html_url stringlengths 57 57 | labels listlengths 1 6 | text stringlengths 32 258k | issue_number int64 22.4k 33k | embedding listlengths 768 768 |
|---|---|---|---|---|
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 | [
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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 | [
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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 | [
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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 | [
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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 | [
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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 | [
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0.0... |
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 | [
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0.0... |
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 | [
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0.0259... |
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 | [
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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 | [
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0.0... |
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 | [
-0.02925458364188671,
0.08425796777009964,
-0.006817384157329798,
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0.09062713384628296,
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0.... |
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 | [
-0.02925458364188671,
0.08425796777009964,
-0.006817384157329798,
0.0019499893533065915,
0.030698416754603386,
0.011756453663110733,
0.07874695956707001,
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0.017508288845419884,
-0.022824235260486603,
-0.013876100070774555,
0.09062713384628296,
-0.02248828299343586,
0.... |
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 | [
-0.02925458364188671,
0.08425796777009964,
-0.006817384157329798,
0.0019499893533065915,
0.030698416754603386,
0.011756453663110733,
0.07874695956707001,
-0.021646052598953247,
0.017508288845419884,
-0.022824235260486603,
-0.013876100070774555,
0.09062713384628296,
-0.02248828299343586,
0.... |
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 | [
-0.02925458364188671,
0.08425796777009964,
-0.006817384157329798,
0.0019499893533065915,
0.030698416754603386,
0.011756453663110733,
0.07874695956707001,
-0.021646052598953247,
0.017508288845419884,
-0.022824235260486603,
-0.013876100070774555,
0.09062713384628296,
-0.02248828299343586,
0.... |
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 | [
-0.02925458364188671,
0.08425796777009964,
-0.006817384157329798,
0.0019499893533065915,
0.030698416754603386,
0.011756453663110733,
0.07874695956707001,
-0.021646052598953247,
0.017508288845419884,
-0.022824235260486603,
-0.013876100070774555,
0.09062713384628296,
-0.02248828299343586,
0.... |
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 | [
-0.02925458364188671,
0.08425796777009964,
-0.006817384157329798,
0.0019499893533065915,
0.030698416754603386,
0.011756453663110733,
0.07874695956707001,
-0.021646052598953247,
0.017508288845419884,
-0.022824235260486603,
-0.013876100070774555,
0.09062713384628296,
-0.02248828299343586,
0.... |
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 | [
-0.02925458364188671,
0.08425796777009964,
-0.006817384157329798,
0.0019499893533065915,
0.030698416754603386,
0.011756453663110733,
0.07874695956707001,
-0.021646052598953247,
0.017508288845419884,
-0.022824235260486603,
-0.013876100070774555,
0.09062713384628296,
-0.02248828299343586,
0.... |
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 | [
-0.02925458364188671,
0.08425796777009964,
-0.006817384157329798,
0.0019499893533065915,
0.030698416754603386,
0.011756453663110733,
0.07874695956707001,
-0.021646052598953247,
0.017508288845419884,
-0.022824235260486603,
-0.013876100070774555,
0.09062713384628296,
-0.02248828299343586,
0.... |
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 | [
-0.02925458364188671,
0.08425796777009964,
-0.006817384157329798,
0.0019499893533065915,
0.030698416754603386,
0.011756453663110733,
0.07874695956707001,
-0.021646052598953247,
0.017508288845419884,
-0.022824235260486603,
-0.013876100070774555,
0.09062713384628296,
-0.02248828299343586,
0.... |
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 | [
-0.02925458364188671,
0.08425796777009964,
-0.006817384157329798,
0.0019499893533065915,
0.030698416754603386,
0.011756453663110733,
0.07874695956707001,
-0.021646052598953247,
0.017508288845419884,
-0.022824235260486603,
-0.013876100070774555,
0.09062713384628296,
-0.02248828299343586,
0.... |
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 | [
-0.02925458364188671,
0.08425796777009964,
-0.006817384157329798,
0.0019499893533065915,
0.030698416754603386,
0.011756453663110733,
0.07874695956707001,
-0.021646052598953247,
0.017508288845419884,
-0.022824235260486603,
-0.013876100070774555,
0.09062713384628296,
-0.02248828299343586,
0.... |
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 | [
-0.02925458364188671,
0.08425796777009964,
-0.006817384157329798,
0.0019499893533065915,
0.030698416754603386,
0.011756453663110733,
0.07874695956707001,
-0.021646052598953247,
0.017508288845419884,
-0.022824235260486603,
-0.013876100070774555,
0.09062713384628296,
-0.02248828299343586,
0.... |
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 | [
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0.0586418... |
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 | [
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0.05467692... |
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 | [
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0.0... |
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 | [
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-0.010600114241242409,
0.0... |
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 | [
0.014873282052576542,
0.015887606889009476,
0.007403794210404158,
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0.06797853857278824,
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0.10349731892347336,
-0.02638894133269787,
0.0536336... |
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 | [
0.014873282052576542,
0.015887606889009476,
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0.0536336... |
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 | [
-0.011000762693583965,
0.033533625304698944,
0.017158476635813713,
0.02289801463484764,
-0.03139836713671684,
-0.04217751324176788,
0.02065844088792801,
0.034166984260082245,
-0.02868366613984108,
-0.04076292738318443,
0.01562444306910038,
0.020633336156606674,
-0.01427939161658287,
0.0276... |
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 | [
-0.011000762693583965,
0.033533625304698944,
0.017158476635813713,
0.02289801463484764,
-0.03139836713671684,
-0.04217751324176788,
0.02065844088792801,
0.034166984260082245,
-0.02868366613984108,
-0.04076292738318443,
0.01562444306910038,
0.020633336156606674,
-0.01427939161658287,
0.0276... |
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 | [
-0.011000762693583965,
0.033533625304698944,
0.017158476635813713,
0.02289801463484764,
-0.03139836713671684,
-0.04217751324176788,
0.02065844088792801,
0.034166984260082245,
-0.02868366613984108,
-0.04076292738318443,
0.01562444306910038,
0.020633336156606674,
-0.01427939161658287,
0.0276... |
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 | [
-0.011000762693583965,
0.033533625304698944,
0.017158476635813713,
0.02289801463484764,
-0.03139836713671684,
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0.02065844088792801,
0.034166984260082245,
-0.02868366613984108,
-0.04076292738318443,
0.01562444306910038,
0.020633336156606674,
-0.01427939161658287,
0.0276... |
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 | [
-0.011000762693583965,
0.033533625304698944,
0.017158476635813713,
0.02289801463484764,
-0.03139836713671684,
-0.04217751324176788,
0.02065844088792801,
0.034166984260082245,
-0.02868366613984108,
-0.04076292738318443,
0.01562444306910038,
0.020633336156606674,
-0.01427939161658287,
0.0276... |
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 | [
-0.011000762693583965,
0.033533625304698944,
0.017158476635813713,
0.02289801463484764,
-0.03139836713671684,
-0.04217751324176788,
0.02065844088792801,
0.034166984260082245,
-0.02868366613984108,
-0.04076292738318443,
0.01562444306910038,
0.020633336156606674,
-0.01427939161658287,
0.0276... |
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 | [
-0.011000762693583965,
0.033533625304698944,
0.017158476635813713,
0.02289801463484764,
-0.03139836713671684,
-0.04217751324176788,
0.02065844088792801,
0.034166984260082245,
-0.02868366613984108,
-0.04076292738318443,
0.01562444306910038,
0.020633336156606674,
-0.01427939161658287,
0.0276... |
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 | [
-0.011000762693583965,
0.033533625304698944,
0.017158476635813713,
0.02289801463484764,
-0.03139836713671684,
-0.04217751324176788,
0.02065844088792801,
0.034166984260082245,
-0.02868366613984108,
-0.04076292738318443,
0.01562444306910038,
0.020633336156606674,
-0.01427939161658287,
0.0276... |
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 | [
-0.011000762693583965,
0.033533625304698944,
0.017158476635813713,
0.02289801463484764,
-0.03139836713671684,
-0.04217751324176788,
0.02065844088792801,
0.034166984260082245,
-0.02868366613984108,
-0.04076292738318443,
0.01562444306910038,
0.020633336156606674,
-0.01427939161658287,
0.0276... |
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 | [
-0.011000762693583965,
0.033533625304698944,
0.017158476635813713,
0.02289801463484764,
-0.03139836713671684,
-0.04217751324176788,
0.02065844088792801,
0.034166984260082245,
-0.02868366613984108,
-0.04076292738318443,
0.01562444306910038,
0.020633336156606674,
-0.01427939161658287,
0.0276... |
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 | [
-0.011000762693583965,
0.033533625304698944,
0.017158476635813713,
0.02289801463484764,
-0.03139836713671684,
-0.04217751324176788,
0.02065844088792801,
0.034166984260082245,
-0.02868366613984108,
-0.04076292738318443,
0.01562444306910038,
0.020633336156606674,
-0.01427939161658287,
0.0276... |
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 | [
-0.011000762693583965,
0.033533625304698944,
0.017158476635813713,
0.02289801463484764,
-0.03139836713671684,
-0.04217751324176788,
0.02065844088792801,
0.034166984260082245,
-0.02868366613984108,
-0.04076292738318443,
0.01562444306910038,
0.020633336156606674,
-0.01427939161658287,
0.0276... |
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 | [
-0.011000762693583965,
0.033533625304698944,
0.017158476635813713,
0.02289801463484764,
-0.03139836713671684,
-0.04217751324176788,
0.02065844088792801,
0.034166984260082245,
-0.02868366613984108,
-0.04076292738318443,
0.01562444306910038,
0.020633336156606674,
-0.01427939161658287,
0.0276... |
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 | [
-0.011000762693583965,
0.033533625304698944,
0.017158476635813713,
0.02289801463484764,
-0.03139836713671684,
-0.04217751324176788,
0.02065844088792801,
0.034166984260082245,
-0.02868366613984108,
-0.04076292738318443,
0.01562444306910038,
0.020633336156606674,
-0.01427939161658287,
0.0276... |
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 | [
-0.011000762693583965,
0.033533625304698944,
0.017158476635813713,
0.02289801463484764,
-0.03139836713671684,
-0.04217751324176788,
0.02065844088792801,
0.034166984260082245,
-0.02868366613984108,
-0.04076292738318443,
0.01562444306910038,
0.020633336156606674,
-0.01427939161658287,
0.0276... |
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 | [
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0.1318... |
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 | [
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0.1... |
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 | [
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0.11... |
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 | [
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0.118... |
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 | [
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0.1171... |
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 | [
-0.028618279844522476,
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0.024853091686964035,
0.005151580087840557,
0.027667000889778137,
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0.01317009050399065,
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0... |
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 | [
-0.028618279844522476,
-0.03227705880999565,
0.024853091686964035,
0.005151580087840557,
0.027667000889778137,
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0.01317009050399065,
0.02353273332118988,
0.042700763791799545,
-0.016175081953406334,
0... |
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 | [
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0.03591347113251686,
0.05880951136350632,
0.016953513026237488,
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0.102... |
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 | [
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0.01764366216957569,
0.10... |
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 | [
0.022316651418805122,
0.031067615374922752,
-0.001091910875402391,
-0.02445816621184349,
-0.034619227051734924,
0.036104507744312286,
0.016624778509140015,
-0.012377447448670864,
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-0.023888902738690376,
0.008899154141545296,
0.023525921627879143,
-0.013448220677673817,
... |
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 | [
-0.00559599744156003,
0.0281448345631361,
0.004659515339881182,
-0.035253386944532394,
-0.0028169958386570215,
0.033951908349990845,
0.02335932105779648,
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-0.01088944636285305,
-0.010095754638314247,
0.033335063606500626,
-0.016179827973246574,
0... |
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 | [
-0.0037956126034259796,
0.10136911273002625,
-0.00002289402073074598,
-0.026815276592969894,
-0.02350953221321106,
-0.03539834916591644,
-0.023451296612620354,
0.02341705933213234,
-0.0943855345249176,
-0.0926707535982132,
0.01003729086369276,
0.014222498051822186,
-0.02438691258430481,
0.... |
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 | [
-0.0037956126034259796,
0.10136911273002625,
-0.00002289402073074598,
-0.026815276592969894,
-0.02350953221321106,
-0.03539834916591644,
-0.023451296612620354,
0.02341705933213234,
-0.0943855345249176,
-0.0926707535982132,
0.01003729086369276,
0.014222498051822186,
-0.02438691258430481,
0.... |
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 | [
-0.0037956126034259796,
0.10136911273002625,
-0.00002289402073074598,
-0.026815276592969894,
-0.02350953221321106,
-0.03539834916591644,
-0.023451296612620354,
0.02341705933213234,
-0.0943855345249176,
-0.0926707535982132,
0.01003729086369276,
0.014222498051822186,
-0.02438691258430481,
0.... |
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 | [
-0.0037956126034259796,
0.10136911273002625,
-0.00002289402073074598,
-0.026815276592969894,
-0.02350953221321106,
-0.03539834916591644,
-0.023451296612620354,
0.02341705933213234,
-0.0943855345249176,
-0.0926707535982132,
0.01003729086369276,
0.014222498051822186,
-0.02438691258430481,
0.... |
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 | [
-0.0037956126034259796,
0.10136911273002625,
-0.00002289402073074598,
-0.026815276592969894,
-0.02350953221321106,
-0.03539834916591644,
-0.023451296612620354,
0.02341705933213234,
-0.0943855345249176,
-0.0926707535982132,
0.01003729086369276,
0.014222498051822186,
-0.02438691258430481,
0.... |
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 | [
-0.0037956126034259796,
0.10136911273002625,
-0.00002289402073074598,
-0.026815276592969894,
-0.02350953221321106,
-0.03539834916591644,
-0.023451296612620354,
0.02341705933213234,
-0.0943855345249176,
-0.0926707535982132,
0.01003729086369276,
0.014222498051822186,
-0.02438691258430481,
0.... |
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 | [
-0.0037956126034259796,
0.10136911273002625,
-0.00002289402073074598,
-0.026815276592969894,
-0.02350953221321106,
-0.03539834916591644,
-0.023451296612620354,
0.02341705933213234,
-0.0943855345249176,
-0.0926707535982132,
0.01003729086369276,
0.014222498051822186,
-0.02438691258430481,
0.... |
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 | [
-0.0037956126034259796,
0.10136911273002625,
-0.00002289402073074598,
-0.026815276592969894,
-0.02350953221321106,
-0.03539834916591644,
-0.023451296612620354,
0.02341705933213234,
-0.0943855345249176,
-0.0926707535982132,
0.01003729086369276,
0.014222498051822186,
-0.02438691258430481,
0.... |
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 | [
-0.0037956126034259796,
0.10136911273002625,
-0.00002289402073074598,
-0.026815276592969894,
-0.02350953221321106,
-0.03539834916591644,
-0.023451296612620354,
0.02341705933213234,
-0.0943855345249176,
-0.0926707535982132,
0.01003729086369276,
0.014222498051822186,
-0.02438691258430481,
0.... |
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 | [
-0.0037956126034259796,
0.10136911273002625,
-0.00002289402073074598,
-0.026815276592969894,
-0.02350953221321106,
-0.03539834916591644,
-0.023451296612620354,
0.02341705933213234,
-0.0943855345249176,
-0.0926707535982132,
0.01003729086369276,
0.014222498051822186,
-0.02438691258430481,
0.... |
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 | [
-0.0037956126034259796,
0.10136911273002625,
-0.00002289402073074598,
-0.026815276592969894,
-0.02350953221321106,
-0.03539834916591644,
-0.023451296612620354,
0.02341705933213234,
-0.0943855345249176,
-0.0926707535982132,
0.01003729086369276,
0.014222498051822186,
-0.02438691258430481,
0.... |
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 | [
0.0215029064565897,
0.04574379697442055,
0.03427284583449364,
-0.031606025993824005,
0.0887727364897728,
-0.00799788162112236,
0.054400935769081116,
0.04028712958097458,
0.018635518848896027,
-0.01674189418554306,
0.05878698453307152,
0.05154503881931305,
0.006361727602779865,
0.0146548869... |
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 | [
0.0215029064565897,
0.04574379697442055,
0.03427284583449364,
-0.031606025993824005,
0.0887727364897728,
-0.00799788162112236,
0.054400935769081116,
0.04028712958097458,
0.018635518848896027,
-0.01674189418554306,
0.05878698453307152,
0.05154503881931305,
0.006361727602779865,
0.0146548869... |
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 | [
-0.040397174656391144,
-0.059224195778369904,
0.004002655856311321,
0.04708688706159592,
0.028689999133348465,
-0.031042736023664474,
0.05342070013284683,
0.058053191751241684,
0.03307934105396271,
0.0028368420898914337,
0.01794551871716976,
0.02199774980545044,
0.002480545546859503,
0.053... |
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 | [
-0.040397174656391144,
-0.059224195778369904,
0.004002655856311321,
0.04708688706159592,
0.028689999133348465,
-0.031042736023664474,
0.05342070013284683,
0.058053191751241684,
0.03307934105396271,
0.0028368420898914337,
0.01794551871716976,
0.02199774980545044,
0.002480545546859503,
0.053... |
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 | [
-0.040397174656391144,
-0.059224195778369904,
0.004002655856311321,
0.04708688706159592,
0.028689999133348465,
-0.031042736023664474,
0.05342070013284683,
0.058053191751241684,
0.03307934105396271,
0.0028368420898914337,
0.01794551871716976,
0.02199774980545044,
0.002480545546859503,
0.053... |
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 | [
-0.040397174656391144,
-0.059224195778369904,
0.004002655856311321,
0.04708688706159592,
0.028689999133348465,
-0.031042736023664474,
0.05342070013284683,
0.058053191751241684,
0.03307934105396271,
0.0028368420898914337,
0.01794551871716976,
0.02199774980545044,
0.002480545546859503,
0.053... |
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 | [
-0.040397174656391144,
-0.059224195778369904,
0.004002655856311321,
0.04708688706159592,
0.028689999133348465,
-0.031042736023664474,
0.05342070013284683,
0.058053191751241684,
0.03307934105396271,
0.0028368420898914337,
0.01794551871716976,
0.02199774980545044,
0.002480545546859503,
0.053... |
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 | [
-0.008101042360067368,
-0.0323164239525795,
0.0012556618312373757,
-0.03890734538435936,
0.091048464179039,
0.008959920145571232,
0.004287379328161478,
-0.01625790260732174,
0.057788245379924774,
-0.020593373104929924,
0.010200940072536469,
0.06890083104372025,
0.002597636077553034,
0.0414... |
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 | [
0.03846297040581703,
0.004968433640897274,
0.02026008814573288,
0.05882273614406586,
-0.008425595238804817,
-0.014625374227762222,
0.06606724858283997,
0.05794157832860947,
0.03300534561276436,
-0.015309843234717846,
-0.016727671027183533,
0.01015406847000122,
0.038733404129743576,
0.01800... |
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 | [
0.03846297040581703,
0.004968433640897274,
0.02026008814573288,
0.05882273614406586,
-0.008425595238804817,
-0.014625374227762222,
0.06606724858283997,
0.05794157832860947,
0.03300534561276436,
-0.015309843234717846,
-0.016727671027183533,
0.01015406847000122,
0.038733404129743576,
0.01800... |
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 | [
-0.014017700217664242,
0.013637460768222809,
0.014895985834300518,
-0.04874560609459877,
0.06336686760187149,
0.001705752220004797,
0.1110299751162529,
0.03425591439008713,
0.01855938695371151,
-0.011141210794448853,
0.009109011851251125,
0.06678442656993866,
0.008003403432667255,
0.005049... |
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 | [
-0.014017700217664242,
0.013637460768222809,
0.014895985834300518,
-0.04874560609459877,
0.06336686760187149,
0.001705752220004797,
0.1110299751162529,
0.03425591439008713,
0.01855938695371151,
-0.011141210794448853,
0.009109011851251125,
0.06678442656993866,
0.008003403432667255,
0.005049... |
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 | [
-0.014017700217664242,
0.013637460768222809,
0.014895985834300518,
-0.04874560609459877,
0.06336686760187149,
0.001705752220004797,
0.1110299751162529,
0.03425591439008713,
0.01855938695371151,
-0.011141210794448853,
0.009109011851251125,
0.06678442656993866,
0.008003403432667255,
0.005049... |
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 | [
-0.014017700217664242,
0.013637460768222809,
0.014895985834300518,
-0.04874560609459877,
0.06336686760187149,
0.001705752220004797,
0.1110299751162529,
0.03425591439008713,
0.01855938695371151,
-0.011141210794448853,
0.009109011851251125,
0.06678442656993866,
0.008003403432667255,
0.005049... |
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 | [
-0.014017700217664242,
0.013637460768222809,
0.014895985834300518,
-0.04874560609459877,
0.06336686760187149,
0.001705752220004797,
0.1110299751162529,
0.03425591439008713,
0.01855938695371151,
-0.011141210794448853,
0.009109011851251125,
0.06678442656993866,
0.008003403432667255,
0.005049... |
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 | [
-0.014017700217664242,
0.013637460768222809,
0.014895985834300518,
-0.04874560609459877,
0.06336686760187149,
0.001705752220004797,
0.1110299751162529,
0.03425591439008713,
0.01855938695371151,
-0.011141210794448853,
0.009109011851251125,
0.06678442656993866,
0.008003403432667255,
0.005049... |
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 | [
-0.01595672406256199,
0.040308304131031036,
0.028362972661852837,
0.0013966236729174852,
0.0801326110959053,
0.014042649418115616,
0.0012659515487030149,
0.04400979354977608,
-0.0006049783551134169,
0.024717530235648155,
0.062102895230054855,
-0.002317313104867935,
0.03296985849738121,
0.0... |
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 | [
-0.01595672406256199,
0.040308304131031036,
0.028362972661852837,
0.0013966236729174852,
0.0801326110959053,
0.014042649418115616,
0.0012659515487030149,
0.04400979354977608,
-0.0006049783551134169,
0.024717530235648155,
0.062102895230054855,
-0.002317313104867935,
0.03296985849738121,
0.0... |
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 | [
-0.01595672406256199,
0.040308304131031036,
0.028362972661852837,
0.0013966236729174852,
0.0801326110959053,
0.014042649418115616,
0.0012659515487030149,
0.04400979354977608,
-0.0006049783551134169,
0.024717530235648155,
0.062102895230054855,
-0.002317313104867935,
0.03296985849738121,
0.0... |
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 | [
-0.01595672406256199,
0.040308304131031036,
0.028362972661852837,
0.0013966236729174852,
0.0801326110959053,
0.014042649418115616,
0.0012659515487030149,
0.04400979354977608,
-0.0006049783551134169,
0.024717530235648155,
0.062102895230054855,
-0.002317313104867935,
0.03296985849738121,
0.0... |
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 | [
-0.01595672406256199,
0.040308304131031036,
0.028362972661852837,
0.0013966236729174852,
0.0801326110959053,
0.014042649418115616,
0.0012659515487030149,
0.04400979354977608,
-0.0006049783551134169,
0.024717530235648155,
0.062102895230054855,
-0.002317313104867935,
0.03296985849738121,
0.0... |
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 | [
-0.01595672406256199,
0.040308304131031036,
0.028362972661852837,
0.0013966236729174852,
0.0801326110959053,
0.014042649418115616,
0.0012659515487030149,
0.04400979354977608,
-0.0006049783551134169,
0.024717530235648155,
0.062102895230054855,
-0.002317313104867935,
0.03296985849738121,
0.0... |
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 | [
-0.01595672406256199,
0.040308304131031036,
0.028362972661852837,
0.0013966236729174852,
0.0801326110959053,
0.014042649418115616,
0.0012659515487030149,
0.04400979354977608,
-0.0006049783551134169,
0.024717530235648155,
0.062102895230054855,
-0.002317313104867935,
0.03296985849738121,
0.0... |
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 | [
-0.01595672406256199,
0.040308304131031036,
0.028362972661852837,
0.0013966236729174852,
0.0801326110959053,
0.014042649418115616,
0.0012659515487030149,
0.04400979354977608,
-0.0006049783551134169,
0.024717530235648155,
0.062102895230054855,
-0.002317313104867935,
0.03296985849738121,
0.0... |
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 | [
-0.01595672406256199,
0.040308304131031036,
0.028362972661852837,
0.0013966236729174852,
0.0801326110959053,
0.014042649418115616,
0.0012659515487030149,
0.04400979354977608,
-0.0006049783551134169,
0.024717530235648155,
0.062102895230054855,
-0.002317313104867935,
0.03296985849738121,
0.0... |
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 | [
-0.01595672406256199,
0.040308304131031036,
0.028362972661852837,
0.0013966236729174852,
0.0801326110959053,
0.014042649418115616,
0.0012659515487030149,
0.04400979354977608,
-0.0006049783551134169,
0.024717530235648155,
0.062102895230054855,
-0.002317313104867935,
0.03296985849738121,
0.0... |
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 | [
-0.01595672406256199,
0.040308304131031036,
0.028362972661852837,
0.0013966236729174852,
0.0801326110959053,
0.014042649418115616,
0.0012659515487030149,
0.04400979354977608,
-0.0006049783551134169,
0.024717530235648155,
0.062102895230054855,
-0.002317313104867935,
0.03296985849738121,
0.0... |
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 | [
-0.01595672406256199,
0.040308304131031036,
0.028362972661852837,
0.0013966236729174852,
0.0801326110959053,
0.014042649418115616,
0.0012659515487030149,
0.04400979354977608,
-0.0006049783551134169,
0.024717530235648155,
0.062102895230054855,
-0.002317313104867935,
0.03296985849738121,
0.0... |
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 | [
-0.01595672406256199,
0.040308304131031036,
0.028362972661852837,
0.0013966236729174852,
0.0801326110959053,
0.014042649418115616,
0.0012659515487030149,
0.04400979354977608,
-0.0006049783551134169,
0.024717530235648155,
0.062102895230054855,
-0.002317313104867935,
0.03296985849738121,
0.0... |
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 | [
-0.01595672406256199,
0.040308304131031036,
0.028362972661852837,
0.0013966236729174852,
0.0801326110959053,
0.014042649418115616,
0.0012659515487030149,
0.04400979354977608,
-0.0006049783551134169,
0.024717530235648155,
0.062102895230054855,
-0.002317313104867935,
0.03296985849738121,
0.0... |
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 | [
-0.01595672406256199,
0.040308304131031036,
0.028362972661852837,
0.0013966236729174852,
0.0801326110959053,
0.014042649418115616,
0.0012659515487030149,
0.04400979354977608,
-0.0006049783551134169,
0.024717530235648155,
0.062102895230054855,
-0.002317313104867935,
0.03296985849738121,
0.0... |
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 | [
-0.01595672406256199,
0.040308304131031036,
0.028362972661852837,
0.0013966236729174852,
0.0801326110959053,
0.014042649418115616,
0.0012659515487030149,
0.04400979354977608,
-0.0006049783551134169,
0.024717530235648155,
0.062102895230054855,
-0.002317313104867935,
0.03296985849738121,
0.0... |
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 | [
-0.01595672406256199,
0.040308304131031036,
0.028362972661852837,
0.0013966236729174852,
0.0801326110959053,
0.014042649418115616,
0.0012659515487030149,
0.04400979354977608,
-0.0006049783551134169,
0.024717530235648155,
0.062102895230054855,
-0.002317313104867935,
0.03296985849738121,
0.0... |
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 | [
-0.01595672406256199,
0.040308304131031036,
0.028362972661852837,
0.0013966236729174852,
0.0801326110959053,
0.014042649418115616,
0.0012659515487030149,
0.04400979354977608,
-0.0006049783551134169,
0.024717530235648155,
0.062102895230054855,
-0.002317313104867935,
0.03296985849738121,
0.0... |
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 | [
-0.01595672406256199,
0.040308304131031036,
0.028362972661852837,
0.0013966236729174852,
0.0801326110959053,
0.014042649418115616,
0.0012659515487030149,
0.04400979354977608,
-0.0006049783551134169,
0.024717530235648155,
0.062102895230054855,
-0.002317313104867935,
0.03296985849738121,
0.0... |
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