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/27737 | [
"Needs Triage"
] | Clarify docstring on HistGradientBoostingRegressor regarding monotonic_cst
Hi scikit team! Enormous fan of all you do 🙏
I'm thinking about opening a small PR and would love your thoughts.
The docs/docstring on `HistGradientBoostingRegressor` [have the following note](https://github.com/scikit-learn/scikit-lear... | 27,737 | [
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0.... |
https://github.com/scikit-learn/scikit-learn/issues/27726 | [
"Bug",
"Needs Triage"
] | Wrong NDCG\DCG calculation
### Describe the bug
I try to calculate NDCG of a binary recommendations.
I assume the two lists are ordered by relevance.
So, `y_true=[1,1,1,1]` means that all the recommendations are valid.
and `y_pred=[1,1,1,0]` means that all the top-3 recommendations are valid, but the last one is... | 27,726 | [
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0.020122217014431953,
0.05463627725839615,
-0.024... |
https://github.com/scikit-learn/scikit-learn/issues/27726 | [
"Bug",
"Needs Triage"
] | Wrong NDCG\DCG calculation
### Describe the bug
I try to calculate NDCG of a binary recommendations.
I assume the two lists are ordered by relevance.
So, `y_true=[1,1,1,1]` means that all the recommendations are valid.
and `y_pred=[1,1,1,0]` means that all the top-3 recommendations are valid, but the last one is... | 27,726 | [
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0.018500763922929764,
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0.03258569538593292,
0.020369378849864006,
0.04908512532711029,
-0.00... |
https://github.com/scikit-learn/scikit-learn/issues/27725 | [
"Bug",
"Blocker"
] | BUG: pytest giving UnicodeDecodeError on Windows machine
### Describe the bug
When running the test suite on my Windows machine, I get the following error:
```
UnicodeDecodeError: 'gbk' codec can't decode byte 0xb8 in position 4836: illegal multibyte sequence
```
https://github.com/scikit-learn/scikit-learn/b... | 27,725 | [
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0.028442351147532463,
0.06316187977790833,
0.01192103885114193,
-0.02977270446717739,
0.019608862698078156,
0.021752042695879936,
-0.010939721018075943,
-0.0163... |
https://github.com/scikit-learn/scikit-learn/issues/27725 | [
"Bug",
"Blocker"
] | BUG: pytest giving UnicodeDecodeError on Windows machine
### Describe the bug
When running the test suite on my Windows machine, I get the following error:
```
UnicodeDecodeError: 'gbk' codec can't decode byte 0xb8 in position 4836: illegal multibyte sequence
```
https://github.com/scikit-learn/scikit-learn/b... | 27,725 | [
0.024532834067940712,
0.05417703464627266,
-0.013465345837175846,
0.004572926089167595,
0.09512337297201157,
0.04906098172068596,
0.028442351147532463,
0.06316187977790833,
0.01192103885114193,
-0.02977270446717739,
0.019608862698078156,
0.021752042695879936,
-0.010939721018075943,
-0.0163... |
https://github.com/scikit-learn/scikit-learn/issues/27725 | [
"Bug",
"Blocker"
] | BUG: pytest giving UnicodeDecodeError on Windows machine
### Describe the bug
When running the test suite on my Windows machine, I get the following error:
```
UnicodeDecodeError: 'gbk' codec can't decode byte 0xb8 in position 4836: illegal multibyte sequence
```
https://github.com/scikit-learn/scikit-learn/b... | 27,725 | [
0.024532834067940712,
0.05417703464627266,
-0.013465345837175846,
0.004572926089167595,
0.09512337297201157,
0.04906098172068596,
0.028442351147532463,
0.06316187977790833,
0.01192103885114193,
-0.02977270446717739,
0.019608862698078156,
0.021752042695879936,
-0.010939721018075943,
-0.0163... |
https://github.com/scikit-learn/scikit-learn/issues/27725 | [
"Bug",
"Blocker"
] | BUG: pytest giving UnicodeDecodeError on Windows machine
### Describe the bug
When running the test suite on my Windows machine, I get the following error:
```
UnicodeDecodeError: 'gbk' codec can't decode byte 0xb8 in position 4836: illegal multibyte sequence
```
https://github.com/scikit-learn/scikit-learn/b... | 27,725 | [
0.024532834067940712,
0.05417703464627266,
-0.013465345837175846,
0.004572926089167595,
0.09512337297201157,
0.04906098172068596,
0.028442351147532463,
0.06316187977790833,
0.01192103885114193,
-0.02977270446717739,
0.019608862698078156,
0.021752042695879936,
-0.010939721018075943,
-0.0163... |
https://github.com/scikit-learn/scikit-learn/issues/27725 | [
"Bug",
"Blocker"
] | BUG: pytest giving UnicodeDecodeError on Windows machine
### Describe the bug
When running the test suite on my Windows machine, I get the following error:
```
UnicodeDecodeError: 'gbk' codec can't decode byte 0xb8 in position 4836: illegal multibyte sequence
```
https://github.com/scikit-learn/scikit-learn/b... | 27,725 | [
0.024532834067940712,
0.05417703464627266,
-0.013465345837175846,
0.004572926089167595,
0.09512337297201157,
0.04906098172068596,
0.028442351147532463,
0.06316187977790833,
0.01192103885114193,
-0.02977270446717739,
0.019608862698078156,
0.021752042695879936,
-0.010939721018075943,
-0.0163... |
https://github.com/scikit-learn/scikit-learn/issues/27725 | [
"Bug",
"Blocker"
] | BUG: pytest giving UnicodeDecodeError on Windows machine
### Describe the bug
When running the test suite on my Windows machine, I get the following error:
```
UnicodeDecodeError: 'gbk' codec can't decode byte 0xb8 in position 4836: illegal multibyte sequence
```
https://github.com/scikit-learn/scikit-learn/b... | 27,725 | [
0.024532834067940712,
0.05417703464627266,
-0.013465345837175846,
0.004572926089167595,
0.09512337297201157,
0.04906098172068596,
0.028442351147532463,
0.06316187977790833,
0.01192103885114193,
-0.02977270446717739,
0.019608862698078156,
0.021752042695879936,
-0.010939721018075943,
-0.0163... |
https://github.com/scikit-learn/scikit-learn/issues/27725 | [
"Bug",
"Blocker"
] | BUG: pytest giving UnicodeDecodeError on Windows machine
### Describe the bug
When running the test suite on my Windows machine, I get the following error:
```
UnicodeDecodeError: 'gbk' codec can't decode byte 0xb8 in position 4836: illegal multibyte sequence
```
https://github.com/scikit-learn/scikit-learn/b... | 27,725 | [
0.024532834067940712,
0.05417703464627266,
-0.013465345837175846,
0.004572926089167595,
0.09512337297201157,
0.04906098172068596,
0.028442351147532463,
0.06316187977790833,
0.01192103885114193,
-0.02977270446717739,
0.019608862698078156,
0.021752042695879936,
-0.010939721018075943,
-0.0163... |
https://github.com/scikit-learn/scikit-learn/issues/27711 | [
"Bug"
] | BUG: Buffer dtype mismatch on Windows and NumPy 2.0
### Describe the bug
Recent [Azure CI failure for MNE-Python](https://dev.azure.com/mne-tools/mne-python/_build/results?buildId=27722&view=logs&jobId=dded70eb-633c-5c42-e995-a7f8d1f99d91&j=dded70eb-633c-5c42-e995-a7f8d1f99d91&t=02d70add-cf2e-52ae-1ea0-298f1e5f37ea) ... | 27,711 | [
0.00958641804754734,
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0.0577390156686306,
0.031682465225458145,
0.0034855720587074757,
0.05336849391460419,
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-0.01958053559064865,
0.011692916974425316,
0.003128645708784461,
-0.017242394387722015,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27711 | [
"Bug"
] | BUG: Buffer dtype mismatch on Windows and NumPy 2.0
### Describe the bug
Recent [Azure CI failure for MNE-Python](https://dev.azure.com/mne-tools/mne-python/_build/results?buildId=27722&view=logs&jobId=dded70eb-633c-5c42-e995-a7f8d1f99d91&j=dded70eb-633c-5c42-e995-a7f8d1f99d91&t=02d70add-cf2e-52ae-1ea0-298f1e5f37ea) ... | 27,711 | [
0.00958641804754734,
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0.0577390156686306,
0.031682465225458145,
0.0034855720587074757,
0.05336849391460419,
-0.026641402393579483,
-0.01958053559064865,
0.011692916974425316,
0.003128645708784461,
-0.017242394387722015,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27711 | [
"Bug"
] | BUG: Buffer dtype mismatch on Windows and NumPy 2.0
### Describe the bug
Recent [Azure CI failure for MNE-Python](https://dev.azure.com/mne-tools/mne-python/_build/results?buildId=27722&view=logs&jobId=dded70eb-633c-5c42-e995-a7f8d1f99d91&j=dded70eb-633c-5c42-e995-a7f8d1f99d91&t=02d70add-cf2e-52ae-1ea0-298f1e5f37ea) ... | 27,711 | [
0.00958641804754734,
0.025704868137836456,
0.011611191555857658,
-0.0017574313096702099,
0.0577390156686306,
0.031682465225458145,
0.0034855720587074757,
0.05336849391460419,
-0.026641402393579483,
-0.01958053559064865,
0.011692916974425316,
0.003128645708784461,
-0.017242394387722015,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27711 | [
"Bug"
] | BUG: Buffer dtype mismatch on Windows and NumPy 2.0
### Describe the bug
Recent [Azure CI failure for MNE-Python](https://dev.azure.com/mne-tools/mne-python/_build/results?buildId=27722&view=logs&jobId=dded70eb-633c-5c42-e995-a7f8d1f99d91&j=dded70eb-633c-5c42-e995-a7f8d1f99d91&t=02d70add-cf2e-52ae-1ea0-298f1e5f37ea) ... | 27,711 | [
0.00958641804754734,
0.025704868137836456,
0.011611191555857658,
-0.0017574313096702099,
0.0577390156686306,
0.031682465225458145,
0.0034855720587074757,
0.05336849391460419,
-0.026641402393579483,
-0.01958053559064865,
0.011692916974425316,
0.003128645708784461,
-0.017242394387722015,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27711 | [
"Bug"
] | BUG: Buffer dtype mismatch on Windows and NumPy 2.0
### Describe the bug
Recent [Azure CI failure for MNE-Python](https://dev.azure.com/mne-tools/mne-python/_build/results?buildId=27722&view=logs&jobId=dded70eb-633c-5c42-e995-a7f8d1f99d91&j=dded70eb-633c-5c42-e995-a7f8d1f99d91&t=02d70add-cf2e-52ae-1ea0-298f1e5f37ea) ... | 27,711 | [
0.00958641804754734,
0.025704868137836456,
0.011611191555857658,
-0.0017574313096702099,
0.0577390156686306,
0.031682465225458145,
0.0034855720587074757,
0.05336849391460419,
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-0.01958053559064865,
0.011692916974425316,
0.003128645708784461,
-0.017242394387722015,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27711 | [
"Bug"
] | BUG: Buffer dtype mismatch on Windows and NumPy 2.0
### Describe the bug
Recent [Azure CI failure for MNE-Python](https://dev.azure.com/mne-tools/mne-python/_build/results?buildId=27722&view=logs&jobId=dded70eb-633c-5c42-e995-a7f8d1f99d91&j=dded70eb-633c-5c42-e995-a7f8d1f99d91&t=02d70add-cf2e-52ae-1ea0-298f1e5f37ea) ... | 27,711 | [
0.00958641804754734,
0.025704868137836456,
0.011611191555857658,
-0.0017574313096702099,
0.0577390156686306,
0.031682465225458145,
0.0034855720587074757,
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-0.01958053559064865,
0.011692916974425316,
0.003128645708784461,
-0.017242394387722015,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27711 | [
"Bug"
] | BUG: Buffer dtype mismatch on Windows and NumPy 2.0
### Describe the bug
Recent [Azure CI failure for MNE-Python](https://dev.azure.com/mne-tools/mne-python/_build/results?buildId=27722&view=logs&jobId=dded70eb-633c-5c42-e995-a7f8d1f99d91&j=dded70eb-633c-5c42-e995-a7f8d1f99d91&t=02d70add-cf2e-52ae-1ea0-298f1e5f37ea) ... | 27,711 | [
0.00958641804754734,
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0.0577390156686306,
0.031682465225458145,
0.0034855720587074757,
0.05336849391460419,
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-0.01958053559064865,
0.011692916974425316,
0.003128645708784461,
-0.017242394387722015,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27711 | [
"Bug"
] | BUG: Buffer dtype mismatch on Windows and NumPy 2.0
### Describe the bug
Recent [Azure CI failure for MNE-Python](https://dev.azure.com/mne-tools/mne-python/_build/results?buildId=27722&view=logs&jobId=dded70eb-633c-5c42-e995-a7f8d1f99d91&j=dded70eb-633c-5c42-e995-a7f8d1f99d91&t=02d70add-cf2e-52ae-1ea0-298f1e5f37ea) ... | 27,711 | [
0.00958641804754734,
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0.0577390156686306,
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0.0034855720587074757,
0.05336849391460419,
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0.011692916974425316,
0.003128645708784461,
-0.017242394387722015,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27708 | [
"Bug",
"Needs Triage"
] | Iris Dataset Wrong Values.
### Describe the bug
There are three incorrect values in the Iris dataset, as follows:
(Instances from: https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/datasets/data/iris.csv)
In Row 36, the 4th feature is recorded as 0.2 instead of 0.1.
In Row 39, the 2nd feature is n... | 27,708 | [
-0.012605090625584126,
-0.044298164546489716,
-0.007455558516085148,
0.04104331135749817,
0.01682286523282528,
0.008930578827857971,
0.04684576019644737,
0.006097298115491867,
0.004504629876464605,
0.032546088099479675,
-0.028211986646056175,
0.03173306584358215,
0.07691343873739243,
0.055... |
https://github.com/scikit-learn/scikit-learn/issues/27708 | [
"Bug",
"Needs Triage"
] | Iris Dataset Wrong Values.
### Describe the bug
There are three incorrect values in the Iris dataset, as follows:
(Instances from: https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/datasets/data/iris.csv)
In Row 36, the 4th feature is recorded as 0.2 instead of 0.1.
In Row 39, the 2nd feature is n... | 27,708 | [
-0.012605090625584126,
-0.044298164546489716,
-0.007455558516085148,
0.04104331135749817,
0.01682286523282528,
0.008930578827857971,
0.04684576019644737,
0.006097298115491867,
0.004504629876464605,
0.032546088099479675,
-0.028211986646056175,
0.03173306584358215,
0.07691343873739243,
0.055... |
https://github.com/scikit-learn/scikit-learn/issues/27708 | [
"Bug",
"Needs Triage"
] | Iris Dataset Wrong Values.
### Describe the bug
There are three incorrect values in the Iris dataset, as follows:
(Instances from: https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/datasets/data/iris.csv)
In Row 36, the 4th feature is recorded as 0.2 instead of 0.1.
In Row 39, the 2nd feature is n... | 27,708 | [
-0.012605090625584126,
-0.044298164546489716,
-0.007455558516085148,
0.04104331135749817,
0.01682286523282528,
0.008930578827857971,
0.04684576019644737,
0.006097298115491867,
0.004504629876464605,
0.032546088099479675,
-0.028211986646056175,
0.03173306584358215,
0.07691343873739243,
0.055... |
https://github.com/scikit-learn/scikit-learn/issues/27703 | [
"New Feature",
"Needs Triage"
] | Add clustering score?
### Describe the workflow you want to enable
I want to reproduce a paper that uses clustering score to measure the goodness of clustering.
I think they should be using adjusted rand index, but they use cluster accuracy.
### Describe your proposed solution
Something roughly like this:
... | 27,703 | [
-0.051074400544166565,
0.0075258975848555565,
0.018285715952515602,
-0.02070501632988453,
0.002532485406845808,
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0.01606500707566738,
0.018667099997401237,
0.0607280433177948,
0.006667464505881071,
-0.004422968253493309,
0.043457403779029846,
-0.00434922706335783,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27703 | [
"New Feature",
"Needs Triage"
] | Add clustering score?
### Describe the workflow you want to enable
I want to reproduce a paper that uses clustering score to measure the goodness of clustering.
I think they should be using adjusted rand index, but they use cluster accuracy.
### Describe your proposed solution
Something roughly like this:
... | 27,703 | [
-0.053178757429122925,
0.0038694010581821203,
0.019678007811307907,
-0.021429773420095444,
0.009174779057502747,
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0.02067500539124012,
0.010864191688597202,
0.0655871331691742,
0.00675355177372694,
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0.048507582396268845,
-0.001617760630324483,
0... |
https://github.com/scikit-learn/scikit-learn/issues/27703 | [
"New Feature",
"Needs Triage"
] | Add clustering score?
### Describe the workflow you want to enable
I want to reproduce a paper that uses clustering score to measure the goodness of clustering.
I think they should be using adjusted rand index, but they use cluster accuracy.
### Describe your proposed solution
Something roughly like this:
... | 27,703 | [
-0.04274052381515503,
0.011416234076023102,
0.02229253388941288,
-0.01945612020790577,
0.005884980317205191,
-0.020541111007332802,
0.018377123400568962,
0.021150479093194008,
0.06233907863497734,
0.005544923711568117,
-0.011395084671676159,
0.04430973157286644,
-0.005873072426766157,
0.06... |
https://github.com/scikit-learn/scikit-learn/issues/27696 | [
"Documentation"
] | DecisionTreeClassifier does not support 'auto' as an option for max_features
### Describe the bug
I was using scikit-learn version 1.3.2, trying to fit a DecisionTreeClassifier to my data, and I got an error that the option 'auto' was invalid.
The [documentation](https://scikit-learn.org/1.3/modules/generated/skle... | 27,696 | [
0.003685011761263013,
-0.037602413445711136,
0.007076484616845846,
-0.02720761112868786,
0.06207045912742615,
-0.013287244364619255,
0.011201683431863785,
0.01365023571997881,
0.0004038047627545893,
-0.050708819180727005,
0.06439155340194702,
0.07695562392473221,
-0.006923222914338112,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27695 | [
"Bug"
] | pipeline using FunctionTransformer with feature_names_out=... fails when applied to dataframe argument
### Describe the bug
(based on this stackoverflow question: https://stackoverflow.com/questions/77379286/sklearn-pipeline-get-feature-names-out-fails-unless-dataframe-has-matching-ren/77396145#77396145)
I have ... | 27,695 | [
0.031757108867168427,
0.021868307143449783,
0.03685556724667549,
-0.027300596237182617,
0.05987691879272461,
-0.00393272191286087,
0.05693276226520538,
-0.011356106959283352,
-0.028047829866409302,
0.015449084341526031,
0.03494423255324364,
-0.007010637316852808,
0.047532789409160614,
0.04... |
https://github.com/scikit-learn/scikit-learn/issues/27695 | [
"Bug"
] | pipeline using FunctionTransformer with feature_names_out=... fails when applied to dataframe argument
### Describe the bug
(based on this stackoverflow question: https://stackoverflow.com/questions/77379286/sklearn-pipeline-get-feature-names-out-fails-unless-dataframe-has-matching-ren/77396145#77396145)
I have ... | 27,695 | [
0.031757108867168427,
0.021868307143449783,
0.03685556724667549,
-0.027300596237182617,
0.05987691879272461,
-0.00393272191286087,
0.05693276226520538,
-0.011356106959283352,
-0.028047829866409302,
0.015449084341526031,
0.03494423255324364,
-0.007010637316852808,
0.047532789409160614,
0.04... |
https://github.com/scikit-learn/scikit-learn/issues/27695 | [
"Bug"
] | pipeline using FunctionTransformer with feature_names_out=... fails when applied to dataframe argument
### Describe the bug
(based on this stackoverflow question: https://stackoverflow.com/questions/77379286/sklearn-pipeline-get-feature-names-out-fails-unless-dataframe-has-matching-ren/77396145#77396145)
I have ... | 27,695 | [
0.031757108867168427,
0.021868307143449783,
0.03685556724667549,
-0.027300596237182617,
0.05987691879272461,
-0.00393272191286087,
0.05693276226520538,
-0.011356106959283352,
-0.028047829866409302,
0.015449084341526031,
0.03494423255324364,
-0.007010637316852808,
0.047532789409160614,
0.04... |
https://github.com/scikit-learn/scikit-learn/issues/27695 | [
"Bug"
] | pipeline using FunctionTransformer with feature_names_out=... fails when applied to dataframe argument
### Describe the bug
(based on this stackoverflow question: https://stackoverflow.com/questions/77379286/sklearn-pipeline-get-feature-names-out-fails-unless-dataframe-has-matching-ren/77396145#77396145)
I have ... | 27,695 | [
0.031757108867168427,
0.021868307143449783,
0.03685556724667549,
-0.027300596237182617,
0.05987691879272461,
-0.00393272191286087,
0.05693276226520538,
-0.011356106959283352,
-0.028047829866409302,
0.015449084341526031,
0.03494423255324364,
-0.007010637316852808,
0.047532789409160614,
0.04... |
https://github.com/scikit-learn/scikit-learn/issues/27695 | [
"Bug"
] | pipeline using FunctionTransformer with feature_names_out=... fails when applied to dataframe argument
### Describe the bug
(based on this stackoverflow question: https://stackoverflow.com/questions/77379286/sklearn-pipeline-get-feature-names-out-fails-unless-dataframe-has-matching-ren/77396145#77396145)
I have ... | 27,695 | [
0.031757108867168427,
0.021868307143449783,
0.03685556724667549,
-0.027300596237182617,
0.05987691879272461,
-0.00393272191286087,
0.05693276226520538,
-0.011356106959283352,
-0.028047829866409302,
0.015449084341526031,
0.03494423255324364,
-0.007010637316852808,
0.047532789409160614,
0.04... |
https://github.com/scikit-learn/scikit-learn/issues/27695 | [
"Bug"
] | pipeline using FunctionTransformer with feature_names_out=... fails when applied to dataframe argument
### Describe the bug
(based on this stackoverflow question: https://stackoverflow.com/questions/77379286/sklearn-pipeline-get-feature-names-out-fails-unless-dataframe-has-matching-ren/77396145#77396145)
I have ... | 27,695 | [
0.031757108867168427,
0.021868307143449783,
0.03685556724667549,
-0.027300596237182617,
0.05987691879272461,
-0.00393272191286087,
0.05693276226520538,
-0.011356106959283352,
-0.028047829866409302,
0.015449084341526031,
0.03494423255324364,
-0.007010637316852808,
0.047532789409160614,
0.04... |
https://github.com/scikit-learn/scikit-learn/issues/27695 | [
"Bug"
] | pipeline using FunctionTransformer with feature_names_out=... fails when applied to dataframe argument
### Describe the bug
(based on this stackoverflow question: https://stackoverflow.com/questions/77379286/sklearn-pipeline-get-feature-names-out-fails-unless-dataframe-has-matching-ren/77396145#77396145)
I have ... | 27,695 | [
0.031757108867168427,
0.021868307143449783,
0.03685556724667549,
-0.027300596237182617,
0.05987691879272461,
-0.00393272191286087,
0.05693276226520538,
-0.011356106959283352,
-0.028047829866409302,
0.015449084341526031,
0.03494423255324364,
-0.007010637316852808,
0.047532789409160614,
0.04... |
https://github.com/scikit-learn/scikit-learn/issues/27690 | [
"Bug",
"Needs Triage"
] | scikit learn project runnable on pycharm but not on vscode?
### Describe the bug
Hello,
I recently created a python project using scikit learn on PyCharm. First, I followed the sample code on official website
`from sklearn import linear_model` and moved on to rest of the code.
Then I tried to run it on vscode,... | 27,690 | [
0.01765679195523262,
-0.05573726445436478,
0.0024044380988925695,
-0.01412628311663866,
0.08897995948791504,
0.04002821445465088,
0.05037007853388786,
-0.004582032561302185,
0.09048718214035034,
0.012017179280519485,
0.021327560767531395,
0.10318539291620255,
-0.009711752645671368,
0.05011... |
https://github.com/scikit-learn/scikit-learn/issues/27690 | [
"Bug",
"Needs Triage"
] | scikit learn project runnable on pycharm but not on vscode?
### Describe the bug
Hello,
I recently created a python project using scikit learn on PyCharm. First, I followed the sample code on official website
`from sklearn import linear_model` and moved on to rest of the code.
Then I tried to run it on vscode,... | 27,690 | [
0.01765679195523262,
-0.05573726445436478,
0.0024044380988925695,
-0.01412628311663866,
0.08897995948791504,
0.04002821445465088,
0.05037007853388786,
-0.004582032561302185,
0.09048718214035034,
0.012017179280519485,
0.021327560767531395,
0.10318539291620255,
-0.009711752645671368,
0.05011... |
https://github.com/scikit-learn/scikit-learn/issues/27690 | [
"Bug",
"Needs Triage"
] | scikit learn project runnable on pycharm but not on vscode?
### Describe the bug
Hello,
I recently created a python project using scikit learn on PyCharm. First, I followed the sample code on official website
`from sklearn import linear_model` and moved on to rest of the code.
Then I tried to run it on vscode,... | 27,690 | [
0.01765679195523262,
-0.05573726445436478,
0.0024044380988925695,
-0.01412628311663866,
0.08897995948791504,
0.04002821445465088,
0.05037007853388786,
-0.004582032561302185,
0.09048718214035034,
0.012017179280519485,
0.021327560767531395,
0.10318539291620255,
-0.009711752645671368,
0.05011... |
https://github.com/scikit-learn/scikit-learn/issues/27690 | [
"Bug",
"Needs Triage"
] | scikit learn project runnable on pycharm but not on vscode?
### Describe the bug
Hello,
I recently created a python project using scikit learn on PyCharm. First, I followed the sample code on official website
`from sklearn import linear_model` and moved on to rest of the code.
Then I tried to run it on vscode,... | 27,690 | [
0.01765679195523262,
-0.05573726445436478,
0.0024044380988925695,
-0.01412628311663866,
0.08897995948791504,
0.04002821445465088,
0.05037007853388786,
-0.004582032561302185,
0.09048718214035034,
0.012017179280519485,
0.021327560767531395,
0.10318539291620255,
-0.009711752645671368,
0.05011... |
https://github.com/scikit-learn/scikit-learn/issues/27690 | [
"Bug",
"Needs Triage"
] | scikit learn project runnable on pycharm but not on vscode?
### Describe the bug
Hello,
I recently created a python project using scikit learn on PyCharm. First, I followed the sample code on official website
`from sklearn import linear_model` and moved on to rest of the code.
Then I tried to run it on vscode,... | 27,690 | [
0.01765679195523262,
-0.05573726445436478,
0.0024044380988925695,
-0.01412628311663866,
0.08897995948791504,
0.04002821445465088,
0.05037007853388786,
-0.004582032561302185,
0.09048718214035034,
0.012017179280519485,
0.021327560767531395,
0.10318539291620255,
-0.009711752645671368,
0.05011... |
https://github.com/scikit-learn/scikit-learn/issues/27683 | [
"Bug",
"Documentation"
] | Typo at documentation of RandomForestRegressor
Hello,
is there a typo at the doc. description of the RandomForestRegressor? It states that the fitting of the data is done using "classifying decision trees" where it should be saying *regressor* decision trees.
see:
https://github.com/scikit-learn/scikit-learn/bl... | 27,683 | [
0.06466273218393326,
-0.016754822805523872,
0.0008132391958497465,
0.0043836128897964954,
-0.018799254670739174,
0.007937216199934483,
0.043989695608615875,
-0.049940336495637894,
0.0067596654407680035,
-0.016639864072203636,
0.06125074252486229,
-0.027763132005929947,
0.06733120232820511,
... |
https://github.com/scikit-learn/scikit-learn/issues/27682 | [
"good first issue",
"cython"
] | MAINT Directly `cimport` interfaces from `std::algorithm`
Some Cython implementations use interfaces from the standard library of C++, namely `std::algorithm::move` and `std::algorithm::fill` from [`std::algorithm`](https://en.cppreference.com/w/cpp/algorithm/).
Before Cython 3, those interfaces had to be imported ... | 27,682 | [
-0.027021853253245354,
0.024207884445786476,
-0.04765452817082405,
0.009836739860475063,
0.011132398620247841,
0.01018443237990141,
0.03587816655635834,
0.004708230495452881,
-0.017265675589442253,
-0.05485953390598297,
0.014312051236629486,
0.03967111185193062,
-0.003561903489753604,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27682 | [
"good first issue",
"cython"
] | MAINT Directly `cimport` interfaces from `std::algorithm`
Some Cython implementations use interfaces from the standard library of C++, namely `std::algorithm::move` and `std::algorithm::fill` from [`std::algorithm`](https://en.cppreference.com/w/cpp/algorithm/).
Before Cython 3, those interfaces had to be imported ... | 27,682 | [
-0.027021853253245354,
0.024207884445786476,
-0.04765452817082405,
0.009836739860475063,
0.011132398620247841,
0.01018443237990141,
0.03587816655635834,
0.004708230495452881,
-0.017265675589442253,
-0.05485953390598297,
0.014312051236629486,
0.03967111185193062,
-0.003561903489753604,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27682 | [
"good first issue",
"cython"
] | MAINT Directly `cimport` interfaces from `std::algorithm`
Some Cython implementations use interfaces from the standard library of C++, namely `std::algorithm::move` and `std::algorithm::fill` from [`std::algorithm`](https://en.cppreference.com/w/cpp/algorithm/).
Before Cython 3, those interfaces had to be imported ... | 27,682 | [
-0.027021853253245354,
0.024207884445786476,
-0.04765452817082405,
0.009836739860475063,
0.011132398620247841,
0.01018443237990141,
0.03587816655635834,
0.004708230495452881,
-0.017265675589442253,
-0.05485953390598297,
0.014312051236629486,
0.03967111185193062,
-0.003561903489753604,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27682 | [
"good first issue",
"cython"
] | MAINT Directly `cimport` interfaces from `std::algorithm`
Some Cython implementations use interfaces from the standard library of C++, namely `std::algorithm::move` and `std::algorithm::fill` from [`std::algorithm`](https://en.cppreference.com/w/cpp/algorithm/).
Before Cython 3, those interfaces had to be imported ... | 27,682 | [
-0.027021853253245354,
0.024207884445786476,
-0.04765452817082405,
0.009836739860475063,
0.011132398620247841,
0.01018443237990141,
0.03587816655635834,
0.004708230495452881,
-0.017265675589442253,
-0.05485953390598297,
0.014312051236629486,
0.03967111185193062,
-0.003561903489753604,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27682 | [
"good first issue",
"cython"
] | MAINT Directly `cimport` interfaces from `std::algorithm`
Some Cython implementations use interfaces from the standard library of C++, namely `std::algorithm::move` and `std::algorithm::fill` from [`std::algorithm`](https://en.cppreference.com/w/cpp/algorithm/).
Before Cython 3, those interfaces had to be imported ... | 27,682 | [
-0.027021853253245354,
0.024207884445786476,
-0.04765452817082405,
0.009836739860475063,
0.011132398620247841,
0.01018443237990141,
0.03587816655635834,
0.004708230495452881,
-0.017265675589442253,
-0.05485953390598297,
0.014312051236629486,
0.03967111185193062,
-0.003561903489753604,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27682 | [
"good first issue",
"cython"
] | MAINT Directly `cimport` interfaces from `std::algorithm`
Some Cython implementations use interfaces from the standard library of C++, namely `std::algorithm::move` and `std::algorithm::fill` from [`std::algorithm`](https://en.cppreference.com/w/cpp/algorithm/).
Before Cython 3, those interfaces had to be imported ... | 27,682 | [
-0.027021853253245354,
0.024207884445786476,
-0.04765452817082405,
0.009836739860475063,
0.011132398620247841,
0.01018443237990141,
0.03587816655635834,
0.004708230495452881,
-0.017265675589442253,
-0.05485953390598297,
0.014312051236629486,
0.03967111185193062,
-0.003561903489753604,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27682 | [
"good first issue",
"cython"
] | MAINT Directly `cimport` interfaces from `std::algorithm`
Some Cython implementations use interfaces from the standard library of C++, namely `std::algorithm::move` and `std::algorithm::fill` from [`std::algorithm`](https://en.cppreference.com/w/cpp/algorithm/).
Before Cython 3, those interfaces had to be imported ... | 27,682 | [
-0.027021853253245354,
0.024207884445786476,
-0.04765452817082405,
0.009836739860475063,
0.011132398620247841,
0.01018443237990141,
0.03587816655635834,
0.004708230495452881,
-0.017265675589442253,
-0.05485953390598297,
0.014312051236629486,
0.03967111185193062,
-0.003561903489753604,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27682 | [
"good first issue",
"cython"
] | MAINT Directly `cimport` interfaces from `std::algorithm`
Some Cython implementations use interfaces from the standard library of C++, namely `std::algorithm::move` and `std::algorithm::fill` from [`std::algorithm`](https://en.cppreference.com/w/cpp/algorithm/).
Before Cython 3, those interfaces had to be imported ... | 27,682 | [
-0.027021853253245354,
0.024207884445786476,
-0.04765452817082405,
0.009836739860475063,
0.011132398620247841,
0.01018443237990141,
0.03587816655635834,
0.004708230495452881,
-0.017265675589442253,
-0.05485953390598297,
0.014312051236629486,
0.03967111185193062,
-0.003561903489753604,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27682 | [
"good first issue",
"cython"
] | MAINT Directly `cimport` interfaces from `std::algorithm`
Some Cython implementations use interfaces from the standard library of C++, namely `std::algorithm::move` and `std::algorithm::fill` from [`std::algorithm`](https://en.cppreference.com/w/cpp/algorithm/).
Before Cython 3, those interfaces had to be imported ... | 27,682 | [
-0.027021853253245354,
0.024207884445786476,
-0.04765452817082405,
0.009836739860475063,
0.011132398620247841,
0.01018443237990141,
0.03587816655635834,
0.004708230495452881,
-0.017265675589442253,
-0.05485953390598297,
0.014312051236629486,
0.03967111185193062,
-0.003561903489753604,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27682 | [
"good first issue",
"cython"
] | MAINT Directly `cimport` interfaces from `std::algorithm`
Some Cython implementations use interfaces from the standard library of C++, namely `std::algorithm::move` and `std::algorithm::fill` from [`std::algorithm`](https://en.cppreference.com/w/cpp/algorithm/).
Before Cython 3, those interfaces had to be imported ... | 27,682 | [
-0.027021853253245354,
0.024207884445786476,
-0.04765452817082405,
0.009836739860475063,
0.011132398620247841,
0.01018443237990141,
0.03587816655635834,
0.004708230495452881,
-0.017265675589442253,
-0.05485953390598297,
0.014312051236629486,
0.03967111185193062,
-0.003561903489753604,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27682 | [
"good first issue",
"cython"
] | MAINT Directly `cimport` interfaces from `std::algorithm`
Some Cython implementations use interfaces from the standard library of C++, namely `std::algorithm::move` and `std::algorithm::fill` from [`std::algorithm`](https://en.cppreference.com/w/cpp/algorithm/).
Before Cython 3, those interfaces had to be imported ... | 27,682 | [
-0.027021853253245354,
0.024207884445786476,
-0.04765452817082405,
0.009836739860475063,
0.011132398620247841,
0.01018443237990141,
0.03587816655635834,
0.004708230495452881,
-0.017265675589442253,
-0.05485953390598297,
0.014312051236629486,
0.03967111185193062,
-0.003561903489753604,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27682 | [
"good first issue",
"cython"
] | MAINT Directly `cimport` interfaces from `std::algorithm`
Some Cython implementations use interfaces from the standard library of C++, namely `std::algorithm::move` and `std::algorithm::fill` from [`std::algorithm`](https://en.cppreference.com/w/cpp/algorithm/).
Before Cython 3, those interfaces had to be imported ... | 27,682 | [
-0.027021853253245354,
0.024207884445786476,
-0.04765452817082405,
0.009836739860475063,
0.011132398620247841,
0.01018443237990141,
0.03587816655635834,
0.004708230495452881,
-0.017265675589442253,
-0.05485953390598297,
0.014312051236629486,
0.03967111185193062,
-0.003561903489753604,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27682 | [
"good first issue",
"cython"
] | MAINT Directly `cimport` interfaces from `std::algorithm`
Some Cython implementations use interfaces from the standard library of C++, namely `std::algorithm::move` and `std::algorithm::fill` from [`std::algorithm`](https://en.cppreference.com/w/cpp/algorithm/).
Before Cython 3, those interfaces had to be imported ... | 27,682 | [
-0.027021853253245354,
0.024207884445786476,
-0.04765452817082405,
0.009836739860475063,
0.011132398620247841,
0.01018443237990141,
0.03587816655635834,
0.004708230495452881,
-0.017265675589442253,
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https://github.com/scikit-learn/scikit-learn/issues/27682 | [
"good first issue",
"cython"
] | MAINT Directly `cimport` interfaces from `std::algorithm`
Some Cython implementations use interfaces from the standard library of C++, namely `std::algorithm::move` and `std::algorithm::fill` from [`std::algorithm`](https://en.cppreference.com/w/cpp/algorithm/).
Before Cython 3, those interfaces had to be imported ... | 27,682 | [
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https://github.com/scikit-learn/scikit-learn/issues/27682 | [
"good first issue",
"cython"
] | MAINT Directly `cimport` interfaces from `std::algorithm`
Some Cython implementations use interfaces from the standard library of C++, namely `std::algorithm::move` and `std::algorithm::fill` from [`std::algorithm`](https://en.cppreference.com/w/cpp/algorithm/).
Before Cython 3, those interfaces had to be imported ... | 27,682 | [
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https://github.com/scikit-learn/scikit-learn/issues/27679 | [
"Needs Triage"
] | NSE Equation used for R2
https://github.com/scikit-learn/scikit-learn/blame/093e0cf14aff026cca6097e8c42f83b735d26358/sklearn/metrics/_regression.py#L830-L838
The equation used for the R2 score is rather that of the [Nash–Sutcliffe model efficiency coefficient (NSE)](https://en.wikipedia.org/wiki/Nash%E2%80%93Sutcli... | 27,679 | [
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... |
https://github.com/scikit-learn/scikit-learn/issues/27679 | [
"Needs Triage"
] | NSE Equation used for R2
https://github.com/scikit-learn/scikit-learn/blame/093e0cf14aff026cca6097e8c42f83b735d26358/sklearn/metrics/_regression.py#L830-L838
The equation used for the R2 score is rather that of the [Nash–Sutcliffe model efficiency coefficient (NSE)](https://en.wikipedia.org/wiki/Nash%E2%80%93Sutcli... | 27,679 | [
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https://github.com/scikit-learn/scikit-learn/issues/27676 | [
"Meta-issue"
] | Callback API plan
The goal of this issue is to track the steps of the implementation of a callback API in scikit-learn.
This is being developed in the `callbacks` feature branch. The first PR to this branch is https://github.com/scikit-learn/scikit-learn/pull/27663 which implements the base infrastructure for the c... | 27,676 | [
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https://github.com/scikit-learn/scikit-learn/issues/27676 | [
"Meta-issue"
] | Callback API plan
The goal of this issue is to track the steps of the implementation of a callback API in scikit-learn.
This is being developed in the `callbacks` feature branch. The first PR to this branch is https://github.com/scikit-learn/scikit-learn/pull/27663 which implements the base infrastructure for the c... | 27,676 | [
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https://github.com/scikit-learn/scikit-learn/issues/27676 | [
"Meta-issue"
] | Callback API plan
The goal of this issue is to track the steps of the implementation of a callback API in scikit-learn.
This is being developed in the `callbacks` feature branch. The first PR to this branch is https://github.com/scikit-learn/scikit-learn/pull/27663 which implements the base infrastructure for the c... | 27,676 | [
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https://github.com/scikit-learn/scikit-learn/issues/27662 | [
"Build / CI"
] | PyPy tests timeouts / memory usage investigation
EDIT: one of the main causes of the problem described below has already been fixed by #27670. However, despite this improvement, there are still important memory problems remaining when running the scikit-learn test suite on PyPy. So similar investigation and fixes are... | 27,662 | [
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https://github.com/scikit-learn/scikit-learn/issues/27662 | [
"Build / CI"
] | PyPy tests timeouts / memory usage investigation
EDIT: one of the main causes of the problem described below has already been fixed by #27670. However, despite this improvement, there are still important memory problems remaining when running the scikit-learn test suite on PyPy. So similar investigation and fixes are... | 27,662 | [
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0.023331865... |
https://github.com/scikit-learn/scikit-learn/issues/27662 | [
"Build / CI"
] | PyPy tests timeouts / memory usage investigation
EDIT: one of the main causes of the problem described below has already been fixed by #27670. However, despite this improvement, there are still important memory problems remaining when running the scikit-learn test suite on PyPy. So similar investigation and fixes are... | 27,662 | [
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0.023331865... |
https://github.com/scikit-learn/scikit-learn/issues/27662 | [
"Build / CI"
] | PyPy tests timeouts / memory usage investigation
EDIT: one of the main causes of the problem described below has already been fixed by #27670. However, despite this improvement, there are still important memory problems remaining when running the scikit-learn test suite on PyPy. So similar investigation and fixes are... | 27,662 | [
-0.022759955376386642,
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0.023331865... |
https://github.com/scikit-learn/scikit-learn/issues/27662 | [
"Build / CI"
] | PyPy tests timeouts / memory usage investigation
EDIT: one of the main causes of the problem described below has already been fixed by #27670. However, despite this improvement, there are still important memory problems remaining when running the scikit-learn test suite on PyPy. So similar investigation and fixes are... | 27,662 | [
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0.023331865... |
https://github.com/scikit-learn/scikit-learn/issues/27662 | [
"Build / CI"
] | PyPy tests timeouts / memory usage investigation
EDIT: one of the main causes of the problem described below has already been fixed by #27670. However, despite this improvement, there are still important memory problems remaining when running the scikit-learn test suite on PyPy. So similar investigation and fixes are... | 27,662 | [
-0.022759955376386642,
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0.023331865... |
https://github.com/scikit-learn/scikit-learn/issues/27662 | [
"Build / CI"
] | PyPy tests timeouts / memory usage investigation
EDIT: one of the main causes of the problem described below has already been fixed by #27670. However, despite this improvement, there are still important memory problems remaining when running the scikit-learn test suite on PyPy. So similar investigation and fixes are... | 27,662 | [
-0.022759955376386642,
0.0273995753377676,
0.012325471267104149,
0.03355704993009567,
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0.03223447501659393,
0.021715344861149788,
-0.07418189197778702,
0.023331865... |
https://github.com/scikit-learn/scikit-learn/issues/27662 | [
"Build / CI"
] | PyPy tests timeouts / memory usage investigation
EDIT: one of the main causes of the problem described below has already been fixed by #27670. However, despite this improvement, there are still important memory problems remaining when running the scikit-learn test suite on PyPy. So similar investigation and fixes are... | 27,662 | [
-0.022759955376386642,
0.0273995753377676,
0.012325471267104149,
0.03355704993009567,
0.04346822202205658,
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0.01992201805114746,
0.0653025358915329,
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-0.011951679363846779,
0.03223447501659393,
0.021715344861149788,
-0.07418189197778702,
0.023331865... |
https://github.com/scikit-learn/scikit-learn/issues/27662 | [
"Build / CI"
] | PyPy tests timeouts / memory usage investigation
EDIT: one of the main causes of the problem described below has already been fixed by #27670. However, despite this improvement, there are still important memory problems remaining when running the scikit-learn test suite on PyPy. So similar investigation and fixes are... | 27,662 | [
-0.022759955376386642,
0.0273995753377676,
0.012325471267104149,
0.03355704993009567,
0.04346822202205658,
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0.01992201805114746,
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-0.011951679363846779,
0.03223447501659393,
0.021715344861149788,
-0.07418189197778702,
0.023331865... |
https://github.com/scikit-learn/scikit-learn/issues/27662 | [
"Build / CI"
] | PyPy tests timeouts / memory usage investigation
EDIT: one of the main causes of the problem described below has already been fixed by #27670. However, despite this improvement, there are still important memory problems remaining when running the scikit-learn test suite on PyPy. So similar investigation and fixes are... | 27,662 | [
-0.022759955376386642,
0.0273995753377676,
0.012325471267104149,
0.03355704993009567,
0.04346822202205658,
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0.01992201805114746,
0.0653025358915329,
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-0.011951679363846779,
0.03223447501659393,
0.021715344861149788,
-0.07418189197778702,
0.023331865... |
https://github.com/scikit-learn/scikit-learn/issues/27662 | [
"Build / CI"
] | PyPy tests timeouts / memory usage investigation
EDIT: one of the main causes of the problem described below has already been fixed by #27670. However, despite this improvement, there are still important memory problems remaining when running the scikit-learn test suite on PyPy. So similar investigation and fixes are... | 27,662 | [
-0.022759955376386642,
0.0273995753377676,
0.012325471267104149,
0.03355704993009567,
0.04346822202205658,
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0.01992201805114746,
0.0653025358915329,
0.031968854367733,
-0.011951679363846779,
0.03223447501659393,
0.021715344861149788,
-0.07418189197778702,
0.023331865... |
https://github.com/scikit-learn/scikit-learn/issues/27662 | [
"Build / CI"
] | PyPy tests timeouts / memory usage investigation
EDIT: one of the main causes of the problem described below has already been fixed by #27670. However, despite this improvement, there are still important memory problems remaining when running the scikit-learn test suite on PyPy. So similar investigation and fixes are... | 27,662 | [
-0.022759955376386642,
0.0273995753377676,
0.012325471267104149,
0.03355704993009567,
0.04346822202205658,
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0.01992201805114746,
0.0653025358915329,
0.031968854367733,
-0.011951679363846779,
0.03223447501659393,
0.021715344861149788,
-0.07418189197778702,
0.023331865... |
https://github.com/scikit-learn/scikit-learn/issues/27662 | [
"Build / CI"
] | PyPy tests timeouts / memory usage investigation
EDIT: one of the main causes of the problem described below has already been fixed by #27670. However, despite this improvement, there are still important memory problems remaining when running the scikit-learn test suite on PyPy. So similar investigation and fixes are... | 27,662 | [
-0.022759955376386642,
0.0273995753377676,
0.012325471267104149,
0.03355704993009567,
0.04346822202205658,
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0.01992201805114746,
0.0653025358915329,
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-0.011951679363846779,
0.03223447501659393,
0.021715344861149788,
-0.07418189197778702,
0.023331865... |
https://github.com/scikit-learn/scikit-learn/issues/27662 | [
"Build / CI"
] | PyPy tests timeouts / memory usage investigation
EDIT: one of the main causes of the problem described below has already been fixed by #27670. However, despite this improvement, there are still important memory problems remaining when running the scikit-learn test suite on PyPy. So similar investigation and fixes are... | 27,662 | [
-0.022759955376386642,
0.0273995753377676,
0.012325471267104149,
0.03355704993009567,
0.04346822202205658,
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0.01992201805114746,
0.0653025358915329,
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0.03223447501659393,
0.021715344861149788,
-0.07418189197778702,
0.023331865... |
https://github.com/scikit-learn/scikit-learn/issues/27662 | [
"Build / CI"
] | PyPy tests timeouts / memory usage investigation
EDIT: one of the main causes of the problem described below has already been fixed by #27670. However, despite this improvement, there are still important memory problems remaining when running the scikit-learn test suite on PyPy. So similar investigation and fixes are... | 27,662 | [
-0.022759955376386642,
0.0273995753377676,
0.012325471267104149,
0.03355704993009567,
0.04346822202205658,
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0.01992201805114746,
0.0653025358915329,
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0.03223447501659393,
0.021715344861149788,
-0.07418189197778702,
0.023331865... |
https://github.com/scikit-learn/scikit-learn/issues/27662 | [
"Build / CI"
] | PyPy tests timeouts / memory usage investigation
EDIT: one of the main causes of the problem described below has already been fixed by #27670. However, despite this improvement, there are still important memory problems remaining when running the scikit-learn test suite on PyPy. So similar investigation and fixes are... | 27,662 | [
-0.022759955376386642,
0.0273995753377676,
0.012325471267104149,
0.03355704993009567,
0.04346822202205658,
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0.01992201805114746,
0.0653025358915329,
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-0.011951679363846779,
0.03223447501659393,
0.021715344861149788,
-0.07418189197778702,
0.023331865... |
https://github.com/scikit-learn/scikit-learn/issues/27662 | [
"Build / CI"
] | PyPy tests timeouts / memory usage investigation
EDIT: one of the main causes of the problem described below has already been fixed by #27670. However, despite this improvement, there are still important memory problems remaining when running the scikit-learn test suite on PyPy. So similar investigation and fixes are... | 27,662 | [
-0.022759955376386642,
0.0273995753377676,
0.012325471267104149,
0.03355704993009567,
0.04346822202205658,
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0.01992201805114746,
0.0653025358915329,
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-0.011951679363846779,
0.03223447501659393,
0.021715344861149788,
-0.07418189197778702,
0.023331865... |
https://github.com/scikit-learn/scikit-learn/issues/27662 | [
"Build / CI"
] | PyPy tests timeouts / memory usage investigation
EDIT: one of the main causes of the problem described below has already been fixed by #27670. However, despite this improvement, there are still important memory problems remaining when running the scikit-learn test suite on PyPy. So similar investigation and fixes are... | 27,662 | [
-0.022759955376386642,
0.0273995753377676,
0.012325471267104149,
0.03355704993009567,
0.04346822202205658,
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0.01992201805114746,
0.0653025358915329,
0.031968854367733,
-0.011951679363846779,
0.03223447501659393,
0.021715344861149788,
-0.07418189197778702,
0.023331865... |
https://github.com/scikit-learn/scikit-learn/issues/27662 | [
"Build / CI"
] | PyPy tests timeouts / memory usage investigation
EDIT: one of the main causes of the problem described below has already been fixed by #27670. However, despite this improvement, there are still important memory problems remaining when running the scikit-learn test suite on PyPy. So similar investigation and fixes are... | 27,662 | [
-0.022759955376386642,
0.0273995753377676,
0.012325471267104149,
0.03355704993009567,
0.04346822202205658,
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0.01992201805114746,
0.0653025358915329,
0.031968854367733,
-0.011951679363846779,
0.03223447501659393,
0.021715344861149788,
-0.07418189197778702,
0.023331865... |
https://github.com/scikit-learn/scikit-learn/issues/27662 | [
"Build / CI"
] | PyPy tests timeouts / memory usage investigation
EDIT: one of the main causes of the problem described below has already been fixed by #27670. However, despite this improvement, there are still important memory problems remaining when running the scikit-learn test suite on PyPy. So similar investigation and fixes are... | 27,662 | [
-0.022759955376386642,
0.0273995753377676,
0.012325471267104149,
0.03355704993009567,
0.04346822202205658,
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0.01992201805114746,
0.0653025358915329,
0.031968854367733,
-0.011951679363846779,
0.03223447501659393,
0.021715344861149788,
-0.07418189197778702,
0.023331865... |
https://github.com/scikit-learn/scikit-learn/issues/27662 | [
"Build / CI"
] | PyPy tests timeouts / memory usage investigation
EDIT: one of the main causes of the problem described below has already been fixed by #27670. However, despite this improvement, there are still important memory problems remaining when running the scikit-learn test suite on PyPy. So similar investigation and fixes are... | 27,662 | [
-0.022759955376386642,
0.0273995753377676,
0.012325471267104149,
0.03355704993009567,
0.04346822202205658,
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0.03223447501659393,
0.021715344861149788,
-0.07418189197778702,
0.023331865... |
https://github.com/scikit-learn/scikit-learn/issues/27662 | [
"Build / CI"
] | PyPy tests timeouts / memory usage investigation
EDIT: one of the main causes of the problem described below has already been fixed by #27670. However, despite this improvement, there are still important memory problems remaining when running the scikit-learn test suite on PyPy. So similar investigation and fixes are... | 27,662 | [
-0.022759955376386642,
0.0273995753377676,
0.012325471267104149,
0.03355704993009567,
0.04346822202205658,
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0.01992201805114746,
0.0653025358915329,
0.031968854367733,
-0.011951679363846779,
0.03223447501659393,
0.021715344861149788,
-0.07418189197778702,
0.023331865... |
https://github.com/scikit-learn/scikit-learn/issues/27662 | [
"Build / CI"
] | PyPy tests timeouts / memory usage investigation
EDIT: one of the main causes of the problem described below has already been fixed by #27670. However, despite this improvement, there are still important memory problems remaining when running the scikit-learn test suite on PyPy. So similar investigation and fixes are... | 27,662 | [
-0.022759955376386642,
0.0273995753377676,
0.012325471267104149,
0.03355704993009567,
0.04346822202205658,
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0.01992201805114746,
0.0653025358915329,
0.031968854367733,
-0.011951679363846779,
0.03223447501659393,
0.021715344861149788,
-0.07418189197778702,
0.023331865... |
https://github.com/scikit-learn/scikit-learn/issues/27662 | [
"Build / CI"
] | PyPy tests timeouts / memory usage investigation
EDIT: one of the main causes of the problem described below has already been fixed by #27670. However, despite this improvement, there are still important memory problems remaining when running the scikit-learn test suite on PyPy. So similar investigation and fixes are... | 27,662 | [
-0.022759955376386642,
0.0273995753377676,
0.012325471267104149,
0.03355704993009567,
0.04346822202205658,
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0.01992201805114746,
0.0653025358915329,
0.031968854367733,
-0.011951679363846779,
0.03223447501659393,
0.021715344861149788,
-0.07418189197778702,
0.023331865... |
https://github.com/scikit-learn/scikit-learn/issues/27662 | [
"Build / CI"
] | PyPy tests timeouts / memory usage investigation
EDIT: one of the main causes of the problem described below has already been fixed by #27670. However, despite this improvement, there are still important memory problems remaining when running the scikit-learn test suite on PyPy. So similar investigation and fixes are... | 27,662 | [
-0.022759955376386642,
0.0273995753377676,
0.012325471267104149,
0.03355704993009567,
0.04346822202205658,
-0.0000822423753561452,
0.01992201805114746,
0.0653025358915329,
0.031968854367733,
-0.011951679363846779,
0.03223447501659393,
0.021715344861149788,
-0.07418189197778702,
0.023331865... |
https://github.com/scikit-learn/scikit-learn/issues/27655 | [
"Enhancement"
] | `sklearn.cluster.AgglomerativeClustering`: allow `'ward'` linkage and `'precomputed'` metric.
Hi,
I'm trying to run `AgglomerativeClustering` with precomputed (Euclidean) distance matrices. However, I can't get it to work with `linkage='ward'` and `metric='precomputed'` due to this `ValueError`:
https://github.c... | 27,655 | [
-0.04552461951971054,
-0.002680942416191101,
0.008209074847400188,
-0.018591158092021942,
0.053769927471876144,
0.042949073016643524,
0.04803125560283661,
0.014798949472606182,
0.0767897516489029,
0.02013712003827095,
0.04672125726938248,
0.006899258587509394,
-0.009442073293030262,
-0.013... |
https://github.com/scikit-learn/scikit-learn/issues/27655 | [
"Enhancement"
] | `sklearn.cluster.AgglomerativeClustering`: allow `'ward'` linkage and `'precomputed'` metric.
Hi,
I'm trying to run `AgglomerativeClustering` with precomputed (Euclidean) distance matrices. However, I can't get it to work with `linkage='ward'` and `metric='precomputed'` due to this `ValueError`:
https://github.c... | 27,655 | [
-0.04912706837058067,
-0.018003737553954124,
0.009135089814662933,
-0.026768872514367104,
0.057880692183971405,
0.04475894570350647,
0.05040059983730316,
0.019761715084314346,
0.07629841566085815,
0.01635536551475525,
0.03244129195809364,
0.007318515330553055,
-0.017750004306435585,
-0.008... |
https://github.com/scikit-learn/scikit-learn/issues/27655 | [
"Enhancement"
] | `sklearn.cluster.AgglomerativeClustering`: allow `'ward'` linkage and `'precomputed'` metric.
Hi,
I'm trying to run `AgglomerativeClustering` with precomputed (Euclidean) distance matrices. However, I can't get it to work with `linkage='ward'` and `metric='precomputed'` due to this `ValueError`:
https://github.c... | 27,655 | [
-0.04364049807190895,
-0.00858964491635561,
0.00935084093362093,
-0.02331600897014141,
0.051722943782806396,
0.041213247925043106,
0.038480475544929504,
0.027511700987815857,
0.05561130866408348,
0.013636505231261253,
0.026253176853060722,
0.011498523876070976,
-0.009905707091093063,
-0.01... |
https://github.com/scikit-learn/scikit-learn/issues/27655 | [
"Enhancement"
] | `sklearn.cluster.AgglomerativeClustering`: allow `'ward'` linkage and `'precomputed'` metric.
Hi,
I'm trying to run `AgglomerativeClustering` with precomputed (Euclidean) distance matrices. However, I can't get it to work with `linkage='ward'` and `metric='precomputed'` due to this `ValueError`:
https://github.c... | 27,655 | [
-0.05095688998699188,
-0.012718060985207558,
0.012175926938652992,
-0.02599073201417923,
0.04804728180170059,
0.03918430954217911,
0.0442400798201561,
0.018256334587931633,
0.07703303545713425,
0.018609555438160896,
0.03415241092443466,
0.0032473683822900057,
-0.018732894212007523,
-0.0114... |
https://github.com/scikit-learn/scikit-learn/issues/27655 | [
"Enhancement"
] | `sklearn.cluster.AgglomerativeClustering`: allow `'ward'` linkage and `'precomputed'` metric.
Hi,
I'm trying to run `AgglomerativeClustering` with precomputed (Euclidean) distance matrices. However, I can't get it to work with `linkage='ward'` and `metric='precomputed'` due to this `ValueError`:
https://github.c... | 27,655 | [
-0.05114329606294632,
-0.015474737621843815,
0.00835139025002718,
-0.025781895965337753,
0.055949948728084564,
0.04677087068557739,
0.0522213876247406,
0.021564600989222527,
0.07636348903179169,
0.016121210530400276,
0.0339575856924057,
0.008255133405327797,
-0.020654983818531036,
-0.00726... |
https://github.com/scikit-learn/scikit-learn/issues/27655 | [
"Enhancement"
] | `sklearn.cluster.AgglomerativeClustering`: allow `'ward'` linkage and `'precomputed'` metric.
Hi,
I'm trying to run `AgglomerativeClustering` with precomputed (Euclidean) distance matrices. However, I can't get it to work with `linkage='ward'` and `metric='precomputed'` due to this `ValueError`:
https://github.c... | 27,655 | [
-0.04550204053521156,
-0.02286584861576557,
0.0201229527592659,
-0.012774914503097534,
0.058264315128326416,
0.03667447343468666,
0.04655572026968002,
0.028426969423890114,
0.09230266511440277,
0.00034484005300328135,
0.013740475289523602,
0.0010176593204960227,
-0.02329464629292488,
-0.01... |
https://github.com/scikit-learn/scikit-learn/issues/27654 | [
"API"
] | inverse_transform Xt argument consistency
### Describe the issue linked to the documentation
Some of the inverse_transform methods take `Xt` as an argument whereas others take `X`. Is there are reason for the differences in the names?
Noting the cases here: https://github.com/search?q=repo%3Ascikit-learn%2Fscikit-... | 27,654 | [
0.021342381834983826,
-0.07018741965293884,
0.008264919742941856,
-0.03038271889090538,
-0.034270983189344406,
-0.006372848991304636,
0.030651172623038292,
0.04105757176876068,
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0.013944244012236595,
0.0015586577355861664,
0.051034439355134964,
0.060815054923295975,
-... |
https://github.com/scikit-learn/scikit-learn/issues/27654 | [
"API"
] | inverse_transform Xt argument consistency
### Describe the issue linked to the documentation
Some of the inverse_transform methods take `Xt` as an argument whereas others take `X`. Is there are reason for the differences in the names?
Noting the cases here: https://github.com/search?q=repo%3Ascikit-learn%2Fscikit-... | 27,654 | [
0.00026103470008820295,
-0.050753142684698105,
0.02511199750006199,
-0.06877803057432175,
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-0.014135653153061867,
0.03590528294444084,
0.02917962335050106,
0.02908981963992119,
0.005684475880116224,
0.004940771032124758,
0.02429939992725849,
0.054542239755392075,
-0... |
https://github.com/scikit-learn/scikit-learn/issues/27654 | [
"API"
] | inverse_transform Xt argument consistency
### Describe the issue linked to the documentation
Some of the inverse_transform methods take `Xt` as an argument whereas others take `X`. Is there are reason for the differences in the names?
Noting the cases here: https://github.com/search?q=repo%3Ascikit-learn%2Fscikit-... | 27,654 | [
0.030263379216194153,
-0.05028783902525902,
0.03186055272817612,
-0.03966942057013512,
-0.0010305843316018581,
0.0015156574081629515,
0.05408339574933052,
0.03889152780175209,
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0.01851833239197731,
0.012108074501156807,
0.04242575913667679,
0.06429103761911392,
-0.034... |
https://github.com/scikit-learn/scikit-learn/issues/27654 | [
"API"
] | inverse_transform Xt argument consistency
### Describe the issue linked to the documentation
Some of the inverse_transform methods take `Xt` as an argument whereas others take `X`. Is there are reason for the differences in the names?
Noting the cases here: https://github.com/search?q=repo%3Ascikit-learn%2Fscikit-... | 27,654 | [
0.027093563228845596,
-0.050355903804302216,
0.017936136573553085,
-0.0383550189435482,
-0.01262932550162077,
-0.0038241420406848192,
0.0465242899954319,
0.036884330213069916,
-0.0289834626019001,
0.022908534854650497,
0.006658107507973909,
0.039847757667303085,
0.07074720412492752,
-0.050... |
https://github.com/scikit-learn/scikit-learn/issues/27654 | [
"API"
] | inverse_transform Xt argument consistency
### Describe the issue linked to the documentation
Some of the inverse_transform methods take `Xt` as an argument whereas others take `X`. Is there are reason for the differences in the names?
Noting the cases here: https://github.com/search?q=repo%3Ascikit-learn%2Fscikit-... | 27,654 | [
0.010967438109219074,
-0.06957483291625977,
0.006772150285542011,
-0.03513515740633011,
-0.02452009543776512,
-0.0089567257091403,
0.02385631948709488,
0.04300307482481003,
-0.018062371760606766,
0.019085237756371498,
0.013010580092668533,
0.049464136362075806,
0.060581255704164505,
-0.042... |
https://github.com/scikit-learn/scikit-learn/issues/27654 | [
"API"
] | inverse_transform Xt argument consistency
### Describe the issue linked to the documentation
Some of the inverse_transform methods take `Xt` as an argument whereas others take `X`. Is there are reason for the differences in the names?
Noting the cases here: https://github.com/search?q=repo%3Ascikit-learn%2Fscikit-... | 27,654 | [
0.027591435238718987,
-0.07391830533742905,
0.020291754975914955,
-0.04985322803258896,
-0.02261371538043022,
-0.006911019794642925,
0.03188227489590645,
0.04419650137424469,
0.010520844720304012,
0.004850972909480333,
0.03341066837310791,
0.04777593910694122,
0.052953578531742096,
-0.0427... |
https://github.com/scikit-learn/scikit-learn/issues/27653 | [
"Bug",
"Needs Triage"
] | scikit-learn-1.3.2.tar.gz archive contains version 1.4.dev0
### Describe the bug
The package downloaded from [https://github.com/scikit-learn/scikit-learn/archive/1.3.2/scikit-learn-1.3.2.tar.gz](https://github.com/scikit-learn/scikit-learn/archive/1.3.2/scikit-learn-1.3.2.tar.gz)
contains version 1.4.dev0:
The... | 27,653 | [
0.029253039509058,
-0.03329789638519287,
-0.0135179553180933,
-0.010904048569500446,
0.0028907498344779015,
0.027898142114281654,
-0.011593812145292759,
0.049458540976047516,
0.0477604977786541,
-0.0116646159440279,
0.07772230356931686,
0.06781556457281113,
0.009214945137500763,
0.03672580... |
https://github.com/scikit-learn/scikit-learn/issues/27653 | [
"Bug",
"Needs Triage"
] | scikit-learn-1.3.2.tar.gz archive contains version 1.4.dev0
### Describe the bug
The package downloaded from [https://github.com/scikit-learn/scikit-learn/archive/1.3.2/scikit-learn-1.3.2.tar.gz](https://github.com/scikit-learn/scikit-learn/archive/1.3.2/scikit-learn-1.3.2.tar.gz)
contains version 1.4.dev0:
The... | 27,653 | [
0.04246694594621658,
-0.04770123213529587,
-0.022919028997421265,
-0.01215737871825695,
-0.0010806540958583355,
0.04348455369472504,
-0.01822006329894066,
0.04135363921523094,
0.049819543957710266,
-0.007153135258704424,
0.07440325617790222,
0.05978336185216904,
0.010969197377562523,
0.019... |
https://github.com/scikit-learn/scikit-learn/issues/27653 | [
"Bug",
"Needs Triage"
] | scikit-learn-1.3.2.tar.gz archive contains version 1.4.dev0
### Describe the bug
The package downloaded from [https://github.com/scikit-learn/scikit-learn/archive/1.3.2/scikit-learn-1.3.2.tar.gz](https://github.com/scikit-learn/scikit-learn/archive/1.3.2/scikit-learn-1.3.2.tar.gz)
contains version 1.4.dev0:
The... | 27,653 | [
0.03351687267422676,
-0.03397165238857269,
-0.01254797913134098,
-0.007896456867456436,
-0.0056041874922811985,
0.025960648432374,
-0.021046089008450508,
0.04242212325334549,
0.045316968113183975,
-0.0027768192812800407,
0.07092329114675522,
0.06794676184654236,
0.010201574303209782,
0.039... |
https://github.com/scikit-learn/scikit-learn/issues/27653 | [
"Bug",
"Needs Triage"
] | scikit-learn-1.3.2.tar.gz archive contains version 1.4.dev0
### Describe the bug
The package downloaded from [https://github.com/scikit-learn/scikit-learn/archive/1.3.2/scikit-learn-1.3.2.tar.gz](https://github.com/scikit-learn/scikit-learn/archive/1.3.2/scikit-learn-1.3.2.tar.gz)
contains version 1.4.dev0:
The... | 27,653 | [
0.02735793963074684,
-0.038040339946746826,
-0.010271161794662476,
-0.011039051227271557,
0.0033169405069202185,
0.025983959436416626,
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0.0485113300383091,
0.05109656602144241,
-0.00733653549104929,
0.07892882078886032,
0.06988323479890823,
0.007859155535697937,
0.035... |
https://github.com/scikit-learn/scikit-learn/issues/27653 | [
"Bug",
"Needs Triage"
] | scikit-learn-1.3.2.tar.gz archive contains version 1.4.dev0
### Describe the bug
The package downloaded from [https://github.com/scikit-learn/scikit-learn/archive/1.3.2/scikit-learn-1.3.2.tar.gz](https://github.com/scikit-learn/scikit-learn/archive/1.3.2/scikit-learn-1.3.2.tar.gz)
contains version 1.4.dev0:
The... | 27,653 | [
0.04964291304349899,
-0.059120628982782364,
-0.02037671208381653,
-0.01160881482064724,
0.011438688263297081,
0.04482118785381317,
-0.015206009149551392,
0.03661251813173294,
0.0733414962887764,
-0.0082471314817667,
0.07318765670061111,
0.06874462962150574,
0.01746560074388981,
0.036158815... |
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