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/28341 | [
"RFC"
] | RFC switch to Polars as the default dataframe lib in our examples
We now support polars as an output for our transformers and `ColumnTransformer`, but our examples use `pd.DataFrame`.
Our `datasets` module also returnes either a numpy array or a pandas DataFrame.
I'm suggesting that we enable datasets to return ... | 28,341 |
https://github.com/scikit-learn/scikit-learn/issues/28341 | [
"RFC"
] | RFC switch to Polars as the default dataframe lib in our examples
We now support polars as an output for our transformers and `ColumnTransformer`, but our examples use `pd.DataFrame`.
Our `datasets` module also returnes either a numpy array or a pandas DataFrame.
I'm suggesting that we enable datasets to return ... | 28,341 |
https://github.com/scikit-learn/scikit-learn/issues/28341 | [
"RFC"
] | RFC switch to Polars as the default dataframe lib in our examples
We now support polars as an output for our transformers and `ColumnTransformer`, but our examples use `pd.DataFrame`.
Our `datasets` module also returnes either a numpy array or a pandas DataFrame.
I'm suggesting that we enable datasets to return ... | 28,341 |
https://github.com/scikit-learn/scikit-learn/issues/28341 | [
"RFC"
] | RFC switch to Polars as the default dataframe lib in our examples
We now support polars as an output for our transformers and `ColumnTransformer`, but our examples use `pd.DataFrame`.
Our `datasets` module also returnes either a numpy array or a pandas DataFrame.
I'm suggesting that we enable datasets to return ... | 28,341 |
https://github.com/scikit-learn/scikit-learn/issues/28341 | [
"RFC"
] | RFC switch to Polars as the default dataframe lib in our examples
We now support polars as an output for our transformers and `ColumnTransformer`, but our examples use `pd.DataFrame`.
Our `datasets` module also returnes either a numpy array or a pandas DataFrame.
I'm suggesting that we enable datasets to return ... | 28,341 |
https://github.com/scikit-learn/scikit-learn/issues/28341 | [
"RFC"
] | RFC switch to Polars as the default dataframe lib in our examples
We now support polars as an output for our transformers and `ColumnTransformer`, but our examples use `pd.DataFrame`.
Our `datasets` module also returnes either a numpy array or a pandas DataFrame.
I'm suggesting that we enable datasets to return ... | 28,341 |
https://github.com/scikit-learn/scikit-learn/issues/28341 | [
"RFC"
] | RFC switch to Polars as the default dataframe lib in our examples
We now support polars as an output for our transformers and `ColumnTransformer`, but our examples use `pd.DataFrame`.
Our `datasets` module also returnes either a numpy array or a pandas DataFrame.
I'm suggesting that we enable datasets to return ... | 28,341 |
https://github.com/scikit-learn/scikit-learn/issues/28341 | [
"RFC"
] | RFC switch to Polars as the default dataframe lib in our examples
We now support polars as an output for our transformers and `ColumnTransformer`, but our examples use `pd.DataFrame`.
Our `datasets` module also returnes either a numpy array or a pandas DataFrame.
I'm suggesting that we enable datasets to return ... | 28,341 |
https://github.com/scikit-learn/scikit-learn/issues/28341 | [
"RFC"
] | RFC switch to Polars as the default dataframe lib in our examples
We now support polars as an output for our transformers and `ColumnTransformer`, but our examples use `pd.DataFrame`.
Our `datasets` module also returnes either a numpy array or a pandas DataFrame.
I'm suggesting that we enable datasets to return ... | 28,341 |
https://github.com/scikit-learn/scikit-learn/issues/28341 | [
"RFC"
] | RFC switch to Polars as the default dataframe lib in our examples
We now support polars as an output for our transformers and `ColumnTransformer`, but our examples use `pd.DataFrame`.
Our `datasets` module also returnes either a numpy array or a pandas DataFrame.
I'm suggesting that we enable datasets to return ... | 28,341 |
https://github.com/scikit-learn/scikit-learn/issues/28341 | [
"RFC"
] | RFC switch to Polars as the default dataframe lib in our examples
We now support polars as an output for our transformers and `ColumnTransformer`, but our examples use `pd.DataFrame`.
Our `datasets` module also returnes either a numpy array or a pandas DataFrame.
I'm suggesting that we enable datasets to return ... | 28,341 |
https://github.com/scikit-learn/scikit-learn/issues/28341 | [
"RFC"
] | RFC switch to Polars as the default dataframe lib in our examples
We now support polars as an output for our transformers and `ColumnTransformer`, but our examples use `pd.DataFrame`.
Our `datasets` module also returnes either a numpy array or a pandas DataFrame.
I'm suggesting that we enable datasets to return ... | 28,341 |
https://github.com/scikit-learn/scikit-learn/issues/28341 | [
"RFC"
] | RFC switch to Polars as the default dataframe lib in our examples
We now support polars as an output for our transformers and `ColumnTransformer`, but our examples use `pd.DataFrame`.
Our `datasets` module also returnes either a numpy array or a pandas DataFrame.
I'm suggesting that we enable datasets to return ... | 28,341 |
https://github.com/scikit-learn/scikit-learn/issues/28341 | [
"RFC"
] | RFC switch to Polars as the default dataframe lib in our examples
We now support polars as an output for our transformers and `ColumnTransformer`, but our examples use `pd.DataFrame`.
Our `datasets` module also returnes either a numpy array or a pandas DataFrame.
I'm suggesting that we enable datasets to return ... | 28,341 |
https://github.com/scikit-learn/scikit-learn/issues/28341 | [
"RFC"
] | RFC switch to Polars as the default dataframe lib in our examples
We now support polars as an output for our transformers and `ColumnTransformer`, but our examples use `pd.DataFrame`.
Our `datasets` module also returnes either a numpy array or a pandas DataFrame.
I'm suggesting that we enable datasets to return ... | 28,341 |
https://github.com/scikit-learn/scikit-learn/issues/28341 | [
"RFC"
] | RFC switch to Polars as the default dataframe lib in our examples
We now support polars as an output for our transformers and `ColumnTransformer`, but our examples use `pd.DataFrame`.
Our `datasets` module also returnes either a numpy array or a pandas DataFrame.
I'm suggesting that we enable datasets to return ... | 28,341 |
https://github.com/scikit-learn/scikit-learn/issues/28341 | [
"RFC"
] | RFC switch to Polars as the default dataframe lib in our examples
We now support polars as an output for our transformers and `ColumnTransformer`, but our examples use `pd.DataFrame`.
Our `datasets` module also returnes either a numpy array or a pandas DataFrame.
I'm suggesting that we enable datasets to return ... | 28,341 |
https://github.com/scikit-learn/scikit-learn/issues/28341 | [
"RFC"
] | RFC switch to Polars as the default dataframe lib in our examples
We now support polars as an output for our transformers and `ColumnTransformer`, but our examples use `pd.DataFrame`.
Our `datasets` module also returnes either a numpy array or a pandas DataFrame.
I'm suggesting that we enable datasets to return ... | 28,341 |
https://github.com/scikit-learn/scikit-learn/issues/28341 | [
"RFC"
] | RFC switch to Polars as the default dataframe lib in our examples
We now support polars as an output for our transformers and `ColumnTransformer`, but our examples use `pd.DataFrame`.
Our `datasets` module also returnes either a numpy array or a pandas DataFrame.
I'm suggesting that we enable datasets to return ... | 28,341 |
https://github.com/scikit-learn/scikit-learn/issues/28341 | [
"RFC"
] | RFC switch to Polars as the default dataframe lib in our examples
We now support polars as an output for our transformers and `ColumnTransformer`, but our examples use `pd.DataFrame`.
Our `datasets` module also returnes either a numpy array or a pandas DataFrame.
I'm suggesting that we enable datasets to return ... | 28,341 |
https://github.com/scikit-learn/scikit-learn/issues/28341 | [
"RFC"
] | RFC switch to Polars as the default dataframe lib in our examples
We now support polars as an output for our transformers and `ColumnTransformer`, but our examples use `pd.DataFrame`.
Our `datasets` module also returnes either a numpy array or a pandas DataFrame.
I'm suggesting that we enable datasets to return ... | 28,341 |
https://github.com/scikit-learn/scikit-learn/issues/28341 | [
"RFC"
] | RFC switch to Polars as the default dataframe lib in our examples
We now support polars as an output for our transformers and `ColumnTransformer`, but our examples use `pd.DataFrame`.
Our `datasets` module also returnes either a numpy array or a pandas DataFrame.
I'm suggesting that we enable datasets to return ... | 28,341 |
https://github.com/scikit-learn/scikit-learn/issues/28341 | [
"RFC"
] | RFC switch to Polars as the default dataframe lib in our examples
We now support polars as an output for our transformers and `ColumnTransformer`, but our examples use `pd.DataFrame`.
Our `datasets` module also returnes either a numpy array or a pandas DataFrame.
I'm suggesting that we enable datasets to return ... | 28,341 |
https://github.com/scikit-learn/scikit-learn/issues/28341 | [
"RFC"
] | RFC switch to Polars as the default dataframe lib in our examples
We now support polars as an output for our transformers and `ColumnTransformer`, but our examples use `pd.DataFrame`.
Our `datasets` module also returnes either a numpy array or a pandas DataFrame.
I'm suggesting that we enable datasets to return ... | 28,341 |
https://github.com/scikit-learn/scikit-learn/issues/28341 | [
"RFC"
] | RFC switch to Polars as the default dataframe lib in our examples
We now support polars as an output for our transformers and `ColumnTransformer`, but our examples use `pd.DataFrame`.
Our `datasets` module also returnes either a numpy array or a pandas DataFrame.
I'm suggesting that we enable datasets to return ... | 28,341 |
https://github.com/scikit-learn/scikit-learn/issues/28339 | [
"Bug"
] | Special characters (e.g. &) are not escaped by sklearn.tree.export_graphviz
### Describe the bug
Exporting a decision tree where the `feature_names` or `class_names` contain special characters (particularly `&<>`) results in invalid graphviz output, as those characters have specific meanings to graphviz. Escaping to ... | 28,339 |
https://github.com/scikit-learn/scikit-learn/issues/28339 | [
"Bug"
] | Special characters (e.g. &) are not escaped by sklearn.tree.export_graphviz
### Describe the bug
Exporting a decision tree where the `feature_names` or `class_names` contain special characters (particularly `&<>`) results in invalid graphviz output, as those characters have specific meanings to graphviz. Escaping to ... | 28,339 |
https://github.com/scikit-learn/scikit-learn/issues/28337 | [
"New Feature",
"Developer API"
] | Enforce `feature_names_in_` and `n_features_in_` in `check_estimator` post SLEP007 implementation
### Describe the workflow you want to enable
I would like to propose an enhancement to the `check_estimator` function, particularly in light of the implementation of SLEP007. As per SLEP007, which was integrated into s... | 28,337 |
https://github.com/scikit-learn/scikit-learn/issues/28337 | [
"New Feature",
"Developer API"
] | Enforce `feature_names_in_` and `n_features_in_` in `check_estimator` post SLEP007 implementation
### Describe the workflow you want to enable
I would like to propose an enhancement to the `check_estimator` function, particularly in light of the implementation of SLEP007. As per SLEP007, which was integrated into s... | 28,337 |
https://github.com/scikit-learn/scikit-learn/issues/28337 | [
"New Feature",
"Developer API"
] | Enforce `feature_names_in_` and `n_features_in_` in `check_estimator` post SLEP007 implementation
### Describe the workflow you want to enable
I would like to propose an enhancement to the `check_estimator` function, particularly in light of the implementation of SLEP007. As per SLEP007, which was integrated into s... | 28,337 |
https://github.com/scikit-learn/scikit-learn/issues/28337 | [
"New Feature",
"Developer API"
] | Enforce `feature_names_in_` and `n_features_in_` in `check_estimator` post SLEP007 implementation
### Describe the workflow you want to enable
I would like to propose an enhancement to the `check_estimator` function, particularly in light of the implementation of SLEP007. As per SLEP007, which was integrated into s... | 28,337 |
https://github.com/scikit-learn/scikit-learn/issues/28337 | [
"New Feature",
"Developer API"
] | Enforce `feature_names_in_` and `n_features_in_` in `check_estimator` post SLEP007 implementation
### Describe the workflow you want to enable
I would like to propose an enhancement to the `check_estimator` function, particularly in light of the implementation of SLEP007. As per SLEP007, which was integrated into s... | 28,337 |
https://github.com/scikit-learn/scikit-learn/issues/28337 | [
"New Feature",
"Developer API"
] | Enforce `feature_names_in_` and `n_features_in_` in `check_estimator` post SLEP007 implementation
### Describe the workflow you want to enable
I would like to propose an enhancement to the `check_estimator` function, particularly in light of the implementation of SLEP007. As per SLEP007, which was integrated into s... | 28,337 |
https://github.com/scikit-learn/scikit-learn/issues/28337 | [
"New Feature",
"Developer API"
] | Enforce `feature_names_in_` and `n_features_in_` in `check_estimator` post SLEP007 implementation
### Describe the workflow you want to enable
I would like to propose an enhancement to the `check_estimator` function, particularly in light of the implementation of SLEP007. As per SLEP007, which was integrated into s... | 28,337 |
https://github.com/scikit-learn/scikit-learn/issues/28337 | [
"New Feature",
"Developer API"
] | Enforce `feature_names_in_` and `n_features_in_` in `check_estimator` post SLEP007 implementation
### Describe the workflow you want to enable
I would like to propose an enhancement to the `check_estimator` function, particularly in light of the implementation of SLEP007. As per SLEP007, which was integrated into s... | 28,337 |
https://github.com/scikit-learn/scikit-learn/issues/28337 | [
"New Feature",
"Developer API"
] | Enforce `feature_names_in_` and `n_features_in_` in `check_estimator` post SLEP007 implementation
### Describe the workflow you want to enable
I would like to propose an enhancement to the `check_estimator` function, particularly in light of the implementation of SLEP007. As per SLEP007, which was integrated into s... | 28,337 |
https://github.com/scikit-learn/scikit-learn/issues/28337 | [
"New Feature",
"Developer API"
] | Enforce `feature_names_in_` and `n_features_in_` in `check_estimator` post SLEP007 implementation
### Describe the workflow you want to enable
I would like to propose an enhancement to the `check_estimator` function, particularly in light of the implementation of SLEP007. As per SLEP007, which was integrated into s... | 28,337 |
https://github.com/scikit-learn/scikit-learn/issues/28337 | [
"New Feature",
"Developer API"
] | Enforce `feature_names_in_` and `n_features_in_` in `check_estimator` post SLEP007 implementation
### Describe the workflow you want to enable
I would like to propose an enhancement to the `check_estimator` function, particularly in light of the implementation of SLEP007. As per SLEP007, which was integrated into s... | 28,337 |
https://github.com/scikit-learn/scikit-learn/issues/28335 | [
"Needs Triage"
] | ⚠️ CI failed on Linux.pymin_conda_defaults_openblas ⚠️
**CI failed on [Linux.pymin_conda_defaults_openblas](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=63344&view=logs&j=66042141-7fd2-581d-812e-1a1b1d5e0f0c)** (Feb 01, 2024)
- sklearn.linear_model._ridge.ridge_regression
COMMENT:
Doctest wi... | 28,335 |
https://github.com/scikit-learn/scikit-learn/issues/28325 | [
"Build / CI"
] | Migrate macOS arm64 wheel building and testing CI to GitHub Actions runner
Our Cirrus CI account often gets rate limited because we tend to exhaust the credits allocated for free to Open Source project.
This can slow down the release process quite significantly.
Fortunately, GitHub Actions just introduced new M1... | 28,325 |
https://github.com/scikit-learn/scikit-learn/issues/28324 | [
"Documentation",
"Needs Triage"
] | [Question, Documentation] Metadata Routing, indicate metadata is required by a method
### Describe the issue linked to the documentation
From my understanding, there is no way to specify that some metadata is required with `set_*_request(...)`.
Doc: https://scikit-learn.org/stable/metadata_routing.html#api-inter... | 28,324 |
https://github.com/scikit-learn/scikit-learn/issues/28321 | [
"Documentation"
] | TimeSeriesSplit Train Size formula correction
### Describe the issue linked to the documentation
The documentation states:
> The training set has size `i * n_samples // (n_splits + 1) + n_samples % (n_splits + 1)` in the `i`th split, with a test set of size `n_samples // (n_splits + 1)` by default, where `n_sample... | 28,321 |
https://github.com/scikit-learn/scikit-learn/issues/28321 | [
"Documentation"
] | TimeSeriesSplit Train Size formula correction
### Describe the issue linked to the documentation
The documentation states:
> The training set has size `i * n_samples // (n_splits + 1) + n_samples % (n_splits + 1)` in the `i`th split, with a test set of size `n_samples // (n_splits + 1)` by default, where `n_sample... | 28,321 |
https://github.com/scikit-learn/scikit-learn/issues/28321 | [
"Documentation"
] | TimeSeriesSplit Train Size formula correction
### Describe the issue linked to the documentation
The documentation states:
> The training set has size `i * n_samples // (n_splits + 1) + n_samples % (n_splits + 1)` in the `i`th split, with a test set of size `n_samples // (n_splits + 1)` by default, where `n_sample... | 28,321 |
https://github.com/scikit-learn/scikit-learn/issues/28321 | [
"Documentation"
] | TimeSeriesSplit Train Size formula correction
### Describe the issue linked to the documentation
The documentation states:
> The training set has size `i * n_samples // (n_splits + 1) + n_samples % (n_splits + 1)` in the `i`th split, with a test set of size `n_samples // (n_splits + 1)` by default, where `n_sample... | 28,321 |
https://github.com/scikit-learn/scikit-learn/issues/28321 | [
"Documentation"
] | TimeSeriesSplit Train Size formula correction
### Describe the issue linked to the documentation
The documentation states:
> The training set has size `i * n_samples // (n_splits + 1) + n_samples % (n_splits + 1)` in the `i`th split, with a test set of size `n_samples // (n_splits + 1)` by default, where `n_sample... | 28,321 |
https://github.com/scikit-learn/scikit-learn/issues/28321 | [
"Documentation"
] | TimeSeriesSplit Train Size formula correction
### Describe the issue linked to the documentation
The documentation states:
> The training set has size `i * n_samples // (n_splits + 1) + n_samples % (n_splits + 1)` in the `i`th split, with a test set of size `n_samples // (n_splits + 1)` by default, where `n_sample... | 28,321 |
https://github.com/scikit-learn/scikit-learn/issues/28321 | [
"Documentation"
] | TimeSeriesSplit Train Size formula correction
### Describe the issue linked to the documentation
The documentation states:
> The training set has size `i * n_samples // (n_splits + 1) + n_samples % (n_splits + 1)` in the `i`th split, with a test set of size `n_samples // (n_splits + 1)` by default, where `n_sample... | 28,321 |
https://github.com/scikit-learn/scikit-learn/issues/28317 | [
"Bug",
"Regression"
] | `HistGradientBoostingClassifier` does not support `pd.Int64Dtype` in v1.4.0
### Describe the bug
Fitting a `HistGradientBoostingClassifier` where one of the features has a `pd.Int64Dtype` dtype will give an error:
```
AttributeError: 'Int64Dtype' object has no attribute 'byteorder'
```
### Steps/Code to Re... | 28,317 |
https://github.com/scikit-learn/scikit-learn/issues/28317 | [
"Bug",
"Regression"
] | `HistGradientBoostingClassifier` does not support `pd.Int64Dtype` in v1.4.0
### Describe the bug
Fitting a `HistGradientBoostingClassifier` where one of the features has a `pd.Int64Dtype` dtype will give an error:
```
AttributeError: 'Int64Dtype' object has no attribute 'byteorder'
```
### Steps/Code to Re... | 28,317 |
https://github.com/scikit-learn/scikit-learn/issues/28317 | [
"Bug",
"Regression"
] | `HistGradientBoostingClassifier` does not support `pd.Int64Dtype` in v1.4.0
### Describe the bug
Fitting a `HistGradientBoostingClassifier` where one of the features has a `pd.Int64Dtype` dtype will give an error:
```
AttributeError: 'Int64Dtype' object has no attribute 'byteorder'
```
### Steps/Code to Re... | 28,317 |
https://github.com/scikit-learn/scikit-learn/issues/28317 | [
"Bug",
"Regression"
] | `HistGradientBoostingClassifier` does not support `pd.Int64Dtype` in v1.4.0
### Describe the bug
Fitting a `HistGradientBoostingClassifier` where one of the features has a `pd.Int64Dtype` dtype will give an error:
```
AttributeError: 'Int64Dtype' object has no attribute 'byteorder'
```
### Steps/Code to Re... | 28,317 |
https://github.com/scikit-learn/scikit-learn/issues/28316 | [
"Bug"
] | TreeRegressors with MSE Criterion do not correctly handle missing-values
### Describe the bug
I found this bug when analyzing the PR/issue from #28295 and working on #27966.
Essentially, this bug is only found in `RegressorCriterion` because there one handles additionally the square of the `y` variables encoded ... | 28,316 |
https://github.com/scikit-learn/scikit-learn/issues/28316 | [
"Bug"
] | TreeRegressors with MSE Criterion do not correctly handle missing-values
### Describe the bug
I found this bug when analyzing the PR/issue from #28295 and working on #27966.
Essentially, this bug is only found in `RegressorCriterion` because there one handles additionally the square of the `y` variables encoded ... | 28,316 |
https://github.com/scikit-learn/scikit-learn/issues/28316 | [
"Bug"
] | TreeRegressors with MSE Criterion do not correctly handle missing-values
### Describe the bug
I found this bug when analyzing the PR/issue from #28295 and working on #27966.
Essentially, this bug is only found in `RegressorCriterion` because there one handles additionally the square of the `y` variables encoded ... | 28,316 |
https://github.com/scikit-learn/scikit-learn/issues/28316 | [
"Bug"
] | TreeRegressors with MSE Criterion do not correctly handle missing-values
### Describe the bug
I found this bug when analyzing the PR/issue from #28295 and working on #27966.
Essentially, this bug is only found in `RegressorCriterion` because there one handles additionally the square of the `y` variables encoded ... | 28,316 |
https://github.com/scikit-learn/scikit-learn/issues/28316 | [
"Bug"
] | TreeRegressors with MSE Criterion do not correctly handle missing-values
### Describe the bug
I found this bug when analyzing the PR/issue from #28295 and working on #27966.
Essentially, this bug is only found in `RegressorCriterion` because there one handles additionally the square of the `y` variables encoded ... | 28,316 |
https://github.com/scikit-learn/scikit-learn/issues/28316 | [
"Bug"
] | TreeRegressors with MSE Criterion do not correctly handle missing-values
### Describe the bug
I found this bug when analyzing the PR/issue from #28295 and working on #27966.
Essentially, this bug is only found in `RegressorCriterion` because there one handles additionally the square of the `y` variables encoded ... | 28,316 |
https://github.com/scikit-learn/scikit-learn/issues/28316 | [
"Bug"
] | TreeRegressors with MSE Criterion do not correctly handle missing-values
### Describe the bug
I found this bug when analyzing the PR/issue from #28295 and working on #27966.
Essentially, this bug is only found in `RegressorCriterion` because there one handles additionally the square of the `y` variables encoded ... | 28,316 |
https://github.com/scikit-learn/scikit-learn/issues/28316 | [
"Bug"
] | TreeRegressors with MSE Criterion do not correctly handle missing-values
### Describe the bug
I found this bug when analyzing the PR/issue from #28295 and working on #27966.
Essentially, this bug is only found in `RegressorCriterion` because there one handles additionally the square of the `y` variables encoded ... | 28,316 |
https://github.com/scikit-learn/scikit-learn/issues/28314 | [
"Documentation"
] | Request to update "Choosing the Right Estimator" Graphic (scikit-learn algorithm cheat sheet)
### Describe the issue linked to the documentation
As seen here:
https://scikit-learn.org/stable/tutorial/machine_learning_map/index.html
One of the "tough luck" paths that go through the clustering section appear to say... | 28,314 |
https://github.com/scikit-learn/scikit-learn/issues/28314 | [
"Documentation"
] | Request to update "Choosing the Right Estimator" Graphic (scikit-learn algorithm cheat sheet)
### Describe the issue linked to the documentation
As seen here:
https://scikit-learn.org/stable/tutorial/machine_learning_map/index.html
One of the "tough luck" paths that go through the clustering section appear to say... | 28,314 |
https://github.com/scikit-learn/scikit-learn/issues/28313 | [
"Bug",
"Needs Triage"
] | Errors in Iterative Imputer Column Naming with scikit-learn 1.4 Integration
### Describe the bug
When attempting to support scikit-learn 1.4 in Pycaret, several bugs arose. Despite efforts to address them, including creating patches in Pycaret, issues persist, particularly regarding iterative imputation and related... | 28,313 |
https://github.com/scikit-learn/scikit-learn/issues/28313 | [
"Bug",
"Needs Triage"
] | Errors in Iterative Imputer Column Naming with scikit-learn 1.4 Integration
### Describe the bug
When attempting to support scikit-learn 1.4 in Pycaret, several bugs arose. Despite efforts to address them, including creating patches in Pycaret, issues persist, particularly regarding iterative imputation and related... | 28,313 |
https://github.com/scikit-learn/scikit-learn/issues/28310 | [
"Bug"
] | `ARDRegressor` variance prediction fails on `X: pd.DataFrame`
### Describe the bug
`ARDRegressor.predict` fails if `return_std=True` and `X` is `pd.DataFrame`.
The failure occurs at the line `X = X[:, self.lambda_ < self.threshold_lambda]`.
The problem occurred while writing an adapter in `skpro` and testing AP... | 28,310 |
https://github.com/scikit-learn/scikit-learn/issues/28310 | [
"Bug"
] | `ARDRegressor` variance prediction fails on `X: pd.DataFrame`
### Describe the bug
`ARDRegressor.predict` fails if `return_std=True` and `X` is `pd.DataFrame`.
The failure occurs at the line `X = X[:, self.lambda_ < self.threshold_lambda]`.
The problem occurred while writing an adapter in `skpro` and testing AP... | 28,310 |
https://github.com/scikit-learn/scikit-learn/issues/28310 | [
"Bug"
] | `ARDRegressor` variance prediction fails on `X: pd.DataFrame`
### Describe the bug
`ARDRegressor.predict` fails if `return_std=True` and `X` is `pd.DataFrame`.
The failure occurs at the line `X = X[:, self.lambda_ < self.threshold_lambda]`.
The problem occurred while writing an adapter in `skpro` and testing AP... | 28,310 |
https://github.com/scikit-learn/scikit-learn/issues/28309 | [
"Bug"
] | SimpleImputer silently cast fill values to integer when the input is of integer type
### Describe the bug
Fitting the SimpleImputer on an integer array silently cast the float `fill_value` values to integer. If `fill_value` is nan, nothing is imputed but a warning is raise:
`RuntimeWarning: invalid value encountered... | 28,309 |
https://github.com/scikit-learn/scikit-learn/issues/28309 | [
"Bug"
] | SimpleImputer silently cast fill values to integer when the input is of integer type
### Describe the bug
Fitting the SimpleImputer on an integer array silently cast the float `fill_value` values to integer. If `fill_value` is nan, nothing is imputed but a warning is raise:
`RuntimeWarning: invalid value encountered... | 28,309 |
https://github.com/scikit-learn/scikit-learn/issues/28309 | [
"Bug"
] | SimpleImputer silently cast fill values to integer when the input is of integer type
### Describe the bug
Fitting the SimpleImputer on an integer array silently cast the float `fill_value` values to integer. If `fill_value` is nan, nothing is imputed but a warning is raise:
`RuntimeWarning: invalid value encountered... | 28,309 |
https://github.com/scikit-learn/scikit-learn/issues/28307 | [
"Needs Triage"
] | MAINT remove old git branches
Can we delete old branches?
- ~~https://github.com/scikit-learn/scikit-learn/tree/feature/PairwiseDistances @jjerphan~~
- https://github.com/scikit-learn/scikit-learn/tree/debian
COMMENT:
> https://github.com/scikit-learn/scikit-learn/tree/feature/PairwiseDistances @jjerphan
`featur... | 28,307 |
https://github.com/scikit-learn/scikit-learn/issues/28307 | [
"Needs Triage"
] | MAINT remove old git branches
Can we delete old branches?
- ~~https://github.com/scikit-learn/scikit-learn/tree/feature/PairwiseDistances @jjerphan~~
- https://github.com/scikit-learn/scikit-learn/tree/debian
COMMENT:
Seems somebody also deleted `debian`, so closing this. Thanks @lorentzenchr | 28,307 |
https://github.com/scikit-learn/scikit-learn/issues/28302 | [
"Needs Triage"
] | ⚠️ CI failed on Wheel builder ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/7720901536)** (Jan 31, 2024)
COMMENT:
This seems legit since it starts to break in https://github.com/scikit-learn/scikit-learn/pull/28303
There is something going on with Python 3.9 | 28,302 |
https://github.com/scikit-learn/scikit-learn/issues/28302 | [
"Needs Triage"
] | ⚠️ CI failed on Wheel builder ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/7720901536)** (Jan 31, 2024)
COMMENT:
This seems related to pytest 8, I have seen some of it elsewhere I think | 28,302 |
https://github.com/scikit-learn/scikit-learn/issues/28302 | [
"Needs Triage"
] | ⚠️ CI failed on Wheel builder ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/7720901536)** (Jan 31, 2024)
COMMENT:
I have some local fixes for pytest 8. Right now the situation is a bit complicated with lock-files update (mostly pandas Pyarrow dependency warning ... | 28,302 |
https://github.com/scikit-learn/scikit-learn/issues/28302 | [
"Needs Triage"
] | ⚠️ CI failed on Wheel builder ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/7720901536)** (Jan 31, 2024)
COMMENT:
## CI is no longer failing! ✅
[Successful run](https://github.com/scikit-learn/scikit-learn/actions/runs/7735950076) on Feb 01, 2024 | 28,302 |
https://github.com/scikit-learn/scikit-learn/issues/28302 | [
"Needs Triage"
] | ⚠️ CI failed on Wheel builder ⚠️
**CI is still failing on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/7720901536)** (Jan 31, 2024)
COMMENT:
Nice to see this finally working after the pandas 2.2 warnings and pytest 8 work! | 28,302 |
https://github.com/scikit-learn/scikit-learn/issues/28299 | [
"New Feature"
] | [API] A public API for creating and using multiple scorers in the sklearn-ecosystem
### Describe the workflow you want to enable
I would like a **public** stable interface for multiple scorers that can be developed against for the sklearn eco-system.
Without this, it makes it difficult for libraries to provide a... | 28,299 |
https://github.com/scikit-learn/scikit-learn/issues/28299 | [
"New Feature"
] | [API] A public API for creating and using multiple scorers in the sklearn-ecosystem
### Describe the workflow you want to enable
I would like a **public** stable interface for multiple scorers that can be developed against for the sklearn eco-system.
Without this, it makes it difficult for libraries to provide a... | 28,299 |
https://github.com/scikit-learn/scikit-learn/issues/28299 | [
"New Feature"
] | [API] A public API for creating and using multiple scorers in the sklearn-ecosystem
### Describe the workflow you want to enable
I would like a **public** stable interface for multiple scorers that can be developed against for the sklearn eco-system.
Without this, it makes it difficult for libraries to provide a... | 28,299 |
https://github.com/scikit-learn/scikit-learn/issues/28299 | [
"New Feature"
] | [API] A public API for creating and using multiple scorers in the sklearn-ecosystem
### Describe the workflow you want to enable
I would like a **public** stable interface for multiple scorers that can be developed against for the sklearn eco-system.
Without this, it makes it difficult for libraries to provide a... | 28,299 |
https://github.com/scikit-learn/scikit-learn/issues/28299 | [
"New Feature"
] | [API] A public API for creating and using multiple scorers in the sklearn-ecosystem
### Describe the workflow you want to enable
I would like a **public** stable interface for multiple scorers that can be developed against for the sklearn eco-system.
Without this, it makes it difficult for libraries to provide a... | 28,299 |
https://github.com/scikit-learn/scikit-learn/issues/28299 | [
"New Feature"
] | [API] A public API for creating and using multiple scorers in the sklearn-ecosystem
### Describe the workflow you want to enable
I would like a **public** stable interface for multiple scorers that can be developed against for the sklearn eco-system.
Without this, it makes it difficult for libraries to provide a... | 28,299 |
https://github.com/scikit-learn/scikit-learn/issues/28299 | [
"New Feature"
] | [API] A public API for creating and using multiple scorers in the sklearn-ecosystem
### Describe the workflow you want to enable
I would like a **public** stable interface for multiple scorers that can be developed against for the sklearn eco-system.
Without this, it makes it difficult for libraries to provide a... | 28,299 |
https://github.com/scikit-learn/scikit-learn/issues/28298 | [
"Bug"
] | Trees are doing too many split with missing values
In the following example:
```python
import numpy as np
import sklearn
from sklearn.datasets import load_iris
from sklearn.tree import DecisionTreeClassifier
from sklearn.model_selection import train_test_split
X, y = load_iris(as_frame=True, return_X_y=True... | 28,298 |
https://github.com/scikit-learn/scikit-learn/issues/28297 | [
"Bug"
] | Getting HTTPError: HTTP Error 403: Forbidden when trying to load California Housing dataset
### Describe the bug
When trying to load the dataset I get an error.
### Steps/Code to Reproduce
```
from sklearn.datasets import fetch_california_housing
from sklearn.model_selection import train_test_split
from sklearn... | 28,297 |
https://github.com/scikit-learn/scikit-learn/issues/28297 | [
"Bug"
] | Getting HTTPError: HTTP Error 403: Forbidden when trying to load California Housing dataset
### Describe the bug
When trying to load the dataset I get an error.
### Steps/Code to Reproduce
```
from sklearn.datasets import fetch_california_housing
from sklearn.model_selection import train_test_split
from sklearn... | 28,297 |
https://github.com/scikit-learn/scikit-learn/issues/28297 | [
"Bug"
] | Getting HTTPError: HTTP Error 403: Forbidden when trying to load California Housing dataset
### Describe the bug
When trying to load the dataset I get an error.
### Steps/Code to Reproduce
```
from sklearn.datasets import fetch_california_housing
from sklearn.model_selection import train_test_split
from sklearn... | 28,297 |
https://github.com/scikit-learn/scikit-learn/issues/28297 | [
"Bug"
] | Getting HTTPError: HTTP Error 403: Forbidden when trying to load California Housing dataset
### Describe the bug
When trying to load the dataset I get an error.
### Steps/Code to Reproduce
```
from sklearn.datasets import fetch_california_housing
from sklearn.model_selection import train_test_split
from sklearn... | 28,297 |
https://github.com/scikit-learn/scikit-learn/issues/28297 | [
"Bug"
] | Getting HTTPError: HTTP Error 403: Forbidden when trying to load California Housing dataset
### Describe the bug
When trying to load the dataset I get an error.
### Steps/Code to Reproduce
```
from sklearn.datasets import fetch_california_housing
from sklearn.model_selection import train_test_split
from sklearn... | 28,297 |
https://github.com/scikit-learn/scikit-learn/issues/28297 | [
"Bug"
] | Getting HTTPError: HTTP Error 403: Forbidden when trying to load California Housing dataset
### Describe the bug
When trying to load the dataset I get an error.
### Steps/Code to Reproduce
```
from sklearn.datasets import fetch_california_housing
from sklearn.model_selection import train_test_split
from sklearn... | 28,297 |
https://github.com/scikit-learn/scikit-learn/issues/28297 | [
"Bug"
] | Getting HTTPError: HTTP Error 403: Forbidden when trying to load California Housing dataset
### Describe the bug
When trying to load the dataset I get an error.
### Steps/Code to Reproduce
```
from sklearn.datasets import fetch_california_housing
from sklearn.model_selection import train_test_split
from sklearn... | 28,297 |
https://github.com/scikit-learn/scikit-learn/issues/28297 | [
"Bug"
] | Getting HTTPError: HTTP Error 403: Forbidden when trying to load California Housing dataset
### Describe the bug
When trying to load the dataset I get an error.
### Steps/Code to Reproduce
```
from sklearn.datasets import fetch_california_housing
from sklearn.model_selection import train_test_split
from sklearn... | 28,297 |
https://github.com/scikit-learn/scikit-learn/issues/28297 | [
"Bug"
] | Getting HTTPError: HTTP Error 403: Forbidden when trying to load California Housing dataset
### Describe the bug
When trying to load the dataset I get an error.
### Steps/Code to Reproduce
```
from sklearn.datasets import fetch_california_housing
from sklearn.model_selection import train_test_split
from sklearn... | 28,297 |
https://github.com/scikit-learn/scikit-learn/issues/28297 | [
"Bug"
] | Getting HTTPError: HTTP Error 403: Forbidden when trying to load California Housing dataset
### Describe the bug
When trying to load the dataset I get an error.
### Steps/Code to Reproduce
```
from sklearn.datasets import fetch_california_housing
from sklearn.model_selection import train_test_split
from sklearn... | 28,297 |
https://github.com/scikit-learn/scikit-learn/issues/28297 | [
"Bug"
] | Getting HTTPError: HTTP Error 403: Forbidden when trying to load California Housing dataset
### Describe the bug
When trying to load the dataset I get an error.
### Steps/Code to Reproduce
```
from sklearn.datasets import fetch_california_housing
from sklearn.model_selection import train_test_split
from sklearn... | 28,297 |
https://github.com/scikit-learn/scikit-learn/issues/28297 | [
"Bug"
] | Getting HTTPError: HTTP Error 403: Forbidden when trying to load California Housing dataset
### Describe the bug
When trying to load the dataset I get an error.
### Steps/Code to Reproduce
```
from sklearn.datasets import fetch_california_housing
from sklearn.model_selection import train_test_split
from sklearn... | 28,297 |
https://github.com/scikit-learn/scikit-learn/issues/28297 | [
"Bug"
] | Getting HTTPError: HTTP Error 403: Forbidden when trying to load California Housing dataset
### Describe the bug
When trying to load the dataset I get an error.
### Steps/Code to Reproduce
```
from sklearn.datasets import fetch_california_housing
from sklearn.model_selection import train_test_split
from sklearn... | 28,297 |
https://github.com/scikit-learn/scikit-learn/issues/28297 | [
"Bug"
] | Getting HTTPError: HTTP Error 403: Forbidden when trying to load California Housing dataset
### Describe the bug
When trying to load the dataset I get an error.
### Steps/Code to Reproduce
```
from sklearn.datasets import fetch_california_housing
from sklearn.model_selection import train_test_split
from sklearn... | 28,297 |
https://github.com/scikit-learn/scikit-learn/issues/28297 | [
"Bug"
] | Getting HTTPError: HTTP Error 403: Forbidden when trying to load California Housing dataset
### Describe the bug
When trying to load the dataset I get an error.
### Steps/Code to Reproduce
```
from sklearn.datasets import fetch_california_housing
from sklearn.model_selection import train_test_split
from sklearn... | 28,297 |
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