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/31098 | [
"Bug",
"Build / CI"
] | Failing CI for check_sample_weight_equivalence_on_dense_data with LinearRegerssion on debian_32bit
Here is the last scheduled run (from 1 day ago) that passed:
https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=75127&view=logs&j=86340c1f-3d76-5202-0821-7817a0f52092&t=a73eff7b-829e-5a65-7648-23ff8e... | 31,098 |
https://github.com/scikit-learn/scikit-learn/issues/31098 | [
"Bug",
"Build / CI"
] | Failing CI for check_sample_weight_equivalence_on_dense_data with LinearRegerssion on debian_32bit
Here is the last scheduled run (from 1 day ago) that passed:
https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=75127&view=logs&j=86340c1f-3d76-5202-0821-7817a0f52092&t=a73eff7b-829e-5a65-7648-23ff8e... | 31,098 |
https://github.com/scikit-learn/scikit-learn/issues/31098 | [
"Bug",
"Build / CI"
] | Failing CI for check_sample_weight_equivalence_on_dense_data with LinearRegerssion on debian_32bit
Here is the last scheduled run (from 1 day ago) that passed:
https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=75127&view=logs&j=86340c1f-3d76-5202-0821-7817a0f52092&t=a73eff7b-829e-5a65-7648-23ff8e... | 31,098 |
https://github.com/scikit-learn/scikit-learn/issues/31098 | [
"Bug",
"Build / CI"
] | Failing CI for check_sample_weight_equivalence_on_dense_data with LinearRegerssion on debian_32bit
Here is the last scheduled run (from 1 day ago) that passed:
https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=75127&view=logs&j=86340c1f-3d76-5202-0821-7817a0f52092&t=a73eff7b-829e-5a65-7648-23ff8e... | 31,098 |
https://github.com/scikit-learn/scikit-learn/issues/31098 | [
"Bug",
"Build / CI"
] | Failing CI for check_sample_weight_equivalence_on_dense_data with LinearRegerssion on debian_32bit
Here is the last scheduled run (from 1 day ago) that passed:
https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=75127&view=logs&j=86340c1f-3d76-5202-0821-7817a0f52092&t=a73eff7b-829e-5a65-7648-23ff8e... | 31,098 |
https://github.com/scikit-learn/scikit-learn/issues/31098 | [
"Bug",
"Build / CI"
] | Failing CI for check_sample_weight_equivalence_on_dense_data with LinearRegerssion on debian_32bit
Here is the last scheduled run (from 1 day ago) that passed:
https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=75127&view=logs&j=86340c1f-3d76-5202-0821-7817a0f52092&t=a73eff7b-829e-5a65-7648-23ff8e... | 31,098 |
https://github.com/scikit-learn/scikit-learn/issues/31098 | [
"Bug",
"Build / CI"
] | Failing CI for check_sample_weight_equivalence_on_dense_data with LinearRegerssion on debian_32bit
Here is the last scheduled run (from 1 day ago) that passed:
https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=75127&view=logs&j=86340c1f-3d76-5202-0821-7817a0f52092&t=a73eff7b-829e-5a65-7648-23ff8e... | 31,098 |
https://github.com/scikit-learn/scikit-learn/issues/31098 | [
"Bug",
"Build / CI"
] | Failing CI for check_sample_weight_equivalence_on_dense_data with LinearRegerssion on debian_32bit
Here is the last scheduled run (from 1 day ago) that passed:
https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=75127&view=logs&j=86340c1f-3d76-5202-0821-7817a0f52092&t=a73eff7b-829e-5a65-7648-23ff8e... | 31,098 |
https://github.com/scikit-learn/scikit-learn/issues/31098 | [
"Bug",
"Build / CI"
] | Failing CI for check_sample_weight_equivalence_on_dense_data with LinearRegerssion on debian_32bit
Here is the last scheduled run (from 1 day ago) that passed:
https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=75127&view=logs&j=86340c1f-3d76-5202-0821-7817a0f52092&t=a73eff7b-829e-5a65-7648-23ff8e... | 31,098 |
https://github.com/scikit-learn/scikit-learn/issues/31098 | [
"Bug",
"Build / CI"
] | Failing CI for check_sample_weight_equivalence_on_dense_data with LinearRegerssion on debian_32bit
Here is the last scheduled run (from 1 day ago) that passed:
https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=75127&view=logs&j=86340c1f-3d76-5202-0821-7817a0f52092&t=a73eff7b-829e-5a65-7648-23ff8e... | 31,098 |
https://github.com/scikit-learn/scikit-learn/issues/31098 | [
"Bug",
"Build / CI"
] | Failing CI for check_sample_weight_equivalence_on_dense_data with LinearRegerssion on debian_32bit
Here is the last scheduled run (from 1 day ago) that passed:
https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=75127&view=logs&j=86340c1f-3d76-5202-0821-7817a0f52092&t=a73eff7b-829e-5a65-7648-23ff8e... | 31,098 |
https://github.com/scikit-learn/scikit-learn/issues/31098 | [
"Bug",
"Build / CI"
] | Failing CI for check_sample_weight_equivalence_on_dense_data with LinearRegerssion on debian_32bit
Here is the last scheduled run (from 1 day ago) that passed:
https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=75127&view=logs&j=86340c1f-3d76-5202-0821-7817a0f52092&t=a73eff7b-829e-5a65-7648-23ff8e... | 31,098 |
https://github.com/scikit-learn/scikit-learn/issues/31098 | [
"Bug",
"Build / CI"
] | Failing CI for check_sample_weight_equivalence_on_dense_data with LinearRegerssion on debian_32bit
Here is the last scheduled run (from 1 day ago) that passed:
https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=75127&view=logs&j=86340c1f-3d76-5202-0821-7817a0f52092&t=a73eff7b-829e-5a65-7648-23ff8e... | 31,098 |
https://github.com/scikit-learn/scikit-learn/issues/31098 | [
"Bug",
"Build / CI"
] | Failing CI for check_sample_weight_equivalence_on_dense_data with LinearRegerssion on debian_32bit
Here is the last scheduled run (from 1 day ago) that passed:
https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=75127&view=logs&j=86340c1f-3d76-5202-0821-7817a0f52092&t=a73eff7b-829e-5a65-7648-23ff8e... | 31,098 |
https://github.com/scikit-learn/scikit-learn/issues/31098 | [
"Bug",
"Build / CI"
] | Failing CI for check_sample_weight_equivalence_on_dense_data with LinearRegerssion on debian_32bit
Here is the last scheduled run (from 1 day ago) that passed:
https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=75127&view=logs&j=86340c1f-3d76-5202-0821-7817a0f52092&t=a73eff7b-829e-5a65-7648-23ff8e... | 31,098 |
https://github.com/scikit-learn/scikit-learn/issues/31098 | [
"Bug",
"Build / CI"
] | Failing CI for check_sample_weight_equivalence_on_dense_data with LinearRegerssion on debian_32bit
Here is the last scheduled run (from 1 day ago) that passed:
https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=75127&view=logs&j=86340c1f-3d76-5202-0821-7817a0f52092&t=a73eff7b-829e-5a65-7648-23ff8e... | 31,098 |
https://github.com/scikit-learn/scikit-learn/issues/31098 | [
"Bug",
"Build / CI"
] | Failing CI for check_sample_weight_equivalence_on_dense_data with LinearRegerssion on debian_32bit
Here is the last scheduled run (from 1 day ago) that passed:
https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=75127&view=logs&j=86340c1f-3d76-5202-0821-7817a0f52092&t=a73eff7b-829e-5a65-7648-23ff8e... | 31,098 |
https://github.com/scikit-learn/scikit-learn/issues/31098 | [
"Bug",
"Build / CI"
] | Failing CI for check_sample_weight_equivalence_on_dense_data with LinearRegerssion on debian_32bit
Here is the last scheduled run (from 1 day ago) that passed:
https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=75127&view=logs&j=86340c1f-3d76-5202-0821-7817a0f52092&t=a73eff7b-829e-5a65-7648-23ff8e... | 31,098 |
https://github.com/scikit-learn/scikit-learn/issues/31093 | [
"Bug"
] | The covariance matrix is incorrect in BayesianRidge
### Describe the bug
The posterior covariance matrix in `BayesianRidge`, attribute `sigma_`, is incorrect when `n_features > n_samples`. This is because the posterior covariance requires the full svd, while the current code uses the reduced svd.
### Steps/Code to ... | 31,093 |
https://github.com/scikit-learn/scikit-learn/issues/31091 | [
"RFC"
] | RFC set up Codespaces to ease contributor experience especially during sprints?
IMO this could be useful as fall-back during sprints, in particular for pesky company Windows laptops, where I (and others for example @adrinjalali and @glemaitre) have been guilty to debug the Windows situation rather than focussing on mo... | 31,091 |
https://github.com/scikit-learn/scikit-learn/issues/31091 | [
"RFC"
] | RFC set up Codespaces to ease contributor experience especially during sprints?
IMO this could be useful as fall-back during sprints, in particular for pesky company Windows laptops, where I (and others for example @adrinjalali and @glemaitre) have been guilty to debug the Windows situation rather than focussing on mo... | 31,091 |
https://github.com/scikit-learn/scikit-learn/issues/31091 | [
"RFC"
] | RFC set up Codespaces to ease contributor experience especially during sprints?
IMO this could be useful as fall-back during sprints, in particular for pesky company Windows laptops, where I (and others for example @adrinjalali and @glemaitre) have been guilty to debug the Windows situation rather than focussing on mo... | 31,091 |
https://github.com/scikit-learn/scikit-learn/issues/31091 | [
"RFC"
] | RFC set up Codespaces to ease contributor experience especially during sprints?
IMO this could be useful as fall-back during sprints, in particular for pesky company Windows laptops, where I (and others for example @adrinjalali and @glemaitre) have been guilty to debug the Windows situation rather than focussing on mo... | 31,091 |
https://github.com/scikit-learn/scikit-learn/issues/31091 | [
"RFC"
] | RFC set up Codespaces to ease contributor experience especially during sprints?
IMO this could be useful as fall-back during sprints, in particular for pesky company Windows laptops, where I (and others for example @adrinjalali and @glemaitre) have been guilty to debug the Windows situation rather than focussing on mo... | 31,091 |
https://github.com/scikit-learn/scikit-learn/issues/31091 | [
"RFC"
] | RFC set up Codespaces to ease contributor experience especially during sprints?
IMO this could be useful as fall-back during sprints, in particular for pesky company Windows laptops, where I (and others for example @adrinjalali and @glemaitre) have been guilty to debug the Windows situation rather than focussing on mo... | 31,091 |
https://github.com/scikit-learn/scikit-learn/issues/31091 | [
"RFC"
] | RFC set up Codespaces to ease contributor experience especially during sprints?
IMO this could be useful as fall-back during sprints, in particular for pesky company Windows laptops, where I (and others for example @adrinjalali and @glemaitre) have been guilty to debug the Windows situation rather than focussing on mo... | 31,091 |
https://github.com/scikit-learn/scikit-learn/issues/31077 | [
"Bug"
] | Partial dependence broken when categorical_features has an empty list
### Describe the bug
When we pass an empty list to **categorical_features**, **partial_dependence** will raise an error ValueError: Expected **categorical_features** to be an array-like of boolean, integer, or string. Got float64 instead.
### Step... | 31,077 |
https://github.com/scikit-learn/scikit-learn/issues/31077 | [
"Bug"
] | Partial dependence broken when categorical_features has an empty list
### Describe the bug
When we pass an empty list to **categorical_features**, **partial_dependence** will raise an error ValueError: Expected **categorical_features** to be an array-like of boolean, integer, or string. Got float64 instead.
### Step... | 31,077 |
https://github.com/scikit-learn/scikit-learn/issues/31077 | [
"Bug"
] | Partial dependence broken when categorical_features has an empty list
### Describe the bug
When we pass an empty list to **categorical_features**, **partial_dependence** will raise an error ValueError: Expected **categorical_features** to be an array-like of boolean, integer, or string. Got float64 instead.
### Step... | 31,077 |
https://github.com/scikit-learn/scikit-learn/issues/31073 | [
"New Feature",
"Needs Reproducible Code"
] | ValueError: Only sparse matrices with 32-bit integer indices are accepted.
### Describe the workflow you want to enable
The use case that triggers the issue is very simple. I am trying to compute the n-gram features of a tokenized 1M dataset (i.e., from List[str] to List[int]) and then perform clustering on the datas... | 31,073 |
https://github.com/scikit-learn/scikit-learn/issues/31073 | [
"New Feature",
"Needs Reproducible Code"
] | ValueError: Only sparse matrices with 32-bit integer indices are accepted.
### Describe the workflow you want to enable
The use case that triggers the issue is very simple. I am trying to compute the n-gram features of a tokenized 1M dataset (i.e., from List[str] to List[int]) and then perform clustering on the datas... | 31,073 |
https://github.com/scikit-learn/scikit-learn/issues/31073 | [
"New Feature",
"Needs Reproducible Code"
] | ValueError: Only sparse matrices with 32-bit integer indices are accepted.
### Describe the workflow you want to enable
The use case that triggers the issue is very simple. I am trying to compute the n-gram features of a tokenized 1M dataset (i.e., from List[str] to List[int]) and then perform clustering on the datas... | 31,073 |
https://github.com/scikit-learn/scikit-learn/issues/31073 | [
"New Feature",
"Needs Reproducible Code"
] | ValueError: Only sparse matrices with 32-bit integer indices are accepted.
### Describe the workflow you want to enable
The use case that triggers the issue is very simple. I am trying to compute the n-gram features of a tokenized 1M dataset (i.e., from List[str] to List[int]) and then perform clustering on the datas... | 31,073 |
https://github.com/scikit-learn/scikit-learn/issues/31073 | [
"New Feature",
"Needs Reproducible Code"
] | ValueError: Only sparse matrices with 32-bit integer indices are accepted.
### Describe the workflow you want to enable
The use case that triggers the issue is very simple. I am trying to compute the n-gram features of a tokenized 1M dataset (i.e., from List[str] to List[int]) and then perform clustering on the datas... | 31,073 |
https://github.com/scikit-learn/scikit-learn/issues/31073 | [
"New Feature",
"Needs Reproducible Code"
] | ValueError: Only sparse matrices with 32-bit integer indices are accepted.
### Describe the workflow you want to enable
The use case that triggers the issue is very simple. I am trying to compute the n-gram features of a tokenized 1M dataset (i.e., from List[str] to List[int]) and then perform clustering on the datas... | 31,073 |
https://github.com/scikit-learn/scikit-learn/issues/31073 | [
"New Feature",
"Needs Reproducible Code"
] | ValueError: Only sparse matrices with 32-bit integer indices are accepted.
### Describe the workflow you want to enable
The use case that triggers the issue is very simple. I am trying to compute the n-gram features of a tokenized 1M dataset (i.e., from List[str] to List[int]) and then perform clustering on the datas... | 31,073 |
https://github.com/scikit-learn/scikit-learn/issues/31073 | [
"New Feature",
"Needs Reproducible Code"
] | ValueError: Only sparse matrices with 32-bit integer indices are accepted.
### Describe the workflow you want to enable
The use case that triggers the issue is very simple. I am trying to compute the n-gram features of a tokenized 1M dataset (i.e., from List[str] to List[int]) and then perform clustering on the datas... | 31,073 |
https://github.com/scikit-learn/scikit-learn/issues/31059 | [
"Bug",
"Needs Info"
] | "The Python kernel is unresponsive" when fitting a reasonable sized sparse matrix into NearestNeighbors
### Describe the bug
Hi all,
I have a python code that has been running every day for the past years, which uses NearestNeighbors to find best matches.
All of a sudden, in both our TEST and PRD environments, our c... | 31,059 |
https://github.com/scikit-learn/scikit-learn/issues/31059 | [
"Bug",
"Needs Info"
] | "The Python kernel is unresponsive" when fitting a reasonable sized sparse matrix into NearestNeighbors
### Describe the bug
Hi all,
I have a python code that has been running every day for the past years, which uses NearestNeighbors to find best matches.
All of a sudden, in both our TEST and PRD environments, our c... | 31,059 |
https://github.com/scikit-learn/scikit-learn/issues/31059 | [
"Bug",
"Needs Info"
] | "The Python kernel is unresponsive" when fitting a reasonable sized sparse matrix into NearestNeighbors
### Describe the bug
Hi all,
I have a python code that has been running every day for the past years, which uses NearestNeighbors to find best matches.
All of a sudden, in both our TEST and PRD environments, our c... | 31,059 |
https://github.com/scikit-learn/scikit-learn/issues/31059 | [
"Bug",
"Needs Info"
] | "The Python kernel is unresponsive" when fitting a reasonable sized sparse matrix into NearestNeighbors
### Describe the bug
Hi all,
I have a python code that has been running every day for the past years, which uses NearestNeighbors to find best matches.
All of a sudden, in both our TEST and PRD environments, our c... | 31,059 |
https://github.com/scikit-learn/scikit-learn/issues/31059 | [
"Bug",
"Needs Info"
] | "The Python kernel is unresponsive" when fitting a reasonable sized sparse matrix into NearestNeighbors
### Describe the bug
Hi all,
I have a python code that has been running every day for the past years, which uses NearestNeighbors to find best matches.
All of a sudden, in both our TEST and PRD environments, our c... | 31,059 |
https://github.com/scikit-learn/scikit-learn/issues/31059 | [
"Bug",
"Needs Info"
] | "The Python kernel is unresponsive" when fitting a reasonable sized sparse matrix into NearestNeighbors
### Describe the bug
Hi all,
I have a python code that has been running every day for the past years, which uses NearestNeighbors to find best matches.
All of a sudden, in both our TEST and PRD environments, our c... | 31,059 |
https://github.com/scikit-learn/scikit-learn/issues/31059 | [
"Bug",
"Needs Info"
] | "The Python kernel is unresponsive" when fitting a reasonable sized sparse matrix into NearestNeighbors
### Describe the bug
Hi all,
I have a python code that has been running every day for the past years, which uses NearestNeighbors to find best matches.
All of a sudden, in both our TEST and PRD environments, our c... | 31,059 |
https://github.com/scikit-learn/scikit-learn/issues/31052 | [
"Bug",
"Needs Triage"
] | `precision_recall_fscore_support` with `zero_division=np.nan` assigns F1-score as `0` instead of `np.nan`
### Describe the bug
According to docs:
```
zero_division : {"warn", 0.0, 1.0, np.nan}, default="warn"
Sets the value to return when there is a zero division, i.e. when all
predictions and labels... | 31,052 |
https://github.com/scikit-learn/scikit-learn/issues/31052 | [
"Bug",
"Needs Triage"
] | `precision_recall_fscore_support` with `zero_division=np.nan` assigns F1-score as `0` instead of `np.nan`
### Describe the bug
According to docs:
```
zero_division : {"warn", 0.0, 1.0, np.nan}, default="warn"
Sets the value to return when there is a zero division, i.e. when all
predictions and labels... | 31,052 |
https://github.com/scikit-learn/scikit-learn/issues/31051 | [
"Bug"
] | `PandasAdapter` causes crash or misattributed features
### Describe the bug
If all the following hold
- Using ColumnTransformer with the output container set to pandas
- At least one transformer transforms 1D inputs to 2D outputs (like [DictVectorizer](https://scikit-learn.org/stable/modules/generated/sklearn.feature... | 31,051 |
https://github.com/scikit-learn/scikit-learn/issues/31051 | [
"Bug"
] | `PandasAdapter` causes crash or misattributed features
### Describe the bug
If all the following hold
- Using ColumnTransformer with the output container set to pandas
- At least one transformer transforms 1D inputs to 2D outputs (like [DictVectorizer](https://scikit-learn.org/stable/modules/generated/sklearn.feature... | 31,051 |
https://github.com/scikit-learn/scikit-learn/issues/31051 | [
"Bug"
] | `PandasAdapter` causes crash or misattributed features
### Describe the bug
If all the following hold
- Using ColumnTransformer with the output container set to pandas
- At least one transformer transforms 1D inputs to 2D outputs (like [DictVectorizer](https://scikit-learn.org/stable/modules/generated/sklearn.feature... | 31,051 |
https://github.com/scikit-learn/scikit-learn/issues/31051 | [
"Bug"
] | `PandasAdapter` causes crash or misattributed features
### Describe the bug
If all the following hold
- Using ColumnTransformer with the output container set to pandas
- At least one transformer transforms 1D inputs to 2D outputs (like [DictVectorizer](https://scikit-learn.org/stable/modules/generated/sklearn.feature... | 31,051 |
https://github.com/scikit-learn/scikit-learn/issues/31049 | [
"RFC"
] | RFC adopt narwhals for dataframe support
At least as of [SLEP018](https://scikit-learn-enhancement-proposals.readthedocs.io/en/latest/slep018/proposal.html), scikit-learn supports dataframes passed as `X`. In #25896 is a further place of current discussions.
This issue is to discuss whether or not, or in which form, ... | 31,049 |
https://github.com/scikit-learn/scikit-learn/issues/31049 | [
"RFC"
] | RFC adopt narwhals for dataframe support
At least as of [SLEP018](https://scikit-learn-enhancement-proposals.readthedocs.io/en/latest/slep018/proposal.html), scikit-learn supports dataframes passed as `X`. In #25896 is a further place of current discussions.
This issue is to discuss whether or not, or in which form, ... | 31,049 |
https://github.com/scikit-learn/scikit-learn/issues/31049 | [
"RFC"
] | RFC adopt narwhals for dataframe support
At least as of [SLEP018](https://scikit-learn-enhancement-proposals.readthedocs.io/en/latest/slep018/proposal.html), scikit-learn supports dataframes passed as `X`. In #25896 is a further place of current discussions.
This issue is to discuss whether or not, or in which form, ... | 31,049 |
https://github.com/scikit-learn/scikit-learn/issues/31049 | [
"RFC"
] | RFC adopt narwhals for dataframe support
At least as of [SLEP018](https://scikit-learn-enhancement-proposals.readthedocs.io/en/latest/slep018/proposal.html), scikit-learn supports dataframes passed as `X`. In #25896 is a further place of current discussions.
This issue is to discuss whether or not, or in which form, ... | 31,049 |
https://github.com/scikit-learn/scikit-learn/issues/31049 | [
"RFC"
] | RFC adopt narwhals for dataframe support
At least as of [SLEP018](https://scikit-learn-enhancement-proposals.readthedocs.io/en/latest/slep018/proposal.html), scikit-learn supports dataframes passed as `X`. In #25896 is a further place of current discussions.
This issue is to discuss whether or not, or in which form, ... | 31,049 |
https://github.com/scikit-learn/scikit-learn/issues/31049 | [
"RFC"
] | RFC adopt narwhals for dataframe support
At least as of [SLEP018](https://scikit-learn-enhancement-proposals.readthedocs.io/en/latest/slep018/proposal.html), scikit-learn supports dataframes passed as `X`. In #25896 is a further place of current discussions.
This issue is to discuss whether or not, or in which form, ... | 31,049 |
https://github.com/scikit-learn/scikit-learn/issues/31049 | [
"RFC"
] | RFC adopt narwhals for dataframe support
At least as of [SLEP018](https://scikit-learn-enhancement-proposals.readthedocs.io/en/latest/slep018/proposal.html), scikit-learn supports dataframes passed as `X`. In #25896 is a further place of current discussions.
This issue is to discuss whether or not, or in which form, ... | 31,049 |
https://github.com/scikit-learn/scikit-learn/issues/31049 | [
"RFC"
] | RFC adopt narwhals for dataframe support
At least as of [SLEP018](https://scikit-learn-enhancement-proposals.readthedocs.io/en/latest/slep018/proposal.html), scikit-learn supports dataframes passed as `X`. In #25896 is a further place of current discussions.
This issue is to discuss whether or not, or in which form, ... | 31,049 |
https://github.com/scikit-learn/scikit-learn/issues/31049 | [
"RFC"
] | RFC adopt narwhals for dataframe support
At least as of [SLEP018](https://scikit-learn-enhancement-proposals.readthedocs.io/en/latest/slep018/proposal.html), scikit-learn supports dataframes passed as `X`. In #25896 is a further place of current discussions.
This issue is to discuss whether or not, or in which form, ... | 31,049 |
https://github.com/scikit-learn/scikit-learn/issues/31049 | [
"RFC"
] | RFC adopt narwhals for dataframe support
At least as of [SLEP018](https://scikit-learn-enhancement-proposals.readthedocs.io/en/latest/slep018/proposal.html), scikit-learn supports dataframes passed as `X`. In #25896 is a further place of current discussions.
This issue is to discuss whether or not, or in which form, ... | 31,049 |
https://github.com/scikit-learn/scikit-learn/issues/31049 | [
"RFC"
] | RFC adopt narwhals for dataframe support
At least as of [SLEP018](https://scikit-learn-enhancement-proposals.readthedocs.io/en/latest/slep018/proposal.html), scikit-learn supports dataframes passed as `X`. In #25896 is a further place of current discussions.
This issue is to discuss whether or not, or in which form, ... | 31,049 |
https://github.com/scikit-learn/scikit-learn/issues/31049 | [
"RFC"
] | RFC adopt narwhals for dataframe support
At least as of [SLEP018](https://scikit-learn-enhancement-proposals.readthedocs.io/en/latest/slep018/proposal.html), scikit-learn supports dataframes passed as `X`. In #25896 is a further place of current discussions.
This issue is to discuss whether or not, or in which form, ... | 31,049 |
https://github.com/scikit-learn/scikit-learn/issues/31049 | [
"RFC"
] | RFC adopt narwhals for dataframe support
At least as of [SLEP018](https://scikit-learn-enhancement-proposals.readthedocs.io/en/latest/slep018/proposal.html), scikit-learn supports dataframes passed as `X`. In #25896 is a further place of current discussions.
This issue is to discuss whether or not, or in which form, ... | 31,049 |
https://github.com/scikit-learn/scikit-learn/issues/31049 | [
"RFC"
] | RFC adopt narwhals for dataframe support
At least as of [SLEP018](https://scikit-learn-enhancement-proposals.readthedocs.io/en/latest/slep018/proposal.html), scikit-learn supports dataframes passed as `X`. In #25896 is a further place of current discussions.
This issue is to discuss whether or not, or in which form, ... | 31,049 |
https://github.com/scikit-learn/scikit-learn/issues/31049 | [
"RFC"
] | RFC adopt narwhals for dataframe support
At least as of [SLEP018](https://scikit-learn-enhancement-proposals.readthedocs.io/en/latest/slep018/proposal.html), scikit-learn supports dataframes passed as `X`. In #25896 is a further place of current discussions.
This issue is to discuss whether or not, or in which form, ... | 31,049 |
https://github.com/scikit-learn/scikit-learn/issues/31039 | [
"Documentation",
"RFC"
] | RFC Move SLEPs to the main scikit-learn website
## Background
The website for scikit-learn enhancement proposals (SLEP) at https://scikit-learn-enhancement-proposals.readthedocs.io/ is very hard to find if you don't know what you are looking for. A second difficulty is to know which SLEP is (fully) implemented in whi... | 31,039 |
https://github.com/scikit-learn/scikit-learn/issues/31039 | [
"Documentation",
"RFC"
] | RFC Move SLEPs to the main scikit-learn website
## Background
The website for scikit-learn enhancement proposals (SLEP) at https://scikit-learn-enhancement-proposals.readthedocs.io/ is very hard to find if you don't know what you are looking for. A second difficulty is to know which SLEP is (fully) implemented in whi... | 31,039 |
https://github.com/scikit-learn/scikit-learn/issues/31039 | [
"Documentation",
"RFC"
] | RFC Move SLEPs to the main scikit-learn website
## Background
The website for scikit-learn enhancement proposals (SLEP) at https://scikit-learn-enhancement-proposals.readthedocs.io/ is very hard to find if you don't know what you are looking for. A second difficulty is to know which SLEP is (fully) implemented in whi... | 31,039 |
https://github.com/scikit-learn/scikit-learn/issues/31039 | [
"Documentation",
"RFC"
] | RFC Move SLEPs to the main scikit-learn website
## Background
The website for scikit-learn enhancement proposals (SLEP) at https://scikit-learn-enhancement-proposals.readthedocs.io/ is very hard to find if you don't know what you are looking for. A second difficulty is to know which SLEP is (fully) implemented in whi... | 31,039 |
https://github.com/scikit-learn/scikit-learn/issues/31033 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_Runs.pylatest_conda_forge_mkl (last failure: Mar 20, 2025) ⚠️
**CI failed on [Linux_Runs.pylatest_conda_forge_mkl](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=74894&view=logs&j=dde5042c-7464-5d47-9507-31bdd2ee0a3a)** (Mar 20, 2025)
- Test Collection Failure
COMMENT:
##... | 31,033 |
https://github.com/scikit-learn/scikit-learn/issues/31033 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_Runs.pylatest_conda_forge_mkl (last failure: Mar 20, 2025) ⚠️
**CI failed on [Linux_Runs.pylatest_conda_forge_mkl](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=74894&view=logs&j=dde5042c-7464-5d47-9507-31bdd2ee0a3a)** (Mar 20, 2025)
- Test Collection Failure
COMMENT:
Th... | 31,033 |
https://github.com/scikit-learn/scikit-learn/issues/31033 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_Runs.pylatest_conda_forge_mkl (last failure: Mar 20, 2025) ⚠️
**CI failed on [Linux_Runs.pylatest_conda_forge_mkl](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=74894&view=logs&j=dde5042c-7464-5d47-9507-31bdd2ee0a3a)** (Mar 20, 2025)
- Test Collection Failure
COMMENT:
So... | 31,033 |
https://github.com/scikit-learn/scikit-learn/issues/31032 | [
"Bug"
] | `weighted_percentile` should error/warn when all sample weights 0
### Describe the bug
Noticed while working on #29431
### Steps/Code to Reproduce
See the following test:
https://github.com/scikit-learn/scikit-learn/blob/cd0478f42b2c873853e6317e3c4f2793dc149636/sklearn/utils/tests/test_stats.py#L67-L73
##... | 31,032 |
https://github.com/scikit-learn/scikit-learn/issues/31032 | [
"Bug"
] | `weighted_percentile` should error/warn when all sample weights 0
### Describe the bug
Noticed while working on #29431
### Steps/Code to Reproduce
See the following test:
https://github.com/scikit-learn/scikit-learn/blob/cd0478f42b2c873853e6317e3c4f2793dc149636/sklearn/utils/tests/test_stats.py#L67-L73
##... | 31,032 |
https://github.com/scikit-learn/scikit-learn/issues/31032 | [
"Bug"
] | `weighted_percentile` should error/warn when all sample weights 0
### Describe the bug
Noticed while working on #29431
### Steps/Code to Reproduce
See the following test:
https://github.com/scikit-learn/scikit-learn/blob/cd0478f42b2c873853e6317e3c4f2793dc149636/sklearn/utils/tests/test_stats.py#L67-L73
##... | 31,032 |
https://github.com/scikit-learn/scikit-learn/issues/31032 | [
"Bug"
] | `weighted_percentile` should error/warn when all sample weights 0
### Describe the bug
Noticed while working on #29431
### Steps/Code to Reproduce
See the following test:
https://github.com/scikit-learn/scikit-learn/blob/cd0478f42b2c873853e6317e3c4f2793dc149636/sklearn/utils/tests/test_stats.py#L67-L73
##... | 31,032 |
https://github.com/scikit-learn/scikit-learn/issues/31032 | [
"Bug"
] | `weighted_percentile` should error/warn when all sample weights 0
### Describe the bug
Noticed while working on #29431
### Steps/Code to Reproduce
See the following test:
https://github.com/scikit-learn/scikit-learn/blob/cd0478f42b2c873853e6317e3c4f2793dc149636/sklearn/utils/tests/test_stats.py#L67-L73
##... | 31,032 |
https://github.com/scikit-learn/scikit-learn/issues/31032 | [
"Bug"
] | `weighted_percentile` should error/warn when all sample weights 0
### Describe the bug
Noticed while working on #29431
### Steps/Code to Reproduce
See the following test:
https://github.com/scikit-learn/scikit-learn/blob/cd0478f42b2c873853e6317e3c4f2793dc149636/sklearn/utils/tests/test_stats.py#L67-L73
##... | 31,032 |
https://github.com/scikit-learn/scikit-learn/issues/31032 | [
"Bug"
] | `weighted_percentile` should error/warn when all sample weights 0
### Describe the bug
Noticed while working on #29431
### Steps/Code to Reproduce
See the following test:
https://github.com/scikit-learn/scikit-learn/blob/cd0478f42b2c873853e6317e3c4f2793dc149636/sklearn/utils/tests/test_stats.py#L67-L73
##... | 31,032 |
https://github.com/scikit-learn/scikit-learn/issues/31032 | [
"Bug"
] | `weighted_percentile` should error/warn when all sample weights 0
### Describe the bug
Noticed while working on #29431
### Steps/Code to Reproduce
See the following test:
https://github.com/scikit-learn/scikit-learn/blob/cd0478f42b2c873853e6317e3c4f2793dc149636/sklearn/utils/tests/test_stats.py#L67-L73
##... | 31,032 |
https://github.com/scikit-learn/scikit-learn/issues/31032 | [
"Bug"
] | `weighted_percentile` should error/warn when all sample weights 0
### Describe the bug
Noticed while working on #29431
### Steps/Code to Reproduce
See the following test:
https://github.com/scikit-learn/scikit-learn/blob/cd0478f42b2c873853e6317e3c4f2793dc149636/sklearn/utils/tests/test_stats.py#L67-L73
##... | 31,032 |
https://github.com/scikit-learn/scikit-learn/issues/31032 | [
"Bug"
] | `weighted_percentile` should error/warn when all sample weights 0
### Describe the bug
Noticed while working on #29431
### Steps/Code to Reproduce
See the following test:
https://github.com/scikit-learn/scikit-learn/blob/cd0478f42b2c873853e6317e3c4f2793dc149636/sklearn/utils/tests/test_stats.py#L67-L73
##... | 31,032 |
https://github.com/scikit-learn/scikit-learn/issues/31032 | [
"Bug"
] | `weighted_percentile` should error/warn when all sample weights 0
### Describe the bug
Noticed while working on #29431
### Steps/Code to Reproduce
See the following test:
https://github.com/scikit-learn/scikit-learn/blob/cd0478f42b2c873853e6317e3c4f2793dc149636/sklearn/utils/tests/test_stats.py#L67-L73
##... | 31,032 |
https://github.com/scikit-learn/scikit-learn/issues/31030 | [
"Bug",
"help wanted",
"Needs Investigation"
] | DBSCAN always triggers and EfficiencyWarning
### Describe the bug
Calling dbscan always triggers an efficiency warning. There is no apparent way to either call it correctly or disable the warning.
This was originally reported as an issue in SemiBin, which uses DBSCAN under the hood: https://github.com/BigDataBiolog... | 31,030 |
https://github.com/scikit-learn/scikit-learn/issues/31030 | [
"Bug",
"help wanted",
"Needs Investigation"
] | DBSCAN always triggers and EfficiencyWarning
### Describe the bug
Calling dbscan always triggers an efficiency warning. There is no apparent way to either call it correctly or disable the warning.
This was originally reported as an issue in SemiBin, which uses DBSCAN under the hood: https://github.com/BigDataBiolog... | 31,030 |
https://github.com/scikit-learn/scikit-learn/issues/31030 | [
"Bug",
"help wanted",
"Needs Investigation"
] | DBSCAN always triggers and EfficiencyWarning
### Describe the bug
Calling dbscan always triggers an efficiency warning. There is no apparent way to either call it correctly or disable the warning.
This was originally reported as an issue in SemiBin, which uses DBSCAN under the hood: https://github.com/BigDataBiolog... | 31,030 |
https://github.com/scikit-learn/scikit-learn/issues/31030 | [
"Bug",
"help wanted",
"Needs Investigation"
] | DBSCAN always triggers and EfficiencyWarning
### Describe the bug
Calling dbscan always triggers an efficiency warning. There is no apparent way to either call it correctly or disable the warning.
This was originally reported as an issue in SemiBin, which uses DBSCAN under the hood: https://github.com/BigDataBiolog... | 31,030 |
https://github.com/scikit-learn/scikit-learn/issues/31030 | [
"Bug",
"help wanted",
"Needs Investigation"
] | DBSCAN always triggers and EfficiencyWarning
### Describe the bug
Calling dbscan always triggers an efficiency warning. There is no apparent way to either call it correctly or disable the warning.
This was originally reported as an issue in SemiBin, which uses DBSCAN under the hood: https://github.com/BigDataBiolog... | 31,030 |
https://github.com/scikit-learn/scikit-learn/issues/31030 | [
"Bug",
"help wanted",
"Needs Investigation"
] | DBSCAN always triggers and EfficiencyWarning
### Describe the bug
Calling dbscan always triggers an efficiency warning. There is no apparent way to either call it correctly or disable the warning.
This was originally reported as an issue in SemiBin, which uses DBSCAN under the hood: https://github.com/BigDataBiolog... | 31,030 |
https://github.com/scikit-learn/scikit-learn/issues/31030 | [
"Bug",
"help wanted",
"Needs Investigation"
] | DBSCAN always triggers and EfficiencyWarning
### Describe the bug
Calling dbscan always triggers an efficiency warning. There is no apparent way to either call it correctly or disable the warning.
This was originally reported as an issue in SemiBin, which uses DBSCAN under the hood: https://github.com/BigDataBiolog... | 31,030 |
https://github.com/scikit-learn/scikit-learn/issues/31030 | [
"Bug",
"help wanted",
"Needs Investigation"
] | DBSCAN always triggers and EfficiencyWarning
### Describe the bug
Calling dbscan always triggers an efficiency warning. There is no apparent way to either call it correctly or disable the warning.
This was originally reported as an issue in SemiBin, which uses DBSCAN under the hood: https://github.com/BigDataBiolog... | 31,030 |
https://github.com/scikit-learn/scikit-learn/issues/31030 | [
"Bug",
"help wanted",
"Needs Investigation"
] | DBSCAN always triggers and EfficiencyWarning
### Describe the bug
Calling dbscan always triggers an efficiency warning. There is no apparent way to either call it correctly or disable the warning.
This was originally reported as an issue in SemiBin, which uses DBSCAN under the hood: https://github.com/BigDataBiolog... | 31,030 |
https://github.com/scikit-learn/scikit-learn/issues/31030 | [
"Bug",
"help wanted",
"Needs Investigation"
] | DBSCAN always triggers and EfficiencyWarning
### Describe the bug
Calling dbscan always triggers an efficiency warning. There is no apparent way to either call it correctly or disable the warning.
This was originally reported as an issue in SemiBin, which uses DBSCAN under the hood: https://github.com/BigDataBiolog... | 31,030 |
https://github.com/scikit-learn/scikit-learn/issues/31030 | [
"Bug",
"help wanted",
"Needs Investigation"
] | DBSCAN always triggers and EfficiencyWarning
### Describe the bug
Calling dbscan always triggers an efficiency warning. There is no apparent way to either call it correctly or disable the warning.
This was originally reported as an issue in SemiBin, which uses DBSCAN under the hood: https://github.com/BigDataBiolog... | 31,030 |
https://github.com/scikit-learn/scikit-learn/issues/31030 | [
"Bug",
"help wanted",
"Needs Investigation"
] | DBSCAN always triggers and EfficiencyWarning
### Describe the bug
Calling dbscan always triggers an efficiency warning. There is no apparent way to either call it correctly or disable the warning.
This was originally reported as an issue in SemiBin, which uses DBSCAN under the hood: https://github.com/BigDataBiolog... | 31,030 |
https://github.com/scikit-learn/scikit-learn/issues/31030 | [
"Bug",
"help wanted",
"Needs Investigation"
] | DBSCAN always triggers and EfficiencyWarning
### Describe the bug
Calling dbscan always triggers an efficiency warning. There is no apparent way to either call it correctly or disable the warning.
This was originally reported as an issue in SemiBin, which uses DBSCAN under the hood: https://github.com/BigDataBiolog... | 31,030 |
https://github.com/scikit-learn/scikit-learn/issues/31030 | [
"Bug",
"help wanted",
"Needs Investigation"
] | DBSCAN always triggers and EfficiencyWarning
### Describe the bug
Calling dbscan always triggers an efficiency warning. There is no apparent way to either call it correctly or disable the warning.
This was originally reported as an issue in SemiBin, which uses DBSCAN under the hood: https://github.com/BigDataBiolog... | 31,030 |
https://github.com/scikit-learn/scikit-learn/issues/31030 | [
"Bug",
"help wanted",
"Needs Investigation"
] | DBSCAN always triggers and EfficiencyWarning
### Describe the bug
Calling dbscan always triggers an efficiency warning. There is no apparent way to either call it correctly or disable the warning.
This was originally reported as an issue in SemiBin, which uses DBSCAN under the hood: https://github.com/BigDataBiolog... | 31,030 |
https://github.com/scikit-learn/scikit-learn/issues/31030 | [
"Bug",
"help wanted",
"Needs Investigation"
] | DBSCAN always triggers and EfficiencyWarning
### Describe the bug
Calling dbscan always triggers an efficiency warning. There is no apparent way to either call it correctly or disable the warning.
This was originally reported as an issue in SemiBin, which uses DBSCAN under the hood: https://github.com/BigDataBiolog... | 31,030 |
https://github.com/scikit-learn/scikit-learn/issues/31030 | [
"Bug",
"help wanted",
"Needs Investigation"
] | DBSCAN always triggers and EfficiencyWarning
### Describe the bug
Calling dbscan always triggers an efficiency warning. There is no apparent way to either call it correctly or disable the warning.
This was originally reported as an issue in SemiBin, which uses DBSCAN under the hood: https://github.com/BigDataBiolog... | 31,030 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.