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/26927 | [
"Documentation",
"Sprint",
"good first issue",
"Meta-issue"
] | Add links to examples from the docstrings and user guides
We have a rich set of examples covering a very broad range of issues, but they're not necessarily easily discoverable via the section on the bottom of the API pages.
This meta-issue is to keep track of the examples for which we've already included links in t... | 26,927 |
https://github.com/scikit-learn/scikit-learn/issues/26927 | [
"Documentation",
"Sprint",
"good first issue",
"Meta-issue"
] | Add links to examples from the docstrings and user guides
We have a rich set of examples covering a very broad range of issues, but they're not necessarily easily discoverable via the section on the bottom of the API pages.
This meta-issue is to keep track of the examples for which we've already included links in t... | 26,927 |
https://github.com/scikit-learn/scikit-learn/issues/26927 | [
"Documentation",
"Sprint",
"good first issue",
"Meta-issue"
] | Add links to examples from the docstrings and user guides
We have a rich set of examples covering a very broad range of issues, but they're not necessarily easily discoverable via the section on the bottom of the API pages.
This meta-issue is to keep track of the examples for which we've already included links in t... | 26,927 |
https://github.com/scikit-learn/scikit-learn/issues/26927 | [
"Documentation",
"Sprint",
"good first issue",
"Meta-issue"
] | Add links to examples from the docstrings and user guides
We have a rich set of examples covering a very broad range of issues, but they're not necessarily easily discoverable via the section on the bottom of the API pages.
This meta-issue is to keep track of the examples for which we've already included links in t... | 26,927 |
https://github.com/scikit-learn/scikit-learn/issues/26927 | [
"Documentation",
"Sprint",
"good first issue",
"Meta-issue"
] | Add links to examples from the docstrings and user guides
We have a rich set of examples covering a very broad range of issues, but they're not necessarily easily discoverable via the section on the bottom of the API pages.
This meta-issue is to keep track of the examples for which we've already included links in t... | 26,927 |
https://github.com/scikit-learn/scikit-learn/issues/26927 | [
"Documentation",
"Sprint",
"good first issue",
"Meta-issue"
] | Add links to examples from the docstrings and user guides
We have a rich set of examples covering a very broad range of issues, but they're not necessarily easily discoverable via the section on the bottom of the API pages.
This meta-issue is to keep track of the examples for which we've already included links in t... | 26,927 |
https://github.com/scikit-learn/scikit-learn/issues/26927 | [
"Documentation",
"Sprint",
"good first issue",
"Meta-issue"
] | Add links to examples from the docstrings and user guides
We have a rich set of examples covering a very broad range of issues, but they're not necessarily easily discoverable via the section on the bottom of the API pages.
This meta-issue is to keep track of the examples for which we've already included links in t... | 26,927 |
https://github.com/scikit-learn/scikit-learn/issues/26925 | [
"Documentation",
"module:tree"
] | [DOCS] Missing values are now supported in Decision Trees
v1.3 of scikit-learn introduced some missing value support as evident in the same documentation [file](https://scikit-learn.org/stable/modules/tree.html#tree-missing-value-support) later on but it still states in the beginning of the dos that missing values are... | 26,925 |
https://github.com/scikit-learn/scikit-learn/issues/26925 | [
"Documentation",
"module:tree"
] | [DOCS] Missing values are now supported in Decision Trees
v1.3 of scikit-learn introduced some missing value support as evident in the same documentation [file](https://scikit-learn.org/stable/modules/tree.html#tree-missing-value-support) later on but it still states in the beginning of the dos that missing values are... | 26,925 |
https://github.com/scikit-learn/scikit-learn/issues/26921 | [
"Needs Investigation"
] | ⚠️ CI failed on macos_arm64_wheel ⚠️
**CI is still failing on [macos_arm64_wheel](https://cirrus-ci.com/build/6592550258081792)** (Oct 15, 2023)
COMMENT:
The CI fails for Python 3.11 because of a failing SciPy import. Here is the backtrack:
```bash
+ pytest --pyargs sklearn -n 4
============================= tes... | 26,921 |
https://github.com/scikit-learn/scikit-learn/issues/26921 | [
"Needs Investigation"
] | ⚠️ CI failed on macos_arm64_wheel ⚠️
**CI is still failing on [macos_arm64_wheel](https://cirrus-ci.com/build/6592550258081792)** (Oct 15, 2023)
COMMENT:
The latest error is the graphical lasso one and has been fixed in https://github.com/scikit-learn/scikit-learn/pull/27616. | 26,921 |
https://github.com/scikit-learn/scikit-learn/issues/26914 | [
"Bug",
"module:cluster",
"Needs Reproducible Code"
] | BUG (likely): DBSCAN producing strange results on a geographical dataset
### Describe the bug
The issue has been described under this StackOverflow question: [https://stackoverflow.com/questions/76774329/dbscan-producing-strange-results-on-a-ships-location-dataset](https://stackoverflow.com/questions/76774329/dbscan-... | 26,914 |
https://github.com/scikit-learn/scikit-learn/issues/26914 | [
"Bug",
"module:cluster",
"Needs Reproducible Code"
] | BUG (likely): DBSCAN producing strange results on a geographical dataset
### Describe the bug
The issue has been described under this StackOverflow question: [https://stackoverflow.com/questions/76774329/dbscan-producing-strange-results-on-a-ships-location-dataset](https://stackoverflow.com/questions/76774329/dbscan-... | 26,914 |
https://github.com/scikit-learn/scikit-learn/issues/26914 | [
"Bug",
"module:cluster",
"Needs Reproducible Code"
] | BUG (likely): DBSCAN producing strange results on a geographical dataset
### Describe the bug
The issue has been described under this StackOverflow question: [https://stackoverflow.com/questions/76774329/dbscan-producing-strange-results-on-a-ships-location-dataset](https://stackoverflow.com/questions/76774329/dbscan-... | 26,914 |
https://github.com/scikit-learn/scikit-learn/issues/26912 | [
"New Feature",
"Needs Triage"
] | Add leaky_relu to Neural Network
### Describe the workflow you want to enable
I would like to use the leaky_relu activation function with MLP Classifier , I thought it has already become quite popular due to its ability to be more robust to noise as compared to relu & avoid the dying relu problem. I think we should c... | 26,912 |
https://github.com/scikit-learn/scikit-learn/issues/26906 | [
"Documentation"
] | DOC Remove some links from the list of related packages
From the list https://scikit-learn.org/stable/related_projects.html, I propose to remove
- svmlight-loader
Reason: Not installable via `pip install`, not license
- Neptune because it is not really usable without an account. Was added in #20767.
- rep
Rea... | 26,906 |
https://github.com/scikit-learn/scikit-learn/issues/26906 | [
"Documentation"
] | DOC Remove some links from the list of related packages
From the list https://scikit-learn.org/stable/related_projects.html, I propose to remove
- svmlight-loader
Reason: Not installable via `pip install`, not license
- Neptune because it is not really usable without an account. Was added in #20767.
- rep
Rea... | 26,906 |
https://github.com/scikit-learn/scikit-learn/issues/26906 | [
"Documentation"
] | DOC Remove some links from the list of related packages
From the list https://scikit-learn.org/stable/related_projects.html, I propose to remove
- svmlight-loader
Reason: Not installable via `pip install`, not license
- Neptune because it is not really usable without an account. Was added in #20767.
- rep
Rea... | 26,906 |
https://github.com/scikit-learn/scikit-learn/issues/26905 | [
"Bug",
"Needs Triage"
] | Crash running `RandomForestClassifier` `fit` with very large values for `n_jobs`
### Describe the bug
When providing `RandomForestClassifier` with a high number of jobs, a `RuntimeError` is raised as the thread fails to start.
```
RuntimeError: can't start new thread
```
We have been fuzzing the library, we o... | 26,905 |
https://github.com/scikit-learn/scikit-learn/issues/26905 | [
"Bug",
"Needs Triage"
] | Crash running `RandomForestClassifier` `fit` with very large values for `n_jobs`
### Describe the bug
When providing `RandomForestClassifier` with a high number of jobs, a `RuntimeError` is raised as the thread fails to start.
```
RuntimeError: can't start new thread
```
We have been fuzzing the library, we o... | 26,905 |
https://github.com/scikit-learn/scikit-learn/issues/26905 | [
"Bug",
"Needs Triage"
] | Crash running `RandomForestClassifier` `fit` with very large values for `n_jobs`
### Describe the bug
When providing `RandomForestClassifier` with a high number of jobs, a `RuntimeError` is raised as the thread fails to start.
```
RuntimeError: can't start new thread
```
We have been fuzzing the library, we o... | 26,905 |
https://github.com/scikit-learn/scikit-learn/issues/26901 | [
"Needs Triage"
] | ⚠️ CI failed on macOS.pylatest_conda_forge_mkl ⚠️
**CI is still failing on [macOS.pylatest_conda_forge_mkl](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=58914&view=logs&j=97641769-79fb-5590-9088-a30ce9b850b9)** (Sep 12, 2023)
- test_pairwise_distances_argkmin[45-float32-parallel_on_X-citybloc... | 26,901 |
https://github.com/scikit-learn/scikit-learn/issues/26901 | [
"Needs Triage"
] | ⚠️ CI failed on macOS.pylatest_conda_forge_mkl ⚠️
**CI is still failing on [macOS.pylatest_conda_forge_mkl](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=58914&view=logs&j=97641769-79fb-5590-9088-a30ce9b850b9)** (Sep 12, 2023)
- test_pairwise_distances_argkmin[45-float32-parallel_on_X-citybloc... | 26,901 |
https://github.com/scikit-learn/scikit-learn/issues/26897 | [
"Needs Investigation",
"Validation"
] | Unclear message regarding param validation
In the context of https://github.com/scikit-learn/scikit-learn/pull/26896 I wrote a test and got a message which I'm really puzzled about. The error message says: `ValueError: No valid specification of the columns. Only a scalar, list or slice of all integers or all strings, ... | 26,897 |
https://github.com/scikit-learn/scikit-learn/issues/26897 | [
"Needs Investigation",
"Validation"
] | Unclear message regarding param validation
In the context of https://github.com/scikit-learn/scikit-learn/pull/26896 I wrote a test and got a message which I'm really puzzled about. The error message says: `ValueError: No valid specification of the columns. Only a scalar, list or slice of all integers or all strings, ... | 26,897 |
https://github.com/scikit-learn/scikit-learn/issues/26897 | [
"Needs Investigation",
"Validation"
] | Unclear message regarding param validation
In the context of https://github.com/scikit-learn/scikit-learn/pull/26896 I wrote a test and got a message which I'm really puzzled about. The error message says: `ValueError: No valid specification of the columns. Only a scalar, list or slice of all integers or all strings, ... | 26,897 |
https://github.com/scikit-learn/scikit-learn/issues/26897 | [
"Needs Investigation",
"Validation"
] | Unclear message regarding param validation
In the context of https://github.com/scikit-learn/scikit-learn/pull/26896 I wrote a test and got a message which I'm really puzzled about. The error message says: `ValueError: No valid specification of the columns. Only a scalar, list or slice of all integers or all strings, ... | 26,897 |
https://github.com/scikit-learn/scikit-learn/issues/26897 | [
"Needs Investigation",
"Validation"
] | Unclear message regarding param validation
In the context of https://github.com/scikit-learn/scikit-learn/pull/26896 I wrote a test and got a message which I'm really puzzled about. The error message says: `ValueError: No valid specification of the columns. Only a scalar, list or slice of all integers or all strings, ... | 26,897 |
https://github.com/scikit-learn/scikit-learn/issues/26895 | [
"Bug",
"Needs Triage"
] | OneHotEncoder linter issues on argument typing
### Describe the bug
The pyright lsp flags type warnings when a OneHotEncoder is initialized with categories as a list and/or dtype specified as anything but np.float64. Code runs fine, so this maybe should not be considered a bug. It is just a slight annoyance.
##... | 26,895 |
https://github.com/scikit-learn/scikit-learn/issues/26895 | [
"Bug",
"Needs Triage"
] | OneHotEncoder linter issues on argument typing
### Describe the bug
The pyright lsp flags type warnings when a OneHotEncoder is initialized with categories as a list and/or dtype specified as anything but np.float64. Code runs fine, so this maybe should not be considered a bug. It is just a slight annoyance.
##... | 26,895 |
https://github.com/scikit-learn/scikit-learn/issues/26895 | [
"Bug",
"Needs Triage"
] | OneHotEncoder linter issues on argument typing
### Describe the bug
The pyright lsp flags type warnings when a OneHotEncoder is initialized with categories as a list and/or dtype specified as anything but np.float64. Code runs fine, so this maybe should not be considered a bug. It is just a slight annoyance.
##... | 26,895 |
https://github.com/scikit-learn/scikit-learn/issues/26895 | [
"Bug",
"Needs Triage"
] | OneHotEncoder linter issues on argument typing
### Describe the bug
The pyright lsp flags type warnings when a OneHotEncoder is initialized with categories as a list and/or dtype specified as anything but np.float64. Code runs fine, so this maybe should not be considered a bug. It is just a slight annoyance.
##... | 26,895 |
https://github.com/scikit-learn/scikit-learn/issues/26895 | [
"Bug",
"Needs Triage"
] | OneHotEncoder linter issues on argument typing
### Describe the bug
The pyright lsp flags type warnings when a OneHotEncoder is initialized with categories as a list and/or dtype specified as anything but np.float64. Code runs fine, so this maybe should not be considered a bug. It is just a slight annoyance.
##... | 26,895 |
https://github.com/scikit-learn/scikit-learn/issues/26892 | [
"Bug",
"New Feature"
] | Balanced Accuracy Score is NOT equal to Recall Score
### Describe the bug
By definition balanced accuracy should be equal to recall averaged over all the classes. Current implementation gives different answers. Please see the example below.
```
import scikit.metrics as skm
y_true = [1,1]
y_pred = [1,2]
... | 26,892 |
https://github.com/scikit-learn/scikit-learn/issues/26892 | [
"Bug",
"New Feature"
] | Balanced Accuracy Score is NOT equal to Recall Score
### Describe the bug
By definition balanced accuracy should be equal to recall averaged over all the classes. Current implementation gives different answers. Please see the example below.
```
import scikit.metrics as skm
y_true = [1,1]
y_pred = [1,2]
... | 26,892 |
https://github.com/scikit-learn/scikit-learn/issues/26892 | [
"Bug",
"New Feature"
] | Balanced Accuracy Score is NOT equal to Recall Score
### Describe the bug
By definition balanced accuracy should be equal to recall averaged over all the classes. Current implementation gives different answers. Please see the example below.
```
import scikit.metrics as skm
y_true = [1,1]
y_pred = [1,2]
... | 26,892 |
https://github.com/scikit-learn/scikit-learn/issues/26892 | [
"Bug",
"New Feature"
] | Balanced Accuracy Score is NOT equal to Recall Score
### Describe the bug
By definition balanced accuracy should be equal to recall averaged over all the classes. Current implementation gives different answers. Please see the example below.
```
import scikit.metrics as skm
y_true = [1,1]
y_pred = [1,2]
... | 26,892 |
https://github.com/scikit-learn/scikit-learn/issues/26892 | [
"Bug",
"New Feature"
] | Balanced Accuracy Score is NOT equal to Recall Score
### Describe the bug
By definition balanced accuracy should be equal to recall averaged over all the classes. Current implementation gives different answers. Please see the example below.
```
import scikit.metrics as skm
y_true = [1,1]
y_pred = [1,2]
... | 26,892 |
https://github.com/scikit-learn/scikit-learn/issues/26891 | [
"Documentation"
] | Putting it all together Pipelining is not working ( missing dependencies and plot )
### Describe the issue linked to the documentation
From https://scikit-learn.org/stable/tutorial/statistical_inference/putting_together.html#pipelining it is missing
```
from sklearn import datasets
import numpy as np
import matpl... | 26,891 |
https://github.com/scikit-learn/scikit-learn/issues/26891 | [
"Documentation"
] | Putting it all together Pipelining is not working ( missing dependencies and plot )
### Describe the issue linked to the documentation
From https://scikit-learn.org/stable/tutorial/statistical_inference/putting_together.html#pipelining it is missing
```
from sklearn import datasets
import numpy as np
import matpl... | 26,891 |
https://github.com/scikit-learn/scikit-learn/issues/26891 | [
"Documentation"
] | Putting it all together Pipelining is not working ( missing dependencies and plot )
### Describe the issue linked to the documentation
From https://scikit-learn.org/stable/tutorial/statistical_inference/putting_together.html#pipelining it is missing
```
from sklearn import datasets
import numpy as np
import matpl... | 26,891 |
https://github.com/scikit-learn/scikit-learn/issues/26891 | [
"Documentation"
] | Putting it all together Pipelining is not working ( missing dependencies and plot )
### Describe the issue linked to the documentation
From https://scikit-learn.org/stable/tutorial/statistical_inference/putting_together.html#pipelining it is missing
```
from sklearn import datasets
import numpy as np
import matpl... | 26,891 |
https://github.com/scikit-learn/scikit-learn/issues/26891 | [
"Documentation"
] | Putting it all together Pipelining is not working ( missing dependencies and plot )
### Describe the issue linked to the documentation
From https://scikit-learn.org/stable/tutorial/statistical_inference/putting_together.html#pipelining it is missing
```
from sklearn import datasets
import numpy as np
import matpl... | 26,891 |
https://github.com/scikit-learn/scikit-learn/issues/26891 | [
"Documentation"
] | Putting it all together Pipelining is not working ( missing dependencies and plot )
### Describe the issue linked to the documentation
From https://scikit-learn.org/stable/tutorial/statistical_inference/putting_together.html#pipelining it is missing
```
from sklearn import datasets
import numpy as np
import matpl... | 26,891 |
https://github.com/scikit-learn/scikit-learn/issues/26891 | [
"Documentation"
] | Putting it all together Pipelining is not working ( missing dependencies and plot )
### Describe the issue linked to the documentation
From https://scikit-learn.org/stable/tutorial/statistical_inference/putting_together.html#pipelining it is missing
```
from sklearn import datasets
import numpy as np
import matpl... | 26,891 |
https://github.com/scikit-learn/scikit-learn/issues/26890 | [
"Bug",
"module:preprocessing"
] | Handling `pd.NA` in encoders
It seems that we don't handle it properly `pd.NA` in the encoder and thus differently than `np.nan`.
`pd.NA` will raise an error as in the following reproducible:
```python
df = pd.DataFrame({"col_1": ["A", "B", pd.NA]})
OneHotEncoder(sparse_output=False).fit_transform(df)
```
or... | 26,890 |
https://github.com/scikit-learn/scikit-learn/issues/26890 | [
"Bug",
"module:preprocessing"
] | Handling `pd.NA` in encoders
It seems that we don't handle it properly `pd.NA` in the encoder and thus differently than `np.nan`.
`pd.NA` will raise an error as in the following reproducible:
```python
df = pd.DataFrame({"col_1": ["A", "B", pd.NA]})
OneHotEncoder(sparse_output=False).fit_transform(df)
```
or... | 26,890 |
https://github.com/scikit-learn/scikit-learn/issues/26890 | [
"Bug",
"module:preprocessing"
] | Handling `pd.NA` in encoders
It seems that we don't handle it properly `pd.NA` in the encoder and thus differently than `np.nan`.
`pd.NA` will raise an error as in the following reproducible:
```python
df = pd.DataFrame({"col_1": ["A", "B", pd.NA]})
OneHotEncoder(sparse_output=False).fit_transform(df)
```
or... | 26,890 |
https://github.com/scikit-learn/scikit-learn/issues/26890 | [
"Bug",
"module:preprocessing"
] | Handling `pd.NA` in encoders
It seems that we don't handle it properly `pd.NA` in the encoder and thus differently than `np.nan`.
`pd.NA` will raise an error as in the following reproducible:
```python
df = pd.DataFrame({"col_1": ["A", "B", pd.NA]})
OneHotEncoder(sparse_output=False).fit_transform(df)
```
or... | 26,890 |
https://github.com/scikit-learn/scikit-learn/issues/26887 | [
"Bug",
"module:tree",
"Needs Reproducible Code",
"Needs Investigation"
] | infinity in split nodes
### Describe the bug
I've created a simple model with decision trees. However, when I used the "export_text" function, I noticed that there are "infinity" values in the split nodes. I... | 26,887 |
https://github.com/scikit-learn/scikit-learn/issues/26887 | [
"Bug",
"module:tree",
"Needs Reproducible Code",
"Needs Investigation"
] | infinity in split nodes
### Describe the bug
I've created a simple model with decision trees. However, when I used the "export_text" function, I noticed that there are "infinity" values in the split nodes. I... | 26,887 |
https://github.com/scikit-learn/scikit-learn/issues/26887 | [
"Bug",
"module:tree",
"Needs Reproducible Code",
"Needs Investigation"
] | infinity in split nodes
### Describe the bug
I've created a simple model with decision trees. However, when I used the "export_text" function, I noticed that there are "infinity" values in the split nodes. I... | 26,887 |
https://github.com/scikit-learn/scikit-learn/issues/26887 | [
"Bug",
"module:tree",
"Needs Reproducible Code",
"Needs Investigation"
] | infinity in split nodes
### Describe the bug
I've created a simple model with decision trees. However, when I used the "export_text" function, I noticed that there are "infinity" values in the split nodes. I... | 26,887 |
https://github.com/scikit-learn/scikit-learn/issues/26885 | [
"Bug",
"High Priority"
] | HalvingRandomSearchCV does not support param_distribution as a list
### Describe the bug
Before scikit-learn version 1.3.0 (e.g. 1.2.0) HalvingRandomSearchCV could be used with a `list[dict]` as the input for param_distribution (similar to RandomizedSearchCV).
The type hint in the documentation states that only `... | 26,885 |
https://github.com/scikit-learn/scikit-learn/issues/26885 | [
"Bug",
"High Priority"
] | HalvingRandomSearchCV does not support param_distribution as a list
### Describe the bug
Before scikit-learn version 1.3.0 (e.g. 1.2.0) HalvingRandomSearchCV could be used with a `list[dict]` as the input for param_distribution (similar to RandomizedSearchCV).
The type hint in the documentation states that only `... | 26,885 |
https://github.com/scikit-learn/scikit-learn/issues/26885 | [
"Bug",
"High Priority"
] | HalvingRandomSearchCV does not support param_distribution as a list
### Describe the bug
Before scikit-learn version 1.3.0 (e.g. 1.2.0) HalvingRandomSearchCV could be used with a `list[dict]` as the input for param_distribution (similar to RandomizedSearchCV).
The type hint in the documentation states that only `... | 26,885 |
https://github.com/scikit-learn/scikit-learn/issues/26885 | [
"Bug",
"High Priority"
] | HalvingRandomSearchCV does not support param_distribution as a list
### Describe the bug
Before scikit-learn version 1.3.0 (e.g. 1.2.0) HalvingRandomSearchCV could be used with a `list[dict]` as the input for param_distribution (similar to RandomizedSearchCV).
The type hint in the documentation states that only `... | 26,885 |
https://github.com/scikit-learn/scikit-learn/issues/26885 | [
"Bug",
"High Priority"
] | HalvingRandomSearchCV does not support param_distribution as a list
### Describe the bug
Before scikit-learn version 1.3.0 (e.g. 1.2.0) HalvingRandomSearchCV could be used with a `list[dict]` as the input for param_distribution (similar to RandomizedSearchCV).
The type hint in the documentation states that only `... | 26,885 |
https://github.com/scikit-learn/scikit-learn/issues/26885 | [
"Bug",
"High Priority"
] | HalvingRandomSearchCV does not support param_distribution as a list
### Describe the bug
Before scikit-learn version 1.3.0 (e.g. 1.2.0) HalvingRandomSearchCV could be used with a `list[dict]` as the input for param_distribution (similar to RandomizedSearchCV).
The type hint in the documentation states that only `... | 26,885 |
https://github.com/scikit-learn/scikit-learn/issues/26885 | [
"Bug",
"High Priority"
] | HalvingRandomSearchCV does not support param_distribution as a list
### Describe the bug
Before scikit-learn version 1.3.0 (e.g. 1.2.0) HalvingRandomSearchCV could be used with a `list[dict]` as the input for param_distribution (similar to RandomizedSearchCV).
The type hint in the documentation states that only `... | 26,885 |
https://github.com/scikit-learn/scikit-learn/issues/26885 | [
"Bug",
"High Priority"
] | HalvingRandomSearchCV does not support param_distribution as a list
### Describe the bug
Before scikit-learn version 1.3.0 (e.g. 1.2.0) HalvingRandomSearchCV could be used with a `list[dict]` as the input for param_distribution (similar to RandomizedSearchCV).
The type hint in the documentation states that only `... | 26,885 |
https://github.com/scikit-learn/scikit-learn/issues/26880 | [
"New Feature"
] | Add sample weighting to V Measure Score
### Describe the workflow you want to enable
Many evaluation metrics in sklearn have the ability to weight samples by some measure of importance (usually included as a `sample_weight`). This is also important to do when evaluating clustering. In particular, the `v_measure_score... | 26,880 |
https://github.com/scikit-learn/scikit-learn/issues/26880 | [
"New Feature"
] | Add sample weighting to V Measure Score
### Describe the workflow you want to enable
Many evaluation metrics in sklearn have the ability to weight samples by some measure of importance (usually included as a `sample_weight`). This is also important to do when evaluating clustering. In particular, the `v_measure_score... | 26,880 |
https://github.com/scikit-learn/scikit-learn/issues/26880 | [
"New Feature"
] | Add sample weighting to V Measure Score
### Describe the workflow you want to enable
Many evaluation metrics in sklearn have the ability to weight samples by some measure of importance (usually included as a `sample_weight`). This is also important to do when evaluating clustering. In particular, the `v_measure_score... | 26,880 |
https://github.com/scikit-learn/scikit-learn/issues/26879 | [
"Build / CI"
] | Cirrus CI usage limits in the future
In a recent [CirrusCI annoucment](https://cirrus-ci.org/blog/2023/07/17/limiting-free-usage-of-cirrus-ci/) they are limited free usage to 40 compute credits. For reference, we used:
- 214 credits in 05/2023
- 355 credits in 06/2023 (Release month, so there was more wheel buildi... | 26,879 |
https://github.com/scikit-learn/scikit-learn/issues/26879 | [
"Build / CI"
] | Cirrus CI usage limits in the future
In a recent [CirrusCI annoucment](https://cirrus-ci.org/blog/2023/07/17/limiting-free-usage-of-cirrus-ci/) they are limited free usage to 40 compute credits. For reference, we used:
- 214 credits in 05/2023
- 355 credits in 06/2023 (Release month, so there was more wheel buildi... | 26,879 |
https://github.com/scikit-learn/scikit-learn/issues/26878 | [
"New Feature",
"Needs Triage"
] | It would be nice if TargetEncoder could apply itself to a subset of columns which it has encoded.
### Describe the workflow you want to enable
Once a TargetEncoder has been fitted, when you go to transform another data set (e.g., in a production job after the models have been trained), the TargetEncoder.transform(X... | 26,878 |
https://github.com/scikit-learn/scikit-learn/issues/26878 | [
"New Feature",
"Needs Triage"
] | It would be nice if TargetEncoder could apply itself to a subset of columns which it has encoded.
### Describe the workflow you want to enable
Once a TargetEncoder has been fitted, when you go to transform another data set (e.g., in a production job after the models have been trained), the TargetEncoder.transform(X... | 26,878 |
https://github.com/scikit-learn/scikit-learn/issues/26875 | [
"Needs Triage"
] | ⚠️ CI failed on macOS.pylatest_conda_forge_mkl ⚠️
**CI failed on [macOS.pylatest_conda_forge_mkl](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=57215&view=logs&j=97641769-79fb-5590-9088-a30ce9b850b9)** (Jul 21, 2023)
- test_pickle_version_warning_is_issued_when_no_version_info_in_pickle
COMME... | 26,875 |
https://github.com/scikit-learn/scikit-learn/issues/26875 | [
"Needs Triage"
] | ⚠️ CI failed on macOS.pylatest_conda_forge_mkl ⚠️
**CI failed on [macOS.pylatest_conda_forge_mkl](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=57215&view=logs&j=97641769-79fb-5590-9088-a30ce9b850b9)** (Jul 21, 2023)
- test_pickle_version_warning_is_issued_when_no_version_info_in_pickle
COMME... | 26,875 |
https://github.com/scikit-learn/scikit-learn/issues/26875 | [
"Needs Triage"
] | ⚠️ CI failed on macOS.pylatest_conda_forge_mkl ⚠️
**CI failed on [macOS.pylatest_conda_forge_mkl](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=57215&view=logs&j=97641769-79fb-5590-9088-a30ce9b850b9)** (Jul 21, 2023)
- test_pickle_version_warning_is_issued_when_no_version_info_in_pickle
COMME... | 26,875 |
https://github.com/scikit-learn/scikit-learn/issues/26875 | [
"Needs Triage"
] | ⚠️ CI failed on macOS.pylatest_conda_forge_mkl ⚠️
**CI failed on [macOS.pylatest_conda_forge_mkl](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=57215&view=logs&j=97641769-79fb-5590-9088-a30ce9b850b9)** (Jul 21, 2023)
- test_pickle_version_warning_is_issued_when_no_version_info_in_pickle
COMME... | 26,875 |
https://github.com/scikit-learn/scikit-learn/issues/26873 | [
"Bug",
"Needs Triage"
] | Nearest neighbor return structure takes significantly longer to garbage collect
The way output is structured in nearest neighbor classes (e.g. KDTree) leads to an order of magnitude greater time required to garbage collect the output, compared to actually generating it. For example:
```python
from sklearn.neighbor... | 26,873 |
https://github.com/scikit-learn/scikit-learn/issues/26873 | [
"Bug",
"Needs Triage"
] | Nearest neighbor return structure takes significantly longer to garbage collect
The way output is structured in nearest neighbor classes (e.g. KDTree) leads to an order of magnitude greater time required to garbage collect the output, compared to actually generating it. For example:
```python
from sklearn.neighbor... | 26,873 |
https://github.com/scikit-learn/scikit-learn/issues/26873 | [
"Bug",
"Needs Triage"
] | Nearest neighbor return structure takes significantly longer to garbage collect
The way output is structured in nearest neighbor classes (e.g. KDTree) leads to an order of magnitude greater time required to garbage collect the output, compared to actually generating it. For example:
```python
from sklearn.neighbor... | 26,873 |
https://github.com/scikit-learn/scikit-learn/issues/26873 | [
"Bug",
"Needs Triage"
] | Nearest neighbor return structure takes significantly longer to garbage collect
The way output is structured in nearest neighbor classes (e.g. KDTree) leads to an order of magnitude greater time required to garbage collect the output, compared to actually generating it. For example:
```python
from sklearn.neighbor... | 26,873 |
https://github.com/scikit-learn/scikit-learn/issues/26873 | [
"Bug",
"Needs Triage"
] | Nearest neighbor return structure takes significantly longer to garbage collect
The way output is structured in nearest neighbor classes (e.g. KDTree) leads to an order of magnitude greater time required to garbage collect the output, compared to actually generating it. For example:
```python
from sklearn.neighbor... | 26,873 |
https://github.com/scikit-learn/scikit-learn/issues/26870 | [
"Needs Triage"
] | Outline for the main encoding example
(migrated from #657)
As discussed with Gaël, here is a proposed outline for the main encoding example. Please submit your suggestions!
- Start with a dirty dataset, probably employee_salaries
- First, use the TableVectorizer, just to say "with little trouble, it works ootb"... | 26,870 |
https://github.com/scikit-learn/scikit-learn/issues/26869 | [
"RFC"
] | RFC Cap uppper versions of dependencies
We've been seeing quite a few issues where people try to install scikit-learn in an environment for which there are no wheels and therefore pip trying to build the package from the source distribution, but failing.
Making scikit-learn work with new versions of dependencies, i... | 26,869 |
https://github.com/scikit-learn/scikit-learn/issues/26869 | [
"RFC"
] | RFC Cap uppper versions of dependencies
We've been seeing quite a few issues where people try to install scikit-learn in an environment for which there are no wheels and therefore pip trying to build the package from the source distribution, but failing.
Making scikit-learn work with new versions of dependencies, i... | 26,869 |
https://github.com/scikit-learn/scikit-learn/issues/26869 | [
"RFC"
] | RFC Cap uppper versions of dependencies
We've been seeing quite a few issues where people try to install scikit-learn in an environment for which there are no wheels and therefore pip trying to build the package from the source distribution, but failing.
Making scikit-learn work with new versions of dependencies, i... | 26,869 |
https://github.com/scikit-learn/scikit-learn/issues/26869 | [
"RFC"
] | RFC Cap uppper versions of dependencies
We've been seeing quite a few issues where people try to install scikit-learn in an environment for which there are no wheels and therefore pip trying to build the package from the source distribution, but failing.
Making scikit-learn work with new versions of dependencies, i... | 26,869 |
https://github.com/scikit-learn/scikit-learn/issues/26869 | [
"RFC"
] | RFC Cap uppper versions of dependencies
We've been seeing quite a few issues where people try to install scikit-learn in an environment for which there are no wheels and therefore pip trying to build the package from the source distribution, but failing.
Making scikit-learn work with new versions of dependencies, i... | 26,869 |
https://github.com/scikit-learn/scikit-learn/issues/26869 | [
"RFC"
] | RFC Cap uppper versions of dependencies
We've been seeing quite a few issues where people try to install scikit-learn in an environment for which there are no wheels and therefore pip trying to build the package from the source distribution, but failing.
Making scikit-learn work with new versions of dependencies, i... | 26,869 |
https://github.com/scikit-learn/scikit-learn/issues/26869 | [
"RFC"
] | RFC Cap uppper versions of dependencies
We've been seeing quite a few issues where people try to install scikit-learn in an environment for which there are no wheels and therefore pip trying to build the package from the source distribution, but failing.
Making scikit-learn work with new versions of dependencies, i... | 26,869 |
https://github.com/scikit-learn/scikit-learn/issues/26869 | [
"RFC"
] | RFC Cap uppper versions of dependencies
We've been seeing quite a few issues where people try to install scikit-learn in an environment for which there are no wheels and therefore pip trying to build the package from the source distribution, but failing.
Making scikit-learn work with new versions of dependencies, i... | 26,869 |
https://github.com/scikit-learn/scikit-learn/issues/26869 | [
"RFC"
] | RFC Cap uppper versions of dependencies
We've been seeing quite a few issues where people try to install scikit-learn in an environment for which there are no wheels and therefore pip trying to build the package from the source distribution, but failing.
Making scikit-learn work with new versions of dependencies, i... | 26,869 |
https://github.com/scikit-learn/scikit-learn/issues/26869 | [
"RFC"
] | RFC Cap uppper versions of dependencies
We've been seeing quite a few issues where people try to install scikit-learn in an environment for which there are no wheels and therefore pip trying to build the package from the source distribution, but failing.
Making scikit-learn work with new versions of dependencies, i... | 26,869 |
https://github.com/scikit-learn/scikit-learn/issues/26869 | [
"RFC"
] | RFC Cap uppper versions of dependencies
We've been seeing quite a few issues where people try to install scikit-learn in an environment for which there are no wheels and therefore pip trying to build the package from the source distribution, but failing.
Making scikit-learn work with new versions of dependencies, i... | 26,869 |
https://github.com/scikit-learn/scikit-learn/issues/26869 | [
"RFC"
] | RFC Cap uppper versions of dependencies
We've been seeing quite a few issues where people try to install scikit-learn in an environment for which there are no wheels and therefore pip trying to build the package from the source distribution, but failing.
Making scikit-learn work with new versions of dependencies, i... | 26,869 |
https://github.com/scikit-learn/scikit-learn/issues/26869 | [
"RFC"
] | RFC Cap uppper versions of dependencies
We've been seeing quite a few issues where people try to install scikit-learn in an environment for which there are no wheels and therefore pip trying to build the package from the source distribution, but failing.
Making scikit-learn work with new versions of dependencies, i... | 26,869 |
https://github.com/scikit-learn/scikit-learn/issues/26869 | [
"RFC"
] | RFC Cap uppper versions of dependencies
We've been seeing quite a few issues where people try to install scikit-learn in an environment for which there are no wheels and therefore pip trying to build the package from the source distribution, but failing.
Making scikit-learn work with new versions of dependencies, i... | 26,869 |
https://github.com/scikit-learn/scikit-learn/issues/26869 | [
"RFC"
] | RFC Cap uppper versions of dependencies
We've been seeing quite a few issues where people try to install scikit-learn in an environment for which there are no wheels and therefore pip trying to build the package from the source distribution, but failing.
Making scikit-learn work with new versions of dependencies, i... | 26,869 |
https://github.com/scikit-learn/scikit-learn/issues/26869 | [
"RFC"
] | RFC Cap uppper versions of dependencies
We've been seeing quite a few issues where people try to install scikit-learn in an environment for which there are no wheels and therefore pip trying to build the package from the source distribution, but failing.
Making scikit-learn work with new versions of dependencies, i... | 26,869 |
https://github.com/scikit-learn/scikit-learn/issues/26868 | [
"Documentation"
] | DOC the pipeline user guide should include same estimators to demonstrate pipeline construction
### Describe the issue linked to the documentation
In the [user guide for pipelines](https://scikit-learn.org/dev/modules/compose.html) the demonstration of the construction of a pipeline includes two examples:
1. Dire... | 26,868 |
https://github.com/scikit-learn/scikit-learn/issues/26868 | [
"Documentation"
] | DOC the pipeline user guide should include same estimators to demonstrate pipeline construction
### Describe the issue linked to the documentation
In the [user guide for pipelines](https://scikit-learn.org/dev/modules/compose.html) the demonstration of the construction of a pipeline includes two examples:
1. Dire... | 26,868 |
https://github.com/scikit-learn/scikit-learn/issues/26868 | [
"Documentation"
] | DOC the pipeline user guide should include same estimators to demonstrate pipeline construction
### Describe the issue linked to the documentation
In the [user guide for pipelines](https://scikit-learn.org/dev/modules/compose.html) the demonstration of the construction of a pipeline includes two examples:
1. Dire... | 26,868 |
https://github.com/scikit-learn/scikit-learn/issues/26868 | [
"Documentation"
] | DOC the pipeline user guide should include same estimators to demonstrate pipeline construction
### Describe the issue linked to the documentation
In the [user guide for pipelines](https://scikit-learn.org/dev/modules/compose.html) the demonstration of the construction of a pipeline includes two examples:
1. Dire... | 26,868 |
https://github.com/scikit-learn/scikit-learn/issues/26868 | [
"Documentation"
] | DOC the pipeline user guide should include same estimators to demonstrate pipeline construction
### Describe the issue linked to the documentation
In the [user guide for pipelines](https://scikit-learn.org/dev/modules/compose.html) the demonstration of the construction of a pipeline includes two examples:
1. Dire... | 26,868 |
https://github.com/scikit-learn/scikit-learn/issues/26868 | [
"Documentation"
] | DOC the pipeline user guide should include same estimators to demonstrate pipeline construction
### Describe the issue linked to the documentation
In the [user guide for pipelines](https://scikit-learn.org/dev/modules/compose.html) the demonstration of the construction of a pipeline includes two examples:
1. Dire... | 26,868 |
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