was trying some stuff out on Cython 3.0, and I saw a bunch of errors of the form:
```
...
warning: sklearn/metrics/_pairwise_distances_reduction/_radius_neighbors.pyx:954:49: Implicit noexcept declaration is deprecated. Function declaratio... | 25,609 |
https://github.com/scikit-learn/scikit-learn/issues/25607 | [
"Bug",
"Needs Triage"
] | Ordinal encoder not encoding missing values as np.nan
### Describe the bug
The documentation for OrdinalEncoder states that the default encoded_missing_value value is np.nan but when I run the encoder, it replace missing values with -9223372036854775808. The same behaviour is seen even if I manually specify the argum... | 25,607 |
https://github.com/scikit-learn/scikit-learn/issues/25604 | [
"Bug",
"Needs Info"
] | MLPR with solver='lbfgs', nonzero alpha doesn't make the same result from multiple run.
### Describe the bug
I have tested the simple regression modeling with MLPRegressor(solver='lbfgs', alpha=0.01, tol=0.0001, random_state=42) with sample data with three input parameters and three targets.
I tested multiple run ... | 25,604 |
https://github.com/scikit-learn/scikit-learn/issues/25604 | [
"Bug",
"Needs Info"
] | MLPR with solver='lbfgs', nonzero alpha doesn't make the same result from multiple run.
### Describe the bug
I have tested the simple regression modeling with MLPRegressor(solver='lbfgs', alpha=0.01, tol=0.0001, random_state=42) with sample data with three input parameters and three targets.
I tested multiple run ... | 25,604 |
https://github.com/scikit-learn/scikit-learn/issues/25604 | [
"Bug",
"Needs Info"
] | MLPR with solver='lbfgs', nonzero alpha doesn't make the same result from multiple run.
### Describe the bug
I have tested the simple regression modeling with MLPRegressor(solver='lbfgs', alpha=0.01, tol=0.0001, random_state=42) with sample data with three input parameters and three targets.
I tested multiple run ... | 25,604 |
https://github.com/scikit-learn/scikit-learn/issues/25603 | [
"Documentation"
] | Building from source fails on Linux systems with pre-installed Intel OpenMP
### Describe the issue linked to the documentation
On systems that have Intel compilers with OpenMP support (like `icx` and `icpc`), building scikit-learn from source fails with the following error.
`ImportError: libomp.so: cannot open s... | 25,603 |
https://github.com/scikit-learn/scikit-learn/issues/25603 | [
"Documentation"
] | Building from source fails on Linux systems with pre-installed Intel OpenMP
### Describe the issue linked to the documentation
On systems that have Intel compilers with OpenMP support (like `icx` and `icpc`), building scikit-learn from source fails with the following error.
`ImportError: libomp.so: cannot open s... | 25,603 |
https://github.com/scikit-learn/scikit-learn/issues/25603 | [
"Documentation"
] | Building from source fails on Linux systems with pre-installed Intel OpenMP
### Describe the issue linked to the documentation
On systems that have Intel compilers with OpenMP support (like `icx` and `icpc`), building scikit-learn from source fails with the following error.
`ImportError: libomp.so: cannot open s... | 25,603 |
https://github.com/scikit-learn/scikit-learn/issues/25603 | [
"Documentation"
] | Building from source fails on Linux systems with pre-installed Intel OpenMP
### Describe the issue linked to the documentation
On systems that have Intel compilers with OpenMP support (like `icx` and `icpc`), building scikit-learn from source fails with the following error.
`ImportError: libomp.so: cannot open s... | 25,603 |
https://github.com/scikit-learn/scikit-learn/issues/25597 | [
"Documentation",
"module:ensemble"
] | Unsupported multioutput stacking regressor
### Describe the bug
The method `fit_transform` of `sklearn.ensemble.StackingRegressor`, according to the documentation, should support as second argument (`y`) an array-like of shape (n_samples,) or (n_samples, n_outputs). However, if an array of shape (n_sample, n_output... | 25,597 |
https://github.com/scikit-learn/scikit-learn/issues/25597 | [
"Documentation",
"module:ensemble"
] | Unsupported multioutput stacking regressor
### Describe the bug
The method `fit_transform` of `sklearn.ensemble.StackingRegressor`, according to the documentation, should support as second argument (`y`) an array-like of shape (n_samples,) or (n_samples, n_outputs). However, if an array of shape (n_sample, n_output... | 25,597 |
https://github.com/scikit-learn/scikit-learn/issues/25597 | [
"Documentation",
"module:ensemble"
] | Unsupported multioutput stacking regressor
### Describe the bug
The method `fit_transform` of `sklearn.ensemble.StackingRegressor`, according to the documentation, should support as second argument (`y`) an array-like of shape (n_samples,) or (n_samples, n_outputs). However, if an array of shape (n_sample, n_output... | 25,597 |
https://github.com/scikit-learn/scikit-learn/issues/25596 | [
"New Feature",
"Needs Triage"
] | Train-test-split for multilabel datasets
### Describe the workflow you want to enable
Train-test splits for 2-dimensional targets (i.e. multi-label datasets).
I saw couple of issues related to multi-label classification, but as far as I can tell, train-test-split has not been addressed there.
Related forum questi... | 25,596 |
https://github.com/scikit-learn/scikit-learn/issues/25596 | [
"New Feature",
"Needs Triage"
] | Train-test-split for multilabel datasets
### Describe the workflow you want to enable
Train-test splits for 2-dimensional targets (i.e. multi-label datasets).
I saw couple of issues related to multi-label classification, but as far as I can tell, train-test-split has not been addressed there.
Related forum questi... | 25,596 |
https://github.com/scikit-learn/scikit-learn/issues/25595 | [
"New Feature",
"Needs Triage"
] | About using feature_Selection many times
### Describe the workflow you want to enable
I will state my question first.
When using a pipeline that combines a variable selection method with multiple estimators.
If I evaluate them with cross_validation, is there a good way not to evaluate fit for variable selection e... | 25,595 |
https://github.com/scikit-learn/scikit-learn/issues/25594 | [
"Bug",
"Needs Decision",
"module:preprocessing"
] | KBinsDiscretizer creates wrong bins.
### Describe the bug
`KBinsDiscretizer` gives wrong bins and wrong transformed data, when the inputs contains only 2 distinct values, and `n_bins=3`. It only produces 1 bin, which is not expected. The warning shows some bins are too small so they are merged.
Note that when s... | 25,594 |
https://github.com/scikit-learn/scikit-learn/issues/25594 | [
"Bug",
"Needs Decision",
"module:preprocessing"
] | KBinsDiscretizer creates wrong bins.
### Describe the bug
`KBinsDiscretizer` gives wrong bins and wrong transformed data, when the inputs contains only 2 distinct values, and `n_bins=3`. It only produces 1 bin, which is not expected. The warning shows some bins are too small so they are merged.
Note that when s... | 25,594 |
https://github.com/scikit-learn/scikit-learn/issues/25594 | [
"Bug",
"Needs Decision",
"module:preprocessing"
] | KBinsDiscretizer creates wrong bins.
### Describe the bug
`KBinsDiscretizer` gives wrong bins and wrong transformed data, when the inputs contains only 2 distinct values, and `n_bins=3`. It only produces 1 bin, which is not expected. The warning shows some bins are too small so they are merged.
Note that when s... | 25,594 |
https://github.com/scikit-learn/scikit-learn/issues/25594 | [
"Bug",
"Needs Decision",
"module:preprocessing"
] | KBinsDiscretizer creates wrong bins.
### Describe the bug
`KBinsDiscretizer` gives wrong bins and wrong transformed data, when the inputs contains only 2 distinct values, and `n_bins=3`. It only produces 1 bin, which is not expected. The warning shows some bins are too small so they are merged.
Note that when s... | 25,594 |
https://github.com/scikit-learn/scikit-learn/issues/25594 | [
"Bug",
"Needs Decision",
"module:preprocessing"
] | KBinsDiscretizer creates wrong bins.
### Describe the bug
`KBinsDiscretizer` gives wrong bins and wrong transformed data, when the inputs contains only 2 distinct values, and `n_bins=3`. It only produces 1 bin, which is not expected. The warning shows some bins are too small so they are merged.
Note that when s... | 25,594 |
https://github.com/scikit-learn/scikit-learn/issues/25594 | [
"Bug",
"Needs Decision",
"module:preprocessing"
] | KBinsDiscretizer creates wrong bins.
### Describe the bug
`KBinsDiscretizer` gives wrong bins and wrong transformed data, when the inputs contains only 2 distinct values, and `n_bins=3`. It only produces 1 bin, which is not expected. The warning shows some bins are too small so they are merged.
Note that when s... | 25,594 |
https://github.com/scikit-learn/scikit-learn/issues/25594 | [
"Bug",
"Needs Decision",
"module:preprocessing"
] | KBinsDiscretizer creates wrong bins.
### Describe the bug
`KBinsDiscretizer` gives wrong bins and wrong transformed data, when the inputs contains only 2 distinct values, and `n_bins=3`. It only produces 1 bin, which is not expected. The warning shows some bins are too small so they are merged.
Note that when s... | 25,594 |
https://github.com/scikit-learn/scikit-learn/issues/25594 | [
"Bug",
"Needs Decision",
"module:preprocessing"
] | KBinsDiscretizer creates wrong bins.
### Describe the bug
`KBinsDiscretizer` gives wrong bins and wrong transformed data, when the inputs contains only 2 distinct values, and `n_bins=3`. It only produces 1 bin, which is not expected. The warning shows some bins are too small so they are merged.
Note that when s... | 25,594 |
https://github.com/scikit-learn/scikit-learn/issues/25594 | [
"Bug",
"Needs Decision",
"module:preprocessing"
] | KBinsDiscretizer creates wrong bins.
### Describe the bug
`KBinsDiscretizer` gives wrong bins and wrong transformed data, when the inputs contains only 2 distinct values, and `n_bins=3`. It only produces 1 bin, which is not expected. The warning shows some bins are too small so they are merged.
Note that when s... | 25,594 |
https://github.com/scikit-learn/scikit-learn/issues/25594 | [
"Bug",
"Needs Decision",
"module:preprocessing"
] | KBinsDiscretizer creates wrong bins.
### Describe the bug
`KBinsDiscretizer` gives wrong bins and wrong transformed data, when the inputs contains only 2 distinct values, and `n_bins=3`. It only produces 1 bin, which is not expected. The warning shows some bins are too small so they are merged.
Note that when s... | 25,594 |
https://github.com/scikit-learn/scikit-learn/issues/25594 | [
"Bug",
"Needs Decision",
"module:preprocessing"
] | KBinsDiscretizer creates wrong bins.
### Describe the bug
`KBinsDiscretizer` gives wrong bins and wrong transformed data, when the inputs contains only 2 distinct values, and `n_bins=3`. It only produces 1 bin, which is not expected. The warning shows some bins are too small so they are merged.
Note that when s... | 25,594 |
https://github.com/scikit-learn/scikit-learn/issues/25592 | [
"New Feature",
"Needs Decision - Include Feature"
] | set_config(transform_output="pandas") does not act on inverse_transform
### Describe the bug
The new [`set_config(transform_output='pandas')` functionality](https://blog.scikit-learn.org/technical/pandas-dataframe-output-for-sklearn-transformer/) is very useful, but unfortunately it is only taking an effect on the `t... | 25,592 |
https://github.com/scikit-learn/scikit-learn/issues/25590 | [
"Bug",
"Needs Investigation"
] | Importing BaseEstimator leads to unnecessary memory usage
### Describe the bug
Importing `BaseEstimator` from `sklearn.base` causes a cascade of imports that leads to unnecessary memory usage (500MiB of stuff at peak, see screenshot below).
![Screenshot from 2023-02-10 19-23-53](https://user-images.githubuserconte... | 25,590 |
https://github.com/scikit-learn/scikit-learn/issues/25590 | [
"Bug",
"Needs Investigation"
] | Importing BaseEstimator leads to unnecessary memory usage
### Describe the bug
Importing `BaseEstimator` from `sklearn.base` causes a cascade of imports that leads to unnecessary memory usage (500MiB of stuff at peak, see screenshot below).
![Screenshot from 2023-02-10 19-23-53](https://user-images.githubuserconte... | 25,590 |
https://github.com/scikit-learn/scikit-learn/issues/25590 | [
"Bug",
"Needs Investigation"
] | Importing BaseEstimator leads to unnecessary memory usage
### Describe the bug
Importing `BaseEstimator` from `sklearn.base` causes a cascade of imports that leads to unnecessary memory usage (500MiB of stuff at peak, see screenshot below).
![Screenshot from 2023-02-10 19-23-53](https://user-images.githubuserconte... | 25,590 |
https://github.com/scikit-learn/scikit-learn/issues/25590 | [
"Bug",
"Needs Investigation"
] | Importing BaseEstimator leads to unnecessary memory usage
### Describe the bug
Importing `BaseEstimator` from `sklearn.base` causes a cascade of imports that leads to unnecessary memory usage (500MiB of stuff at peak, see screenshot below).
![Screenshot from 2023-02-10 19-23-53](https://user-images.githubuserconte... | 25,590 |
https://github.com/scikit-learn/scikit-learn/issues/25590 | [
"Bug",
"Needs Investigation"
] | Importing BaseEstimator leads to unnecessary memory usage
### Describe the bug
Importing `BaseEstimator` from `sklearn.base` causes a cascade of imports that leads to unnecessary memory usage (500MiB of stuff at peak, see screenshot below).
![Screenshot from 2023-02-10 19-23-53](https://user-images.githubuserconte... | 25,590 |
https://github.com/scikit-learn/scikit-learn/issues/25588 | [
"Bug",
"module:ensemble"
] | Broken estimator_ attribute on some ensemble models
### Describe the bug
Several ensemble models raise an error when trying to access the existing `estimator_` attribute.
The problem is that this `property` tries to access `self._estimator`, which is set by `sklearn.ensemble.BaseEnsemble._validate_estimator`, bu... | 25,588 |
https://github.com/scikit-learn/scikit-learn/issues/25588 | [
"Bug",
"module:ensemble"
] | Broken estimator_ attribute on some ensemble models
### Describe the bug
Several ensemble models raise an error when trying to access the existing `estimator_` attribute.
The problem is that this `property` tries to access `self._estimator`, which is set by `sklearn.ensemble.BaseEnsemble._validate_estimator`, bu... | 25,588 |
https://github.com/scikit-learn/scikit-learn/issues/25588 | [
"Bug",
"module:ensemble"
] | Broken estimator_ attribute on some ensemble models
### Describe the bug
Several ensemble models raise an error when trying to access the existing `estimator_` attribute.
The problem is that this `property` tries to access `self._estimator`, which is set by `sklearn.ensemble.BaseEnsemble._validate_estimator`, bu... | 25,588 |
https://github.com/scikit-learn/scikit-learn/issues/25588 | [
"Bug",
"module:ensemble"
] | Broken estimator_ attribute on some ensemble models
### Describe the bug
Several ensemble models raise an error when trying to access the existing `estimator_` attribute.
The problem is that this `property` tries to access `self._estimator`, which is set by `sklearn.ensemble.BaseEnsemble._validate_estimator`, bu... | 25,588 |
https://github.com/scikit-learn/scikit-learn/issues/25588 | [
"Bug",
"module:ensemble"
] | Broken estimator_ attribute on some ensemble models
### Describe the bug
Several ensemble models raise an error when trying to access the existing `estimator_` attribute.
The problem is that this `property` tries to access `self._estimator`, which is set by `sklearn.ensemble.BaseEnsemble._validate_estimator`, bu... | 25,588 |
https://github.com/scikit-learn/scikit-learn/issues/25584 | [
"Bug",
"cython"
] | ValueError: buffer source array is read-only when derializing a Tree from a readonly buffer.
As observed on our Circle CI and reproduced locally:
```python-traceback
/home/circleci/project/examples/release_highlights/plot_release_highlights_0_24_0.py failed leaving traceback:
Traceback (most recent call last):
... | 25,584 |
https://github.com/scikit-learn/scikit-learn/issues/25584 | [
"Bug",
"cython"
] | ValueError: buffer source array is read-only when derializing a Tree from a readonly buffer.
As observed on our Circle CI and reproduced locally:
```python-traceback
/home/circleci/project/examples/release_highlights/plot_release_highlights_0_24_0.py failed leaving traceback:
Traceback (most recent call last):
... | 25,584 |
https://github.com/scikit-learn/scikit-learn/issues/25584 | [
"Bug",
"cython"
] | ValueError: buffer source array is read-only when derializing a Tree from a readonly buffer.
As observed on our Circle CI and reproduced locally:
```python-traceback
/home/circleci/project/examples/release_highlights/plot_release_highlights_0_24_0.py failed leaving traceback:
Traceback (most recent call last):
... | 25,584 |
https://github.com/scikit-learn/scikit-learn/issues/25584 | [
"Bug",
"cython"
] | ValueError: buffer source array is read-only when derializing a Tree from a readonly buffer.
As observed on our Circle CI and reproduced locally:
```python-traceback
/home/circleci/project/examples/release_highlights/plot_release_highlights_0_24_0.py failed leaving traceback:
Traceback (most recent call last):
... | 25,584 |
https://github.com/scikit-learn/scikit-learn/issues/25583 | [
"RFC"
] | RFC enable github's pull request merge queue?
https://github.blog/changelog/2023-02-08-pull-request-merge-queue-public-beta/
It seems like a nice usability improvement.
COMMENT:
Just curious, I quickly read the article and I am not to sure this would be a game changer, but maybe I missed something ...
> Before ... | 25,583 |
https://github.com/scikit-learn/scikit-learn/issues/25583 | [
"RFC"
] | RFC enable github's pull request merge queue?
https://github.blog/changelog/2023-02-08-pull-request-merge-queue-public-beta/
It seems like a nice usability improvement.
COMMENT:
I think it reduces the likelihood of wasting CI when using conditional delayed merges. | 25,583 |
https://github.com/scikit-learn/scikit-learn/issues/25583 | [
"RFC"
] | RFC enable github's pull request merge queue?
https://github.blog/changelog/2023-02-08-pull-request-merge-queue-public-beta/
It seems like a nice usability improvement.
COMMENT:
As I understand it the problem that a merge queue solves is that PRs are "constantly" being merged into `main` and you have to rebase on ... | 25,583 |
https://github.com/scikit-learn/scikit-learn/issues/25583 | [
"RFC"
] | RFC enable github's pull request merge queue?
https://github.blog/changelog/2023-02-08-pull-request-merge-queue-public-beta/
It seems like a nice usability improvement.
COMMENT:
From memory, the issue that merge queue solves for happens around ~2 times a year in the past 3 years. For example, when a new test was a... | 25,583 |
https://github.com/scikit-learn/scikit-learn/issues/25583 | [
"RFC"
] | RFC enable github's pull request merge queue?
https://github.blog/changelog/2023-02-08-pull-request-merge-queue-public-beta/
It seems like a nice usability improvement.
COMMENT:
I enabled it for `main`. Let's see how it goes. | 25,583 |
https://github.com/scikit-learn/scikit-learn/issues/25583 | [
"RFC"
] | RFC enable github's pull request merge queue?
https://github.blog/changelog/2023-02-08-pull-request-merge-queue-public-beta/
It seems like a nice usability improvement.
COMMENT:
I had a problem when trying to use it today in #25585. Not sure what's going one because everything was green on this PR but apparently t... | 25,583 |
https://github.com/scikit-learn/scikit-learn/issues/25583 | [
"RFC"
] | RFC enable github's pull request merge queue?
https://github.blog/changelog/2023-02-08-pull-request-merge-queue-public-beta/
It seems like a nice usability improvement.
COMMENT:
I saw the same issue with the merge queue in https://github.com/scikit-learn/scikit-learn/pull/25613. | 25,583 |
https://github.com/scikit-learn/scikit-learn/issues/25583 | [
"RFC"
] | RFC enable github's pull request merge queue?
https://github.blog/changelog/2023-02-08-pull-request-merge-queue-public-beta/
It seems like a nice usability improvement.
COMMENT:
I saw the same issue with the merge queue in https://github.com/scikit-learn/scikit-learn/pull/25633. I increase the wait time to 90 minu... | 25,583 |
https://github.com/scikit-learn/scikit-learn/issues/25582 | [
"New Feature"
] | Add option to scale Matthews correlation coefficient (MCC) output to the [0, 1] range
### Describe the workflow you want to enable
Matthew's correlation coefficient is known to have a different range of possible values from most other classification performance metrics. While it's usual for metrics to lie in the [0... | 25,582 |
https://github.com/scikit-learn/scikit-learn/issues/25582 | [
"New Feature"
] | Add option to scale Matthews correlation coefficient (MCC) output to the [0, 1] range
### Describe the workflow you want to enable
Matthew's correlation coefficient is known to have a different range of possible values from most other classification performance metrics. While it's usual for metrics to lie in the [0... | 25,582 |
https://github.com/scikit-learn/scikit-learn/issues/25582 | [
"New Feature"
] | Add option to scale Matthews correlation coefficient (MCC) output to the [0, 1] range
### Describe the workflow you want to enable
Matthew's correlation coefficient is known to have a different range of possible values from most other classification performance metrics. While it's usual for metrics to lie in the [0... | 25,582 |
https://github.com/scikit-learn/scikit-learn/issues/25580 | [
"Bug",
"Needs Triage"
] | Proposal to change default value of n_neighbors in mutual_info_regression
### Describe the bug
Hi, recently I figured out that for short sequences default value of 3 is way too unstable and gives poor results.
Don't know the reasons why 3 was used, my testing shows that 2 is a far more appropriate choice for som... | 25,580 |
https://github.com/scikit-learn/scikit-learn/issues/25580 | [
"Bug",
"Needs Triage"
] | Proposal to change default value of n_neighbors in mutual_info_regression
### Describe the bug
Hi, recently I figured out that for short sequences default value of 3 is way too unstable and gives poor results.
Don't know the reasons why 3 was used, my testing shows that 2 is a far more appropriate choice for som... | 25,580 |
https://github.com/scikit-learn/scikit-learn/issues/25578 | [
"New Feature",
"Needs Triage"
] | Support pandas nullable dtypes for scoring metrics
### Describe the workflow you want to enable
I would like to be able to pass data with the nullable pandas dtypes (`Int64`, `Float64`, and `boolean`) into sklearn metrics such as `matthews_corrcoef`, `accuracy_score`, and `f1_score` (and more) even if the data does n... | 25,578 |
https://github.com/scikit-learn/scikit-learn/issues/25578 | [
"New Feature",
"Needs Triage"
] | Support pandas nullable dtypes for scoring metrics
### Describe the workflow you want to enable
I would like to be able to pass data with the nullable pandas dtypes (`Int64`, `Float64`, and `boolean`) into sklearn metrics such as `matthews_corrcoef`, `accuracy_score`, and `f1_score` (and more) even if the data does n... | 25,578 |
https://github.com/scikit-learn/scikit-learn/issues/25578 | [
"New Feature",
"Needs Triage"
] | Support pandas nullable dtypes for scoring metrics
### Describe the workflow you want to enable
I would like to be able to pass data with the nullable pandas dtypes (`Int64`, `Float64`, and `boolean`) into sklearn metrics such as `matthews_corrcoef`, `accuracy_score`, and `f1_score` (and more) even if the data does n... | 25,578 |
https://github.com/scikit-learn/scikit-learn/issues/25578 | [
"New Feature",
"Needs Triage"
] | Support pandas nullable dtypes for scoring metrics
### Describe the workflow you want to enable
I would like to be able to pass data with the nullable pandas dtypes (`Int64`, `Float64`, and `boolean`) into sklearn metrics such as `matthews_corrcoef`, `accuracy_score`, and `f1_score` (and more) even if the data does n... | 25,578 |
https://github.com/scikit-learn/scikit-learn/issues/25572 | [
"RFC",
"cython"
] | RFC Guideline for usage of Cython types
## Goal
Have a documented consensus on which types to use in Cython code.
### Types
We should distinguish between floating point numbers and integers. We may also split the use cases of integers: As data value and as index for pointers and memoryviews.
## Linked issues
... | 25,572 |
https://github.com/scikit-learn/scikit-learn/issues/25572 | [
"RFC",
"cython"
] | RFC Guideline for usage of Cython types
## Goal
Have a documented consensus on which types to use in Cython code.
### Types
We should distinguish between floating point numbers and integers. We may also split the use cases of integers: As data value and as index for pointers and memoryviews.
## Linked issues
... | 25,572 |
https://github.com/scikit-learn/scikit-learn/issues/25572 | [
"RFC",
"cython"
] | RFC Guideline for usage of Cython types
## Goal
Have a documented consensus on which types to use in Cython code.
### Types
We should distinguish between floating point numbers and integers. We may also split the use cases of integers: As data value and as index for pointers and memoryviews.
## Linked issues
... | 25,572 |
https://github.com/scikit-learn/scikit-learn/issues/25572 | [
"RFC",
"cython"
] | RFC Guideline for usage of Cython types
## Goal
Have a documented consensus on which types to use in Cython code.
### Types
We should distinguish between floating point numbers and integers. We may also split the use cases of integers: As data value and as index for pointers and memoryviews.
## Linked issues
... | 25,572 |
https://github.com/scikit-learn/scikit-learn/issues/25572 | [
"RFC",
"cython"
] | RFC Guideline for usage of Cython types
## Goal
Have a documented consensus on which types to use in Cython code.
### Types
We should distinguish between floating point numbers and integers. We may also split the use cases of integers: As data value and as index for pointers and memoryviews.
## Linked issues
... | 25,572 |
https://github.com/scikit-learn/scikit-learn/issues/25572 | [
"RFC",
"cython"
] | RFC Guideline for usage of Cython types
## Goal
Have a documented consensus on which types to use in Cython code.
### Types
We should distinguish between floating point numbers and integers. We may also split the use cases of integers: As data value and as index for pointers and memoryviews.
## Linked issues
... | 25,572 |
https://github.com/scikit-learn/scikit-learn/issues/25572 | [
"RFC",
"cython"
] | RFC Guideline for usage of Cython types
## Goal
Have a documented consensus on which types to use in Cython code.
### Types
We should distinguish between floating point numbers and integers. We may also split the use cases of integers: As data value and as index for pointers and memoryviews.
## Linked issues
... | 25,572 |
https://github.com/scikit-learn/scikit-learn/issues/25572 | [
"RFC",
"cython"
] | RFC Guideline for usage of Cython types
## Goal
Have a documented consensus on which types to use in Cython code.
### Types
We should distinguish between floating point numbers and integers. We may also split the use cases of integers: As data value and as index for pointers and memoryviews.
## Linked issues
... | 25,572 |
https://github.com/scikit-learn/scikit-learn/issues/25572 | [
"RFC",
"cython"
] | RFC Guideline for usage of Cython types
## Goal
Have a documented consensus on which types to use in Cython code.
### Types
We should distinguish between floating point numbers and integers. We may also split the use cases of integers: As data value and as index for pointers and memoryviews.
## Linked issues
... | 25,572 |
https://github.com/scikit-learn/scikit-learn/issues/25572 | [
"RFC",
"cython"
] | RFC Guideline for usage of Cython types
## Goal
Have a documented consensus on which types to use in Cython code.
### Types
We should distinguish between floating point numbers and integers. We may also split the use cases of integers: As data value and as index for pointers and memoryviews.
## Linked issues
... | 25,572 |
https://github.com/scikit-learn/scikit-learn/issues/25572 | [
"RFC",
"cython"
] | RFC Guideline for usage of Cython types
## Goal
Have a documented consensus on which types to use in Cython code.
### Types
We should distinguish between floating point numbers and integers. We may also split the use cases of integers: As data value and as index for pointers and memoryviews.
## Linked issues
... | 25,572 |
https://github.com/scikit-learn/scikit-learn/issues/25572 | [
"RFC",
"cython"
] | RFC Guideline for usage of Cython types
## Goal
Have a documented consensus on which types to use in Cython code.
### Types
We should distinguish between floating point numbers and integers. We may also split the use cases of integers: As data value and as index for pointers and memoryviews.
## Linked issues
... | 25,572 |
https://github.com/scikit-learn/scikit-learn/issues/25572 | [
"RFC",
"cython"
] | RFC Guideline for usage of Cython types
## Goal
Have a documented consensus on which types to use in Cython code.
### Types
We should distinguish between floating point numbers and integers. We may also split the use cases of integers: As data value and as index for pointers and memoryviews.
## Linked issues
... | 25,572 |
https://github.com/scikit-learn/scikit-learn/issues/25572 | [
"RFC",
"cython"
] | RFC Guideline for usage of Cython types
## Goal
Have a documented consensus on which types to use in Cython code.
### Types
We should distinguish between floating point numbers and integers. We may also split the use cases of integers: As data value and as index for pointers and memoryviews.
## Linked issues
... | 25,572 |
https://github.com/scikit-learn/scikit-learn/issues/25572 | [
"RFC",
"cython"
] | RFC Guideline for usage of Cython types
## Goal
Have a documented consensus on which types to use in Cython code.
### Types
We should distinguish between floating point numbers and integers. We may also split the use cases of integers: As data value and as index for pointers and memoryviews.
## Linked issues
... | 25,572 |
https://github.com/scikit-learn/scikit-learn/issues/25572 | [
"RFC",
"cython"
] | RFC Guideline for usage of Cython types
## Goal
Have a documented consensus on which types to use in Cython code.
### Types
We should distinguish between floating point numbers and integers. We may also split the use cases of integers: As data value and as index for pointers and memoryviews.
## Linked issues
... | 25,572 |
https://github.com/scikit-learn/scikit-learn/issues/25571 | [
"Bug"
] | Bug in Calibration Curve Documentation
### Describe the bug
https://scikit-learn.org/stable/auto_examples/calibration/plot_calibration_curve.html
In the calibration curve page, a "scores_df" is generated to showcase supporting model evaluation metrics in addition to the calibration curves.
I noticed that my ROC... | 25,571 |
https://github.com/scikit-learn/scikit-learn/issues/25571 | [
"Bug"
] | Bug in Calibration Curve Documentation
### Describe the bug
https://scikit-learn.org/stable/auto_examples/calibration/plot_calibration_curve.html
In the calibration curve page, a "scores_df" is generated to showcase supporting model evaluation metrics in addition to the calibration curves.
I noticed that my ROC... | 25,571 |
https://github.com/scikit-learn/scikit-learn/issues/25571 | [
"Bug"
] | Bug in Calibration Curve Documentation
### Describe the bug
https://scikit-learn.org/stable/auto_examples/calibration/plot_calibration_curve.html
In the calibration curve page, a "scores_df" is generated to showcase supporting model evaluation metrics in addition to the calibration curves.
I noticed that my ROC... | 25,571 |
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