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/25022 | [
"module:cluster"
] | Reconsider the change for `n_init` in `KMeans` and `MiniBatchKMeans`
I open this PR to reconsider the changes introduced in #23038.
We decided to use a single initialization when using `init="kmeans++`. In the original issue (#9729), it seems that we based our choice on two aspects:
1. the default parameter used... | 25,022 |
https://github.com/scikit-learn/scikit-learn/issues/25022 | [
"module:cluster"
] | Reconsider the change for `n_init` in `KMeans` and `MiniBatchKMeans`
I open this PR to reconsider the changes introduced in #23038.
We decided to use a single initialization when using `init="kmeans++`. In the original issue (#9729), it seems that we based our choice on two aspects:
1. the default parameter used... | 25,022 |
https://github.com/scikit-learn/scikit-learn/issues/25022 | [
"module:cluster"
] | Reconsider the change for `n_init` in `KMeans` and `MiniBatchKMeans`
I open this PR to reconsider the changes introduced in #23038.
We decided to use a single initialization when using `init="kmeans++`. In the original issue (#9729), it seems that we based our choice on two aspects:
1. the default parameter used... | 25,022 |
https://github.com/scikit-learn/scikit-learn/issues/25022 | [
"module:cluster"
] | Reconsider the change for `n_init` in `KMeans` and `MiniBatchKMeans`
I open this PR to reconsider the changes introduced in #23038.
We decided to use a single initialization when using `init="kmeans++`. In the original issue (#9729), it seems that we based our choice on two aspects:
1. the default parameter used... | 25,022 |
https://github.com/scikit-learn/scikit-learn/issues/25022 | [
"module:cluster"
] | Reconsider the change for `n_init` in `KMeans` and `MiniBatchKMeans`
I open this PR to reconsider the changes introduced in #23038.
We decided to use a single initialization when using `init="kmeans++`. In the original issue (#9729), it seems that we based our choice on two aspects:
1. the default parameter used... | 25,022 |
https://github.com/scikit-learn/scikit-learn/issues/25022 | [
"module:cluster"
] | Reconsider the change for `n_init` in `KMeans` and `MiniBatchKMeans`
I open this PR to reconsider the changes introduced in #23038.
We decided to use a single initialization when using `init="kmeans++`. In the original issue (#9729), it seems that we based our choice on two aspects:
1. the default parameter used... | 25,022 |
https://github.com/scikit-learn/scikit-learn/issues/25022 | [
"module:cluster"
] | Reconsider the change for `n_init` in `KMeans` and `MiniBatchKMeans`
I open this PR to reconsider the changes introduced in #23038.
We decided to use a single initialization when using `init="kmeans++`. In the original issue (#9729), it seems that we based our choice on two aspects:
1. the default parameter used... | 25,022 |
https://github.com/scikit-learn/scikit-learn/issues/25022 | [
"module:cluster"
] | Reconsider the change for `n_init` in `KMeans` and `MiniBatchKMeans`
I open this PR to reconsider the changes introduced in #23038.
We decided to use a single initialization when using `init="kmeans++`. In the original issue (#9729), it seems that we based our choice on two aspects:
1. the default parameter used... | 25,022 |
https://github.com/scikit-learn/scikit-learn/issues/25019 | [
"Bug",
"Needs Triage"
] | The shape of dual_coef_ of KernelRidge, SVR
### Describe the bug
Fear of potential bugs.
The shape of dual_coef_ does not match in two models that use kernels (e.g. KernelRidge and SVR)
KernelRidge has a shape of (n_samples,)
SVR has a shape of (1, n_samples).
Is there a compelling reason for this discrep... | 25,019 |
https://github.com/scikit-learn/scikit-learn/issues/25004 | [
"module:tree"
] | MAINT Convert `samples` parameter in Criterion classes to memory view
## Summary
The `samples` parameter can be changed to a Cython memoryview from its current `SIZE_t* samples` type.
_Originally posted by @adam2392 in https://github.com/scikit-learn/scikit-learn/pull/24994#discussion_r1028818076_
COMMENT:
Hi @... | 25,004 |
https://github.com/scikit-learn/scikit-learn/issues/25000 | [
"New Feature",
"Needs Decision - Include Feature",
"Array API"
] | Feature request: an additional config context for forcing conversion toward a specific Array API-compatible array library.
### Describe the workflow you want to enable
Per https://github.com/scikit-learn/scikit-learn/pull/22554 such workflow is possible:
```python
from sklearn.datasets import make_classificatio... | 25,000 |
https://github.com/scikit-learn/scikit-learn/issues/25000 | [
"New Feature",
"Needs Decision - Include Feature",
"Array API"
] | Feature request: an additional config context for forcing conversion toward a specific Array API-compatible array library.
### Describe the workflow you want to enable
Per https://github.com/scikit-learn/scikit-learn/pull/22554 such workflow is possible:
```python
from sklearn.datasets import make_classificatio... | 25,000 |
https://github.com/scikit-learn/scikit-learn/issues/25000 | [
"New Feature",
"Needs Decision - Include Feature",
"Array API"
] | Feature request: an additional config context for forcing conversion toward a specific Array API-compatible array library.
### Describe the workflow you want to enable
Per https://github.com/scikit-learn/scikit-learn/pull/22554 such workflow is possible:
```python
from sklearn.datasets import make_classificatio... | 25,000 |
https://github.com/scikit-learn/scikit-learn/issues/25000 | [
"New Feature",
"Needs Decision - Include Feature",
"Array API"
] | Feature request: an additional config context for forcing conversion toward a specific Array API-compatible array library.
### Describe the workflow you want to enable
Per https://github.com/scikit-learn/scikit-learn/pull/22554 such workflow is possible:
```python
from sklearn.datasets import make_classificatio... | 25,000 |
https://github.com/scikit-learn/scikit-learn/issues/25000 | [
"New Feature",
"Needs Decision - Include Feature",
"Array API"
] | Feature request: an additional config context for forcing conversion toward a specific Array API-compatible array library.
### Describe the workflow you want to enable
Per https://github.com/scikit-learn/scikit-learn/pull/22554 such workflow is possible:
```python
from sklearn.datasets import make_classificatio... | 25,000 |
https://github.com/scikit-learn/scikit-learn/issues/25000 | [
"New Feature",
"Needs Decision - Include Feature",
"Array API"
] | Feature request: an additional config context for forcing conversion toward a specific Array API-compatible array library.
### Describe the workflow you want to enable
Per https://github.com/scikit-learn/scikit-learn/pull/22554 such workflow is possible:
```python
from sklearn.datasets import make_classificatio... | 25,000 |
https://github.com/scikit-learn/scikit-learn/issues/25000 | [
"New Feature",
"Needs Decision - Include Feature",
"Array API"
] | Feature request: an additional config context for forcing conversion toward a specific Array API-compatible array library.
### Describe the workflow you want to enable
Per https://github.com/scikit-learn/scikit-learn/pull/22554 such workflow is possible:
```python
from sklearn.datasets import make_classificatio... | 25,000 |
https://github.com/scikit-learn/scikit-learn/issues/25000 | [
"New Feature",
"Needs Decision - Include Feature",
"Array API"
] | Feature request: an additional config context for forcing conversion toward a specific Array API-compatible array library.
### Describe the workflow you want to enable
Per https://github.com/scikit-learn/scikit-learn/pull/22554 such workflow is possible:
```python
from sklearn.datasets import make_classificatio... | 25,000 |
https://github.com/scikit-learn/scikit-learn/issues/25000 | [
"New Feature",
"Needs Decision - Include Feature",
"Array API"
] | Feature request: an additional config context for forcing conversion toward a specific Array API-compatible array library.
### Describe the workflow you want to enable
Per https://github.com/scikit-learn/scikit-learn/pull/22554 such workflow is possible:
```python
from sklearn.datasets import make_classificatio... | 25,000 |
https://github.com/scikit-learn/scikit-learn/issues/25000 | [
"New Feature",
"Needs Decision - Include Feature",
"Array API"
] | Feature request: an additional config context for forcing conversion toward a specific Array API-compatible array library.
### Describe the workflow you want to enable
Per https://github.com/scikit-learn/scikit-learn/pull/22554 such workflow is possible:
```python
from sklearn.datasets import make_classificatio... | 25,000 |
https://github.com/scikit-learn/scikit-learn/issues/25000 | [
"New Feature",
"Needs Decision - Include Feature",
"Array API"
] | Feature request: an additional config context for forcing conversion toward a specific Array API-compatible array library.
### Describe the workflow you want to enable
Per https://github.com/scikit-learn/scikit-learn/pull/22554 such workflow is possible:
```python
from sklearn.datasets import make_classificatio... | 25,000 |
https://github.com/scikit-learn/scikit-learn/issues/25000 | [
"New Feature",
"Needs Decision - Include Feature",
"Array API"
] | Feature request: an additional config context for forcing conversion toward a specific Array API-compatible array library.
### Describe the workflow you want to enable
Per https://github.com/scikit-learn/scikit-learn/pull/22554 such workflow is possible:
```python
from sklearn.datasets import make_classificatio... | 25,000 |
https://github.com/scikit-learn/scikit-learn/issues/24996 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_Nightly_PyPy.pypy3 ⚠️
**CI failed on [Linux_Nightly_PyPy.pypy3](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=49087&view=logs&j=0b16f832-29d6-5b92-1c23-eb006f606a66)** (Nov 21, 2022)
Unable to find junit file. Please see link for details.
COMMENT:
## CI is no longer fail... | 24,996 |
https://github.com/scikit-learn/scikit-learn/issues/24996 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_Nightly_PyPy.pypy3 ⚠️
**CI failed on [Linux_Nightly_PyPy.pypy3](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=49087&view=logs&j=0b16f832-29d6-5b92-1c23-eb006f606a66)** (Nov 21, 2022)
Unable to find junit file. Please see link for details.
COMMENT:
The failure looks like ... | 24,996 |
https://github.com/scikit-learn/scikit-learn/issues/24993 | [
"New Feature",
"Needs Triage"
] | TransformerChain
### Describe the workflow you want to enable
1. To be able to encapsulate extraction and encoding of features from a source feature
2. To be able to turn off features derived from a source feature easier than having to turn off the extraction and encoding stages of the pipeline.
3. To be able to se... | 24,993 |
https://github.com/scikit-learn/scikit-learn/issues/24993 | [
"New Feature",
"Needs Triage"
] | TransformerChain
### Describe the workflow you want to enable
1. To be able to encapsulate extraction and encoding of features from a source feature
2. To be able to turn off features derived from a source feature easier than having to turn off the extraction and encoding stages of the pipeline.
3. To be able to se... | 24,993 |
https://github.com/scikit-learn/scikit-learn/issues/24992 | [
"Bug",
"Needs Triage"
] | Sklearn pip installation broke because of issues with setuptools
### Describe the bug
Apparently because of this other issue https://github.com/pypa/setuptools/issues/3693
Installation of sklearn breaks with pip install right now.
```
File "/tmp/pip-build-env-mmiaw08q/overlay/lib/python3.10/site-packages/numpy... | 24,992 |
https://github.com/scikit-learn/scikit-learn/issues/24992 | [
"Bug",
"Needs Triage"
] | Sklearn pip installation broke because of issues with setuptools
### Describe the bug
Apparently because of this other issue https://github.com/pypa/setuptools/issues/3693
Installation of sklearn breaks with pip install right now.
```
File "/tmp/pip-build-env-mmiaw08q/overlay/lib/python3.10/site-packages/numpy... | 24,992 |
https://github.com/scikit-learn/scikit-learn/issues/24990 | [
"module:tree",
"cython",
"Refactor"
] | MAINT Split `Splitter` into a `BaseSplitter` and a `Splitter` subclass to allow easier inheritance
### Summary
With #24678, we make it easier for the `Criterion` class to be inherited. However, the Splitter class can also leverage this improvement. We should separate the current `Splitter` class into an abstract base... | 24,990 |
https://github.com/scikit-learn/scikit-learn/issues/24990 | [
"module:tree",
"cython",
"Refactor"
] | MAINT Split `Splitter` into a `BaseSplitter` and a `Splitter` subclass to allow easier inheritance
### Summary
With #24678, we make it easier for the `Criterion` class to be inherited. However, the Splitter class can also leverage this improvement. We should separate the current `Splitter` class into an abstract base... | 24,990 |
https://github.com/scikit-learn/scikit-learn/issues/24990 | [
"module:tree",
"cython",
"Refactor"
] | MAINT Split `Splitter` into a `BaseSplitter` and a `Splitter` subclass to allow easier inheritance
### Summary
With #24678, we make it easier for the `Criterion` class to be inherited. However, the Splitter class can also leverage this improvement. We should separate the current `Splitter` class into an abstract base... | 24,990 |
https://github.com/scikit-learn/scikit-learn/issues/24990 | [
"module:tree",
"cython",
"Refactor"
] | MAINT Split `Splitter` into a `BaseSplitter` and a `Splitter` subclass to allow easier inheritance
### Summary
With #24678, we make it easier for the `Criterion` class to be inherited. However, the Splitter class can also leverage this improvement. We should separate the current `Splitter` class into an abstract base... | 24,990 |
https://github.com/scikit-learn/scikit-learn/issues/24990 | [
"module:tree",
"cython",
"Refactor"
] | MAINT Split `Splitter` into a `BaseSplitter` and a `Splitter` subclass to allow easier inheritance
### Summary
With #24678, we make it easier for the `Criterion` class to be inherited. However, the Splitter class can also leverage this improvement. We should separate the current `Splitter` class into an abstract base... | 24,990 |
https://github.com/scikit-learn/scikit-learn/issues/24990 | [
"module:tree",
"cython",
"Refactor"
] | MAINT Split `Splitter` into a `BaseSplitter` and a `Splitter` subclass to allow easier inheritance
### Summary
With #24678, we make it easier for the `Criterion` class to be inherited. However, the Splitter class can also leverage this improvement. We should separate the current `Splitter` class into an abstract base... | 24,990 |
https://github.com/scikit-learn/scikit-learn/issues/24990 | [
"module:tree",
"cython",
"Refactor"
] | MAINT Split `Splitter` into a `BaseSplitter` and a `Splitter` subclass to allow easier inheritance
### Summary
With #24678, we make it easier for the `Criterion` class to be inherited. However, the Splitter class can also leverage this improvement. We should separate the current `Splitter` class into an abstract base... | 24,990 |
https://github.com/scikit-learn/scikit-learn/issues/24990 | [
"module:tree",
"cython",
"Refactor"
] | MAINT Split `Splitter` into a `BaseSplitter` and a `Splitter` subclass to allow easier inheritance
### Summary
With #24678, we make it easier for the `Criterion` class to be inherited. However, the Splitter class can also leverage this improvement. We should separate the current `Splitter` class into an abstract base... | 24,990 |
https://github.com/scikit-learn/scikit-learn/issues/24990 | [
"module:tree",
"cython",
"Refactor"
] | MAINT Split `Splitter` into a `BaseSplitter` and a `Splitter` subclass to allow easier inheritance
### Summary
With #24678, we make it easier for the `Criterion` class to be inherited. However, the Splitter class can also leverage this improvement. We should separate the current `Splitter` class into an abstract base... | 24,990 |
https://github.com/scikit-learn/scikit-learn/issues/24990 | [
"module:tree",
"cython",
"Refactor"
] | MAINT Split `Splitter` into a `BaseSplitter` and a `Splitter` subclass to allow easier inheritance
### Summary
With #24678, we make it easier for the `Criterion` class to be inherited. However, the Splitter class can also leverage this improvement. We should separate the current `Splitter` class into an abstract base... | 24,990 |
https://github.com/scikit-learn/scikit-learn/issues/24990 | [
"module:tree",
"cython",
"Refactor"
] | MAINT Split `Splitter` into a `BaseSplitter` and a `Splitter` subclass to allow easier inheritance
### Summary
With #24678, we make it easier for the `Criterion` class to be inherited. However, the Splitter class can also leverage this improvement. We should separate the current `Splitter` class into an abstract base... | 24,990 |
https://github.com/scikit-learn/scikit-learn/issues/24990 | [
"module:tree",
"cython",
"Refactor"
] | MAINT Split `Splitter` into a `BaseSplitter` and a `Splitter` subclass to allow easier inheritance
### Summary
With #24678, we make it easier for the `Criterion` class to be inherited. However, the Splitter class can also leverage this improvement. We should separate the current `Splitter` class into an abstract base... | 24,990 |
https://github.com/scikit-learn/scikit-learn/issues/24990 | [
"module:tree",
"cython",
"Refactor"
] | MAINT Split `Splitter` into a `BaseSplitter` and a `Splitter` subclass to allow easier inheritance
### Summary
With #24678, we make it easier for the `Criterion` class to be inherited. However, the Splitter class can also leverage this improvement. We should separate the current `Splitter` class into an abstract base... | 24,990 |
https://github.com/scikit-learn/scikit-learn/issues/24990 | [
"module:tree",
"cython",
"Refactor"
] | MAINT Split `Splitter` into a `BaseSplitter` and a `Splitter` subclass to allow easier inheritance
### Summary
With #24678, we make it easier for the `Criterion` class to be inherited. However, the Splitter class can also leverage this improvement. We should separate the current `Splitter` class into an abstract base... | 24,990 |
https://github.com/scikit-learn/scikit-learn/issues/24990 | [
"module:tree",
"cython",
"Refactor"
] | MAINT Split `Splitter` into a `BaseSplitter` and a `Splitter` subclass to allow easier inheritance
### Summary
With #24678, we make it easier for the `Criterion` class to be inherited. However, the Splitter class can also leverage this improvement. We should separate the current `Splitter` class into an abstract base... | 24,990 |
https://github.com/scikit-learn/scikit-learn/issues/24988 | [
"New Feature",
"Needs Triage"
] | NEW FEATURE: MarginalSumsRegression
### Describe the workflow you want to enable
Adding Marginal Sums as a regression estimator. Marginal Sums are used in actuarial science to construct a multiplicative estimator: f1 * f2 * ... * fn * b = y with fi being a factor for every feature and b being a base value (the mean... | 24,988 |
https://github.com/scikit-learn/scikit-learn/issues/24988 | [
"New Feature",
"Needs Triage"
] | NEW FEATURE: MarginalSumsRegression
### Describe the workflow you want to enable
Adding Marginal Sums as a regression estimator. Marginal Sums are used in actuarial science to construct a multiplicative estimator: f1 * f2 * ... * fn * b = y with fi being a factor for every feature and b being a base value (the mean... | 24,988 |
https://github.com/scikit-learn/scikit-learn/issues/24988 | [
"New Feature",
"Needs Triage"
] | NEW FEATURE: MarginalSumsRegression
### Describe the workflow you want to enable
Adding Marginal Sums as a regression estimator. Marginal Sums are used in actuarial science to construct a multiplicative estimator: f1 * f2 * ... * fn * b = y with fi being a factor for every feature and b being a base value (the mean... | 24,988 |
https://github.com/scikit-learn/scikit-learn/issues/24988 | [
"New Feature",
"Needs Triage"
] | NEW FEATURE: MarginalSumsRegression
### Describe the workflow you want to enable
Adding Marginal Sums as a regression estimator. Marginal Sums are used in actuarial science to construct a multiplicative estimator: f1 * f2 * ... * fn * b = y with fi being a factor for every feature and b being a base value (the mean... | 24,988 |
https://github.com/scikit-learn/scikit-learn/issues/24988 | [
"New Feature",
"Needs Triage"
] | NEW FEATURE: MarginalSumsRegression
### Describe the workflow you want to enable
Adding Marginal Sums as a regression estimator. Marginal Sums are used in actuarial science to construct a multiplicative estimator: f1 * f2 * ... * fn * b = y with fi being a factor for every feature and b being a base value (the mean... | 24,988 |
https://github.com/scikit-learn/scikit-learn/issues/24976 | [
"New Feature",
"Needs Triage"
] | Control default behavior of PR curve
### Describe the workflow you want to enable
Display the recall as a function of the predicted positive rate (PP) using `sklearn.metrics.precision_recall_curve` to compute the recall and PP as a quantiles of the threshold scores. Currently not possible to perform consistently as... | 24,976 |
https://github.com/scikit-learn/scikit-learn/issues/24976 | [
"New Feature",
"Needs Triage"
] | Control default behavior of PR curve
### Describe the workflow you want to enable
Display the recall as a function of the predicted positive rate (PP) using `sklearn.metrics.precision_recall_curve` to compute the recall and PP as a quantiles of the threshold scores. Currently not possible to perform consistently as... | 24,976 |
https://github.com/scikit-learn/scikit-learn/issues/24974 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_Nightly_PyPy.pypy3 ⚠️
**CI failed on [Linux_Nightly_PyPy.pypy3](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=48973&view=logs&j=0b16f832-29d6-5b92-1c23-eb006f606a66)** (Nov 18, 2022)
- test_fit_and_score_verbosity[False-scorer2-10-split_prg2-cdt_prg2-\\[CV 2/3; 1/1\\] END... | 24,974 |
https://github.com/scikit-learn/scikit-learn/issues/24974 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_Nightly_PyPy.pypy3 ⚠️
**CI failed on [Linux_Nightly_PyPy.pypy3](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=48973&view=logs&j=0b16f832-29d6-5b92-1c23-eb006f606a66)** (Nov 18, 2022)
- test_fit_and_score_verbosity[False-scorer2-10-split_prg2-cdt_prg2-\\[CV 2/3; 1/1\\] END... | 24,974 |
https://github.com/scikit-learn/scikit-learn/issues/24972 | [
"New Feature",
"module:cluster",
"Needs Decision - Include Feature"
] | Dirichlet Multinomial Mixture Model
### Describe the workflow you want to enable
Is there an intention to implement the Dirichlet Multinomial Mixture Model with EM algorithm?
Dirichlet Multinomial Mixture Model is a popular clustering model in NLP, Information Retrieval and Bioinformatics.
### Describe your prop... | 24,972 |
https://github.com/scikit-learn/scikit-learn/issues/24972 | [
"New Feature",
"module:cluster",
"Needs Decision - Include Feature"
] | Dirichlet Multinomial Mixture Model
### Describe the workflow you want to enable
Is there an intention to implement the Dirichlet Multinomial Mixture Model with EM algorithm?
Dirichlet Multinomial Mixture Model is a popular clustering model in NLP, Information Retrieval and Bioinformatics.
### Describe your prop... | 24,972 |
https://github.com/scikit-learn/scikit-learn/issues/24967 | [
"New Feature"
] | Transformer for nominal categories, with the goal of improving category support in decision trees
I'd like to find out how keen people would be for adding a transformer like this.
### Describe the workflow you want to enable
Improved support for nominal categories in tree based models. Nominal categories are one... | 24,967 |
https://github.com/scikit-learn/scikit-learn/issues/24967 | [
"New Feature"
] | Transformer for nominal categories, with the goal of improving category support in decision trees
I'd like to find out how keen people would be for adding a transformer like this.
### Describe the workflow you want to enable
Improved support for nominal categories in tree based models. Nominal categories are one... | 24,967 |
https://github.com/scikit-learn/scikit-learn/issues/24967 | [
"New Feature"
] | Transformer for nominal categories, with the goal of improving category support in decision trees
I'd like to find out how keen people would be for adding a transformer like this.
### Describe the workflow you want to enable
Improved support for nominal categories in tree based models. Nominal categories are one... | 24,967 |
https://github.com/scikit-learn/scikit-learn/issues/24967 | [
"New Feature"
] | Transformer for nominal categories, with the goal of improving category support in decision trees
I'd like to find out how keen people would be for adding a transformer like this.
### Describe the workflow you want to enable
Improved support for nominal categories in tree based models. Nominal categories are one... | 24,967 |
https://github.com/scikit-learn/scikit-learn/issues/24967 | [
"New Feature"
] | Transformer for nominal categories, with the goal of improving category support in decision trees
I'd like to find out how keen people would be for adding a transformer like this.
### Describe the workflow you want to enable
Improved support for nominal categories in tree based models. Nominal categories are one... | 24,967 |
https://github.com/scikit-learn/scikit-learn/issues/24967 | [
"New Feature"
] | Transformer for nominal categories, with the goal of improving category support in decision trees
I'd like to find out how keen people would be for adding a transformer like this.
### Describe the workflow you want to enable
Improved support for nominal categories in tree based models. Nominal categories are one... | 24,967 |
https://github.com/scikit-learn/scikit-learn/issues/24967 | [
"New Feature"
] | Transformer for nominal categories, with the goal of improving category support in decision trees
I'd like to find out how keen people would be for adding a transformer like this.
### Describe the workflow you want to enable
Improved support for nominal categories in tree based models. Nominal categories are one... | 24,967 |
https://github.com/scikit-learn/scikit-learn/issues/24967 | [
"New Feature"
] | Transformer for nominal categories, with the goal of improving category support in decision trees
I'd like to find out how keen people would be for adding a transformer like this.
### Describe the workflow you want to enable
Improved support for nominal categories in tree based models. Nominal categories are one... | 24,967 |
https://github.com/scikit-learn/scikit-learn/issues/24967 | [
"New Feature"
] | Transformer for nominal categories, with the goal of improving category support in decision trees
I'd like to find out how keen people would be for adding a transformer like this.
### Describe the workflow you want to enable
Improved support for nominal categories in tree based models. Nominal categories are one... | 24,967 |
https://github.com/scikit-learn/scikit-learn/issues/24967 | [
"New Feature"
] | Transformer for nominal categories, with the goal of improving category support in decision trees
I'd like to find out how keen people would be for adding a transformer like this.
### Describe the workflow you want to enable
Improved support for nominal categories in tree based models. Nominal categories are one... | 24,967 |
https://github.com/scikit-learn/scikit-learn/issues/24967 | [
"New Feature"
] | Transformer for nominal categories, with the goal of improving category support in decision trees
I'd like to find out how keen people would be for adding a transformer like this.
### Describe the workflow you want to enable
Improved support for nominal categories in tree based models. Nominal categories are one... | 24,967 |
https://github.com/scikit-learn/scikit-learn/issues/24949 | [
"Bug",
"Blocker"
] | Regression in 1.2.dev: GenericUnivariateSelect with _parameter_constraints
### Describe the bug
When `mode="k_best"`, previously `param="all"` would be accepted, but that option is not provided in `GenericUnivariateSelect._parameter_constraints`, and so an error is raised.
It's perhaps not a common usecase, and ... | 24,949 |
https://github.com/scikit-learn/scikit-learn/issues/24949 | [
"Bug",
"Blocker"
] | Regression in 1.2.dev: GenericUnivariateSelect with _parameter_constraints
### Describe the bug
When `mode="k_best"`, previously `param="all"` would be accepted, but that option is not provided in `GenericUnivariateSelect._parameter_constraints`, and so an error is raised.
It's perhaps not a common usecase, and ... | 24,949 |
https://github.com/scikit-learn/scikit-learn/issues/24947 | [
"Bug",
"Needs Triage"
] | KFold returning folds with different lengths of Train and test splits
### Describe the bug
The sizes of the train and test split change over different splits.
For example, the size of the IRIS dataset is 150 rows. In 4-fold cross-validation, we would expect to see either 112-38 splits or 113-37 splits for all 4... | 24,947 |
https://github.com/scikit-learn/scikit-learn/issues/24947 | [
"Bug",
"Needs Triage"
] | KFold returning folds with different lengths of Train and test splits
### Describe the bug
The sizes of the train and test split change over different splits.
For example, the size of the IRIS dataset is 150 rows. In 4-fold cross-validation, we would expect to see either 112-38 splits or 113-37 splits for all 4... | 24,947 |
https://github.com/scikit-learn/scikit-learn/issues/24947 | [
"Bug",
"Needs Triage"
] | KFold returning folds with different lengths of Train and test splits
### Describe the bug
The sizes of the train and test split change over different splits.
For example, the size of the IRIS dataset is 150 rows. In 4-fold cross-validation, we would expect to see either 112-38 splits or 113-37 splits for all 4... | 24,947 |
https://github.com/scikit-learn/scikit-learn/issues/24947 | [
"Bug",
"Needs Triage"
] | KFold returning folds with different lengths of Train and test splits
### Describe the bug
The sizes of the train and test split change over different splits.
For example, the size of the IRIS dataset is 150 rows. In 4-fold cross-validation, we would expect to see either 112-38 splits or 113-37 splits for all 4... | 24,947 |
https://github.com/scikit-learn/scikit-learn/issues/24947 | [
"Bug",
"Needs Triage"
] | KFold returning folds with different lengths of Train and test splits
### Describe the bug
The sizes of the train and test split change over different splits.
For example, the size of the IRIS dataset is 150 rows. In 4-fold cross-validation, we would expect to see either 112-38 splits or 113-37 splits for all 4... | 24,947 |
https://github.com/scikit-learn/scikit-learn/issues/24945 | [
"Bug",
"Needs Triage"
] | Cannot import cross_validation
### Describe the bug
For about a week now, I've tried various things to get cross_validation to import and run in my code, but it appears to be missing from my installation of scikit-learn. I went back and forth with PyCharm, and we confirmed (as best as we can) that it's not PyCharm's ... | 24,945 |
https://github.com/scikit-learn/scikit-learn/issues/24942 | [
"Bug",
"Blocker"
] | Bug in fetch_lfw_people() function
### Describe the bug
There is a bug on line 162 of _lfw.py. That line currently reads:
`pil_img.crop((w_slice.start, h_slice.start, w_slice.stop, h_slice.stop))`
It should read:
`pil_img = pil_img.crop((w_slice.start, h_slice.start, w_slice.stop, h_slice.stop))`
Becaus... | 24,942 |
https://github.com/scikit-learn/scikit-learn/issues/24942 | [
"Bug",
"Blocker"
] | Bug in fetch_lfw_people() function
### Describe the bug
There is a bug on line 162 of _lfw.py. That line currently reads:
`pil_img.crop((w_slice.start, h_slice.start, w_slice.stop, h_slice.stop))`
It should read:
`pil_img = pil_img.crop((w_slice.start, h_slice.start, w_slice.stop, h_slice.stop))`
Becaus... | 24,942 |
https://github.com/scikit-learn/scikit-learn/issues/24923 | [
"Bug",
"Blocker"
] | `IterativeImputer` `InvalidIndexError` on dev branch after setting `transform_output`
### Describe the bug
After using `sklearn.set_config(transform_output="pandas")` to set output globally, `IterativeImputer` fails with an `InvalidIndexError` error.
### Steps/Code to Reproduce
From [`IterativeImputer` exampl... | 24,923 |
https://github.com/scikit-learn/scikit-learn/issues/24923 | [
"Bug",
"Blocker"
] | `IterativeImputer` `InvalidIndexError` on dev branch after setting `transform_output`
### Describe the bug
After using `sklearn.set_config(transform_output="pandas")` to set output globally, `IterativeImputer` fails with an `InvalidIndexError` error.
### Steps/Code to Reproduce
From [`IterativeImputer` exampl... | 24,923 |
https://github.com/scikit-learn/scikit-learn/issues/24923 | [
"Bug",
"Blocker"
] | `IterativeImputer` `InvalidIndexError` on dev branch after setting `transform_output`
### Describe the bug
After using `sklearn.set_config(transform_output="pandas")` to set output globally, `IterativeImputer` fails with an `InvalidIndexError` error.
### Steps/Code to Reproduce
From [`IterativeImputer` exampl... | 24,923 |
https://github.com/scikit-learn/scikit-learn/issues/24923 | [
"Bug",
"Blocker"
] | `IterativeImputer` `InvalidIndexError` on dev branch after setting `transform_output`
### Describe the bug
After using `sklearn.set_config(transform_output="pandas")` to set output globally, `IterativeImputer` fails with an `InvalidIndexError` error.
### Steps/Code to Reproduce
From [`IterativeImputer` exampl... | 24,923 |
https://github.com/scikit-learn/scikit-learn/issues/24923 | [
"Bug",
"Blocker"
] | `IterativeImputer` `InvalidIndexError` on dev branch after setting `transform_output`
### Describe the bug
After using `sklearn.set_config(transform_output="pandas")` to set output globally, `IterativeImputer` fails with an `InvalidIndexError` error.
### Steps/Code to Reproduce
From [`IterativeImputer` exampl... | 24,923 |
https://github.com/scikit-learn/scikit-learn/issues/24923 | [
"Bug",
"Blocker"
] | `IterativeImputer` `InvalidIndexError` on dev branch after setting `transform_output`
### Describe the bug
After using `sklearn.set_config(transform_output="pandas")` to set output globally, `IterativeImputer` fails with an `InvalidIndexError` error.
### Steps/Code to Reproduce
From [`IterativeImputer` exampl... | 24,923 |
https://github.com/scikit-learn/scikit-learn/issues/24916 | [
"New Feature",
"Enhancement",
"help wanted",
"Meta-issue"
] | Make error message uniform when calling `get_feature_names_out` before `fit`
While working #24838, we found out that we are not consistent with the error type and message when calling `get_feature_names_out` before `fit`.
From @jpangas:
> Here is the updated list of the estimators that raise inconsistent errors wh... | 24,916 |
https://github.com/scikit-learn/scikit-learn/issues/24916 | [
"New Feature",
"Enhancement",
"help wanted",
"Meta-issue"
] | Make error message uniform when calling `get_feature_names_out` before `fit`
While working #24838, we found out that we are not consistent with the error type and message when calling `get_feature_names_out` before `fit`.
From @jpangas:
> Here is the updated list of the estimators that raise inconsistent errors wh... | 24,916 |
https://github.com/scikit-learn/scikit-learn/issues/24916 | [
"New Feature",
"Enhancement",
"help wanted",
"Meta-issue"
] | Make error message uniform when calling `get_feature_names_out` before `fit`
While working #24838, we found out that we are not consistent with the error type and message when calling `get_feature_names_out` before `fit`.
From @jpangas:
> Here is the updated list of the estimators that raise inconsistent errors wh... | 24,916 |
https://github.com/scikit-learn/scikit-learn/issues/24916 | [
"New Feature",
"Enhancement",
"help wanted",
"Meta-issue"
] | Make error message uniform when calling `get_feature_names_out` before `fit`
While working #24838, we found out that we are not consistent with the error type and message when calling `get_feature_names_out` before `fit`.
From @jpangas:
> Here is the updated list of the estimators that raise inconsistent errors wh... | 24,916 |
https://github.com/scikit-learn/scikit-learn/issues/24916 | [
"New Feature",
"Enhancement",
"help wanted",
"Meta-issue"
] | Make error message uniform when calling `get_feature_names_out` before `fit`
While working #24838, we found out that we are not consistent with the error type and message when calling `get_feature_names_out` before `fit`.
From @jpangas:
> Here is the updated list of the estimators that raise inconsistent errors wh... | 24,916 |
https://github.com/scikit-learn/scikit-learn/issues/24916 | [
"New Feature",
"Enhancement",
"help wanted",
"Meta-issue"
] | Make error message uniform when calling `get_feature_names_out` before `fit`
While working #24838, we found out that we are not consistent with the error type and message when calling `get_feature_names_out` before `fit`.
From @jpangas:
> Here is the updated list of the estimators that raise inconsistent errors wh... | 24,916 |
https://github.com/scikit-learn/scikit-learn/issues/24916 | [
"New Feature",
"Enhancement",
"help wanted",
"Meta-issue"
] | Make error message uniform when calling `get_feature_names_out` before `fit`
While working #24838, we found out that we are not consistent with the error type and message when calling `get_feature_names_out` before `fit`.
From @jpangas:
> Here is the updated list of the estimators that raise inconsistent errors wh... | 24,916 |
https://github.com/scikit-learn/scikit-learn/issues/24916 | [
"New Feature",
"Enhancement",
"help wanted",
"Meta-issue"
] | Make error message uniform when calling `get_feature_names_out` before `fit`
While working #24838, we found out that we are not consistent with the error type and message when calling `get_feature_names_out` before `fit`.
From @jpangas:
> Here is the updated list of the estimators that raise inconsistent errors wh... | 24,916 |
https://github.com/scikit-learn/scikit-learn/issues/24916 | [
"New Feature",
"Enhancement",
"help wanted",
"Meta-issue"
] | Make error message uniform when calling `get_feature_names_out` before `fit`
While working #24838, we found out that we are not consistent with the error type and message when calling `get_feature_names_out` before `fit`.
From @jpangas:
> Here is the updated list of the estimators that raise inconsistent errors wh... | 24,916 |
https://github.com/scikit-learn/scikit-learn/issues/24916 | [
"New Feature",
"Enhancement",
"help wanted",
"Meta-issue"
] | Make error message uniform when calling `get_feature_names_out` before `fit`
While working #24838, we found out that we are not consistent with the error type and message when calling `get_feature_names_out` before `fit`.
From @jpangas:
> Here is the updated list of the estimators that raise inconsistent errors wh... | 24,916 |
https://github.com/scikit-learn/scikit-learn/issues/24916 | [
"New Feature",
"Enhancement",
"help wanted",
"Meta-issue"
] | Make error message uniform when calling `get_feature_names_out` before `fit`
While working #24838, we found out that we are not consistent with the error type and message when calling `get_feature_names_out` before `fit`.
From @jpangas:
> Here is the updated list of the estimators that raise inconsistent errors wh... | 24,916 |
https://github.com/scikit-learn/scikit-learn/issues/24916 | [
"New Feature",
"Enhancement",
"help wanted",
"Meta-issue"
] | Make error message uniform when calling `get_feature_names_out` before `fit`
While working #24838, we found out that we are not consistent with the error type and message when calling `get_feature_names_out` before `fit`.
From @jpangas:
> Here is the updated list of the estimators that raise inconsistent errors wh... | 24,916 |
https://github.com/scikit-learn/scikit-learn/issues/24916 | [
"New Feature",
"Enhancement",
"help wanted",
"Meta-issue"
] | Make error message uniform when calling `get_feature_names_out` before `fit`
While working #24838, we found out that we are not consistent with the error type and message when calling `get_feature_names_out` before `fit`.
From @jpangas:
> Here is the updated list of the estimators that raise inconsistent errors wh... | 24,916 |
https://github.com/scikit-learn/scikit-learn/issues/24916 | [
"New Feature",
"Enhancement",
"help wanted",
"Meta-issue"
] | Make error message uniform when calling `get_feature_names_out` before `fit`
While working #24838, we found out that we are not consistent with the error type and message when calling `get_feature_names_out` before `fit`.
From @jpangas:
> Here is the updated list of the estimators that raise inconsistent errors wh... | 24,916 |
https://github.com/scikit-learn/scikit-learn/issues/24916 | [
"New Feature",
"Enhancement",
"help wanted",
"Meta-issue"
] | Make error message uniform when calling `get_feature_names_out` before `fit`
While working #24838, we found out that we are not consistent with the error type and message when calling `get_feature_names_out` before `fit`.
From @jpangas:
> Here is the updated list of the estimators that raise inconsistent errors wh... | 24,916 |
https://github.com/scikit-learn/scikit-learn/issues/24916 | [
"New Feature",
"Enhancement",
"help wanted",
"Meta-issue"
] | Make error message uniform when calling `get_feature_names_out` before `fit`
While working #24838, we found out that we are not consistent with the error type and message when calling `get_feature_names_out` before `fit`.
From @jpangas:
> Here is the updated list of the estimators that raise inconsistent errors wh... | 24,916 |
https://github.com/scikit-learn/scikit-learn/issues/24916 | [
"New Feature",
"Enhancement",
"help wanted",
"Meta-issue"
] | Make error message uniform when calling `get_feature_names_out` before `fit`
While working #24838, we found out that we are not consistent with the error type and message when calling `get_feature_names_out` before `fit`.
From @jpangas:
> Here is the updated list of the estimators that raise inconsistent errors wh... | 24,916 |
https://github.com/scikit-learn/scikit-learn/issues/24916 | [
"New Feature",
"Enhancement",
"help wanted",
"Meta-issue"
] | Make error message uniform when calling `get_feature_names_out` before `fit`
While working #24838, we found out that we are not consistent with the error type and message when calling `get_feature_names_out` before `fit`.
From @jpangas:
> Here is the updated list of the estimators that raise inconsistent errors wh... | 24,916 |
https://github.com/scikit-learn/scikit-learn/issues/24916 | [
"New Feature",
"Enhancement",
"help wanted",
"Meta-issue"
] | Make error message uniform when calling `get_feature_names_out` before `fit`
While working #24838, we found out that we are not consistent with the error type and message when calling `get_feature_names_out` before `fit`.
From @jpangas:
> Here is the updated list of the estimators that raise inconsistent errors wh... | 24,916 |
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