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/22881 | [
"help wanted",
"Hard",
"module:test-suite",
"Meta-issue",
"float32"
] | Improve tests to make them run on variously typed data using the `global_dtype` fixture
## Context: the new `global_dtype` fixture and `SKLEARN_RUN_FLOAT32_TESTS` environment variable
Introduction of low-level computational routines for 32bit motivated an extension of tests to run them on 32bit.
In this regards,... | 22,881 | [
-0.040006812661886215,
0.01912323385477066,
-0.01085315365344286,
0.03974715620279312,
0.018551934510469437,
0.022800032049417496,
0.07511391490697861,
0.08400633931159973,
0.007371400482952595,
-0.040778160095214844,
0.026359522715210915,
-0.010787741281092167,
-0.012147189117968082,
0.02... |
https://github.com/scikit-learn/scikit-learn/issues/22881 | [
"help wanted",
"Hard",
"module:test-suite",
"Meta-issue",
"float32"
] | Improve tests to make them run on variously typed data using the `global_dtype` fixture
## Context: the new `global_dtype` fixture and `SKLEARN_RUN_FLOAT32_TESTS` environment variable
Introduction of low-level computational routines for 32bit motivated an extension of tests to run them on 32bit.
In this regards,... | 22,881 | [
-0.040006812661886215,
0.01912323385477066,
-0.01085315365344286,
0.03974715620279312,
0.018551934510469437,
0.022800032049417496,
0.07511391490697861,
0.08400633931159973,
0.007371400482952595,
-0.040778160095214844,
0.026359522715210915,
-0.010787741281092167,
-0.012147189117968082,
0.02... |
https://github.com/scikit-learn/scikit-learn/issues/22881 | [
"help wanted",
"Hard",
"module:test-suite",
"Meta-issue",
"float32"
] | Improve tests to make them run on variously typed data using the `global_dtype` fixture
## Context: the new `global_dtype` fixture and `SKLEARN_RUN_FLOAT32_TESTS` environment variable
Introduction of low-level computational routines for 32bit motivated an extension of tests to run them on 32bit.
In this regards,... | 22,881 | [
-0.040006812661886215,
0.01912323385477066,
-0.01085315365344286,
0.03974715620279312,
0.018551934510469437,
0.022800032049417496,
0.07511391490697861,
0.08400633931159973,
0.007371400482952595,
-0.040778160095214844,
0.026359522715210915,
-0.010787741281092167,
-0.012147189117968082,
0.02... |
https://github.com/scikit-learn/scikit-learn/issues/22881 | [
"help wanted",
"Hard",
"module:test-suite",
"Meta-issue",
"float32"
] | Improve tests to make them run on variously typed data using the `global_dtype` fixture
## Context: the new `global_dtype` fixture and `SKLEARN_RUN_FLOAT32_TESTS` environment variable
Introduction of low-level computational routines for 32bit motivated an extension of tests to run them on 32bit.
In this regards,... | 22,881 | [
-0.040006812661886215,
0.01912323385477066,
-0.01085315365344286,
0.03974715620279312,
0.018551934510469437,
0.022800032049417496,
0.07511391490697861,
0.08400633931159973,
0.007371400482952595,
-0.040778160095214844,
0.026359522715210915,
-0.010787741281092167,
-0.012147189117968082,
0.02... |
https://github.com/scikit-learn/scikit-learn/issues/22881 | [
"help wanted",
"Hard",
"module:test-suite",
"Meta-issue",
"float32"
] | Improve tests to make them run on variously typed data using the `global_dtype` fixture
## Context: the new `global_dtype` fixture and `SKLEARN_RUN_FLOAT32_TESTS` environment variable
Introduction of low-level computational routines for 32bit motivated an extension of tests to run them on 32bit.
In this regards,... | 22,881 | [
-0.040006812661886215,
0.01912323385477066,
-0.01085315365344286,
0.03974715620279312,
0.018551934510469437,
0.022800032049417496,
0.07511391490697861,
0.08400633931159973,
0.007371400482952595,
-0.040778160095214844,
0.026359522715210915,
-0.010787741281092167,
-0.012147189117968082,
0.02... |
https://github.com/scikit-learn/scikit-learn/issues/22881 | [
"help wanted",
"Hard",
"module:test-suite",
"Meta-issue",
"float32"
] | Improve tests to make them run on variously typed data using the `global_dtype` fixture
## Context: the new `global_dtype` fixture and `SKLEARN_RUN_FLOAT32_TESTS` environment variable
Introduction of low-level computational routines for 32bit motivated an extension of tests to run them on 32bit.
In this regards,... | 22,881 | [
-0.040006812661886215,
0.01912323385477066,
-0.01085315365344286,
0.03974715620279312,
0.018551934510469437,
0.022800032049417496,
0.07511391490697861,
0.08400633931159973,
0.007371400482952595,
-0.040778160095214844,
0.026359522715210915,
-0.010787741281092167,
-0.012147189117968082,
0.02... |
https://github.com/scikit-learn/scikit-learn/issues/22881 | [
"help wanted",
"Hard",
"module:test-suite",
"Meta-issue",
"float32"
] | Improve tests to make them run on variously typed data using the `global_dtype` fixture
## Context: the new `global_dtype` fixture and `SKLEARN_RUN_FLOAT32_TESTS` environment variable
Introduction of low-level computational routines for 32bit motivated an extension of tests to run them on 32bit.
In this regards,... | 22,881 | [
-0.040006812661886215,
0.01912323385477066,
-0.01085315365344286,
0.03974715620279312,
0.018551934510469437,
0.022800032049417496,
0.07511391490697861,
0.08400633931159973,
0.007371400482952595,
-0.040778160095214844,
0.026359522715210915,
-0.010787741281092167,
-0.012147189117968082,
0.02... |
https://github.com/scikit-learn/scikit-learn/issues/22881 | [
"help wanted",
"Hard",
"module:test-suite",
"Meta-issue",
"float32"
] | Improve tests to make them run on variously typed data using the `global_dtype` fixture
## Context: the new `global_dtype` fixture and `SKLEARN_RUN_FLOAT32_TESTS` environment variable
Introduction of low-level computational routines for 32bit motivated an extension of tests to run them on 32bit.
In this regards,... | 22,881 | [
-0.040006812661886215,
0.01912323385477066,
-0.01085315365344286,
0.03974715620279312,
0.018551934510469437,
0.022800032049417496,
0.07511391490697861,
0.08400633931159973,
0.007371400482952595,
-0.040778160095214844,
0.026359522715210915,
-0.010787741281092167,
-0.012147189117968082,
0.02... |
https://github.com/scikit-learn/scikit-learn/issues/22880 | [
"New Feature",
"Documentation",
"module:neighbors"
] | Encapsulate nearest neighbor code for `sort_sparse_row_values` in a function
### Describe the issue linked to the documentation
The [nearest neighbor code](https://github.com/scikit-learn/scikit-learn/blob/fb71eeff5a40399648d63258239079f5db7dcd76/sklearn/neighbors/_base.py#L206) often raises an `EfficiencyWarning`,... | 22,880 | [
-0.003854045644402504,
0.03916561231017113,
0.022003376856446266,
0.020469065755605698,
0.0706428661942482,
0.03633115813136101,
0.04528043791651726,
0.04588167741894722,
0.05710696429014206,
0.008094115182757378,
-0.020900990813970566,
0.029594415798783302,
0.024697059765458107,
0.0076455... |
https://github.com/scikit-learn/scikit-learn/issues/22880 | [
"New Feature",
"Documentation",
"module:neighbors"
] | Encapsulate nearest neighbor code for `sort_sparse_row_values` in a function
### Describe the issue linked to the documentation
The [nearest neighbor code](https://github.com/scikit-learn/scikit-learn/blob/fb71eeff5a40399648d63258239079f5db7dcd76/sklearn/neighbors/_base.py#L206) often raises an `EfficiencyWarning`,... | 22,880 | [
-0.003854045644402504,
0.03916561231017113,
0.022003376856446266,
0.020469065755605698,
0.0706428661942482,
0.03633115813136101,
0.04528043791651726,
0.04588167741894722,
0.05710696429014206,
0.008094115182757378,
-0.020900990813970566,
0.029594415798783302,
0.024697059765458107,
0.0076455... |
https://github.com/scikit-learn/scikit-learn/issues/22867 | [
"pypy"
] | Failing nightly tests with PyPy
Observed here:
https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=39570&view=logs&j=0b16f832-29d6-5b92-1c23-eb006f606a66&t=0cdfadab-878f-502c-9df1-54a896e98c4f
Here are the failures:
```
________________ [doctest] sklearn.externals._pilutil.bytescale ______... | 22,867 | [
0.02477448433637619,
0.016434382647275925,
-0.0006419356795959175,
-0.04372643679380417,
0.05592931807041168,
0.031408436596393585,
0.06419423222541809,
0.08173836767673492,
0.0012773132184520364,
-0.014220943674445152,
0.02841412089765072,
0.017600126564502716,
-0.016215139999985695,
0.00... |
https://github.com/scikit-learn/scikit-learn/issues/22867 | [
"pypy"
] | Failing nightly tests with PyPy
Observed here:
https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=39570&view=logs&j=0b16f832-29d6-5b92-1c23-eb006f606a66&t=0cdfadab-878f-502c-9df1-54a896e98c4f
Here are the failures:
```
________________ [doctest] sklearn.externals._pilutil.bytescale ______... | 22,867 | [
0.02477448433637619,
0.016434382647275925,
-0.0006419356795959175,
-0.04372643679380417,
0.05592931807041168,
0.031408436596393585,
0.06419423222541809,
0.08173836767673492,
0.0012773132184520364,
-0.014220943674445152,
0.02841412089765072,
0.017600126564502716,
-0.016215139999985695,
0.00... |
https://github.com/scikit-learn/scikit-learn/issues/22867 | [
"pypy"
] | Failing nightly tests with PyPy
Observed here:
https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=39570&view=logs&j=0b16f832-29d6-5b92-1c23-eb006f606a66&t=0cdfadab-878f-502c-9df1-54a896e98c4f
Here are the failures:
```
________________ [doctest] sklearn.externals._pilutil.bytescale ______... | 22,867 | [
0.02477448433637619,
0.016434382647275925,
-0.0006419356795959175,
-0.04372643679380417,
0.05592931807041168,
0.031408436596393585,
0.06419423222541809,
0.08173836767673492,
0.0012773132184520364,
-0.014220943674445152,
0.02841412089765072,
0.017600126564502716,
-0.016215139999985695,
0.00... |
https://github.com/scikit-learn/scikit-learn/issues/22867 | [
"pypy"
] | Failing nightly tests with PyPy
Observed here:
https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=39570&view=logs&j=0b16f832-29d6-5b92-1c23-eb006f606a66&t=0cdfadab-878f-502c-9df1-54a896e98c4f
Here are the failures:
```
________________ [doctest] sklearn.externals._pilutil.bytescale ______... | 22,867 | [
0.02477448433637619,
0.016434382647275925,
-0.0006419356795959175,
-0.04372643679380417,
0.05592931807041168,
0.031408436596393585,
0.06419423222541809,
0.08173836767673492,
0.0012773132184520364,
-0.014220943674445152,
0.02841412089765072,
0.017600126564502716,
-0.016215139999985695,
0.00... |
https://github.com/scikit-learn/scikit-learn/issues/22867 | [
"pypy"
] | Failing nightly tests with PyPy
Observed here:
https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=39570&view=logs&j=0b16f832-29d6-5b92-1c23-eb006f606a66&t=0cdfadab-878f-502c-9df1-54a896e98c4f
Here are the failures:
```
________________ [doctest] sklearn.externals._pilutil.bytescale ______... | 22,867 | [
0.02477448433637619,
0.016434382647275925,
-0.0006419356795959175,
-0.04372643679380417,
0.05592931807041168,
0.031408436596393585,
0.06419423222541809,
0.08173836767673492,
0.0012773132184520364,
-0.014220943674445152,
0.02841412089765072,
0.017600126564502716,
-0.016215139999985695,
0.00... |
https://github.com/scikit-learn/scikit-learn/issues/22857 | [
"Bug"
] | RuntimeError: "Cannot clone object ..." when cloning an estimator that copies parameters in either __init__ or get_params
### Describe the bug
Context: https://github.com/scikit-learn/scikit-learn/issues/15722#issuecomment-893942972
Calling `clone()` on a BaseEstimator that copies parameters results in a Runtime... | 22,857 | [
0.01613561622798443,
0.05099822208285332,
0.028081238269805908,
-0.006652326788753271,
0.018892204388976097,
-0.028591299429535866,
0.04323134198784828,
0.00799210648983717,
-0.01884721778333187,
0.019465357065200806,
0.028265783563256264,
0.032860130071640015,
-0.00759011460468173,
-0.042... |
https://github.com/scikit-learn/scikit-learn/issues/22857 | [
"Bug"
] | RuntimeError: "Cannot clone object ..." when cloning an estimator that copies parameters in either __init__ or get_params
### Describe the bug
Context: https://github.com/scikit-learn/scikit-learn/issues/15722#issuecomment-893942972
Calling `clone()` on a BaseEstimator that copies parameters results in a Runtime... | 22,857 | [
0.01613561622798443,
0.05099822208285332,
0.028081238269805908,
-0.006652326788753271,
0.018892204388976097,
-0.028591299429535866,
0.04323134198784828,
0.00799210648983717,
-0.01884721778333187,
0.019465357065200806,
0.028265783563256264,
0.032860130071640015,
-0.00759011460468173,
-0.042... |
https://github.com/scikit-learn/scikit-learn/issues/22857 | [
"Bug"
] | RuntimeError: "Cannot clone object ..." when cloning an estimator that copies parameters in either __init__ or get_params
### Describe the bug
Context: https://github.com/scikit-learn/scikit-learn/issues/15722#issuecomment-893942972
Calling `clone()` on a BaseEstimator that copies parameters results in a Runtime... | 22,857 | [
0.01613561622798443,
0.05099822208285332,
0.028081238269805908,
-0.006652326788753271,
0.018892204388976097,
-0.028591299429535866,
0.04323134198784828,
0.00799210648983717,
-0.01884721778333187,
0.019465357065200806,
0.028265783563256264,
0.032860130071640015,
-0.00759011460468173,
-0.042... |
https://github.com/scikit-learn/scikit-learn/issues/22857 | [
"Bug"
] | RuntimeError: "Cannot clone object ..." when cloning an estimator that copies parameters in either __init__ or get_params
### Describe the bug
Context: https://github.com/scikit-learn/scikit-learn/issues/15722#issuecomment-893942972
Calling `clone()` on a BaseEstimator that copies parameters results in a Runtime... | 22,857 | [
0.01613561622798443,
0.05099822208285332,
0.028081238269805908,
-0.006652326788753271,
0.018892204388976097,
-0.028591299429535866,
0.04323134198784828,
0.00799210648983717,
-0.01884721778333187,
0.019465357065200806,
0.028265783563256264,
0.032860130071640015,
-0.00759011460468173,
-0.042... |
https://github.com/scikit-learn/scikit-learn/issues/22857 | [
"Bug"
] | RuntimeError: "Cannot clone object ..." when cloning an estimator that copies parameters in either __init__ or get_params
### Describe the bug
Context: https://github.com/scikit-learn/scikit-learn/issues/15722#issuecomment-893942972
Calling `clone()` on a BaseEstimator that copies parameters results in a Runtime... | 22,857 | [
0.01613561622798443,
0.05099822208285332,
0.028081238269805908,
-0.006652326788753271,
0.018892204388976097,
-0.028591299429535866,
0.04323134198784828,
0.00799210648983717,
-0.01884721778333187,
0.019465357065200806,
0.028265783563256264,
0.032860130071640015,
-0.00759011460468173,
-0.042... |
https://github.com/scikit-learn/scikit-learn/issues/22857 | [
"Bug"
] | RuntimeError: "Cannot clone object ..." when cloning an estimator that copies parameters in either __init__ or get_params
### Describe the bug
Context: https://github.com/scikit-learn/scikit-learn/issues/15722#issuecomment-893942972
Calling `clone()` on a BaseEstimator that copies parameters results in a Runtime... | 22,857 | [
0.01613561622798443,
0.05099822208285332,
0.028081238269805908,
-0.006652326788753271,
0.018892204388976097,
-0.028591299429535866,
0.04323134198784828,
0.00799210648983717,
-0.01884721778333187,
0.019465357065200806,
0.028265783563256264,
0.032860130071640015,
-0.00759011460468173,
-0.042... |
https://github.com/scikit-learn/scikit-learn/issues/22857 | [
"Bug"
] | RuntimeError: "Cannot clone object ..." when cloning an estimator that copies parameters in either __init__ or get_params
### Describe the bug
Context: https://github.com/scikit-learn/scikit-learn/issues/15722#issuecomment-893942972
Calling `clone()` on a BaseEstimator that copies parameters results in a Runtime... | 22,857 | [
0.01613561622798443,
0.05099822208285332,
0.028081238269805908,
-0.006652326788753271,
0.018892204388976097,
-0.028591299429535866,
0.04323134198784828,
0.00799210648983717,
-0.01884721778333187,
0.019465357065200806,
0.028265783563256264,
0.032860130071640015,
-0.00759011460468173,
-0.042... |
https://github.com/scikit-learn/scikit-learn/issues/22857 | [
"Bug"
] | RuntimeError: "Cannot clone object ..." when cloning an estimator that copies parameters in either __init__ or get_params
### Describe the bug
Context: https://github.com/scikit-learn/scikit-learn/issues/15722#issuecomment-893942972
Calling `clone()` on a BaseEstimator that copies parameters results in a Runtime... | 22,857 | [
0.01613561622798443,
0.05099822208285332,
0.028081238269805908,
-0.006652326788753271,
0.018892204388976097,
-0.028591299429535866,
0.04323134198784828,
0.00799210648983717,
-0.01884721778333187,
0.019465357065200806,
0.028265783563256264,
0.032860130071640015,
-0.00759011460468173,
-0.042... |
https://github.com/scikit-learn/scikit-learn/issues/22857 | [
"Bug"
] | RuntimeError: "Cannot clone object ..." when cloning an estimator that copies parameters in either __init__ or get_params
### Describe the bug
Context: https://github.com/scikit-learn/scikit-learn/issues/15722#issuecomment-893942972
Calling `clone()` on a BaseEstimator that copies parameters results in a Runtime... | 22,857 | [
0.01613561622798443,
0.05099822208285332,
0.028081238269805908,
-0.006652326788753271,
0.018892204388976097,
-0.028591299429535866,
0.04323134198784828,
0.00799210648983717,
-0.01884721778333187,
0.019465357065200806,
0.028265783563256264,
0.032860130071640015,
-0.00759011460468173,
-0.042... |
https://github.com/scikit-learn/scikit-learn/issues/22855 | [
"Performance",
"module:linear_model"
] | The fit performance of LinearRegression is sub-optimal
It seems that the performance of Linear Regression is sub-optimal when the number of samples is very large.
[sklearn_benchmarks](https://github.com/mbatoul/sklearn_benchmarks) measures a [speedup of 48](https://mbatoul.github.io/sklearn_benchmarks/results/gith... | 22,855 | [
-0.01595933735370636,
0.055361557751894,
0.01789109595119953,
0.04100774973630905,
0.04136230796575546,
-0.012455142103135586,
0.02240644209086895,
0.08614026755094528,
0.037431925535202026,
-0.011811153031885624,
0.020215189084410667,
0.051706183701753616,
0.005083975847810507,
0.02512532... |
https://github.com/scikit-learn/scikit-learn/issues/22855 | [
"Performance",
"module:linear_model"
] | The fit performance of LinearRegression is sub-optimal
It seems that the performance of Linear Regression is sub-optimal when the number of samples is very large.
[sklearn_benchmarks](https://github.com/mbatoul/sklearn_benchmarks) measures a [speedup of 48](https://mbatoul.github.io/sklearn_benchmarks/results/gith... | 22,855 | [
-0.01595933735370636,
0.055361557751894,
0.01789109595119953,
0.04100774973630905,
0.04136230796575546,
-0.012455142103135586,
0.02240644209086895,
0.08614026755094528,
0.037431925535202026,
-0.011811153031885624,
0.020215189084410667,
0.051706183701753616,
0.005083975847810507,
0.02512532... |
https://github.com/scikit-learn/scikit-learn/issues/22855 | [
"Performance",
"module:linear_model"
] | The fit performance of LinearRegression is sub-optimal
It seems that the performance of Linear Regression is sub-optimal when the number of samples is very large.
[sklearn_benchmarks](https://github.com/mbatoul/sklearn_benchmarks) measures a [speedup of 48](https://mbatoul.github.io/sklearn_benchmarks/results/gith... | 22,855 | [
-0.01595933735370636,
0.055361557751894,
0.01789109595119953,
0.04100774973630905,
0.04136230796575546,
-0.012455142103135586,
0.02240644209086895,
0.08614026755094528,
0.037431925535202026,
-0.011811153031885624,
0.020215189084410667,
0.051706183701753616,
0.005083975847810507,
0.02512532... |
https://github.com/scikit-learn/scikit-learn/issues/22855 | [
"Performance",
"module:linear_model"
] | The fit performance of LinearRegression is sub-optimal
It seems that the performance of Linear Regression is sub-optimal when the number of samples is very large.
[sklearn_benchmarks](https://github.com/mbatoul/sklearn_benchmarks) measures a [speedup of 48](https://mbatoul.github.io/sklearn_benchmarks/results/gith... | 22,855 | [
-0.01595933735370636,
0.055361557751894,
0.01789109595119953,
0.04100774973630905,
0.04136230796575546,
-0.012455142103135586,
0.02240644209086895,
0.08614026755094528,
0.037431925535202026,
-0.011811153031885624,
0.020215189084410667,
0.051706183701753616,
0.005083975847810507,
0.02512532... |
https://github.com/scikit-learn/scikit-learn/issues/22855 | [
"Performance",
"module:linear_model"
] | The fit performance of LinearRegression is sub-optimal
It seems that the performance of Linear Regression is sub-optimal when the number of samples is very large.
[sklearn_benchmarks](https://github.com/mbatoul/sklearn_benchmarks) measures a [speedup of 48](https://mbatoul.github.io/sklearn_benchmarks/results/gith... | 22,855 | [
-0.01595933735370636,
0.055361557751894,
0.01789109595119953,
0.04100774973630905,
0.04136230796575546,
-0.012455142103135586,
0.02240644209086895,
0.08614026755094528,
0.037431925535202026,
-0.011811153031885624,
0.020215189084410667,
0.051706183701753616,
0.005083975847810507,
0.02512532... |
https://github.com/scikit-learn/scikit-learn/issues/22855 | [
"Performance",
"module:linear_model"
] | The fit performance of LinearRegression is sub-optimal
It seems that the performance of Linear Regression is sub-optimal when the number of samples is very large.
[sklearn_benchmarks](https://github.com/mbatoul/sklearn_benchmarks) measures a [speedup of 48](https://mbatoul.github.io/sklearn_benchmarks/results/gith... | 22,855 | [
-0.01595933735370636,
0.055361557751894,
0.01789109595119953,
0.04100774973630905,
0.04136230796575546,
-0.012455142103135586,
0.02240644209086895,
0.08614026755094528,
0.037431925535202026,
-0.011811153031885624,
0.020215189084410667,
0.051706183701753616,
0.005083975847810507,
0.02512532... |
https://github.com/scikit-learn/scikit-learn/issues/22855 | [
"Performance",
"module:linear_model"
] | The fit performance of LinearRegression is sub-optimal
It seems that the performance of Linear Regression is sub-optimal when the number of samples is very large.
[sklearn_benchmarks](https://github.com/mbatoul/sklearn_benchmarks) measures a [speedup of 48](https://mbatoul.github.io/sklearn_benchmarks/results/gith... | 22,855 | [
-0.01595933735370636,
0.055361557751894,
0.01789109595119953,
0.04100774973630905,
0.04136230796575546,
-0.012455142103135586,
0.02240644209086895,
0.08614026755094528,
0.037431925535202026,
-0.011811153031885624,
0.020215189084410667,
0.051706183701753616,
0.005083975847810507,
0.02512532... |
https://github.com/scikit-learn/scikit-learn/issues/22855 | [
"Performance",
"module:linear_model"
] | The fit performance of LinearRegression is sub-optimal
It seems that the performance of Linear Regression is sub-optimal when the number of samples is very large.
[sklearn_benchmarks](https://github.com/mbatoul/sklearn_benchmarks) measures a [speedup of 48](https://mbatoul.github.io/sklearn_benchmarks/results/gith... | 22,855 | [
-0.01595933735370636,
0.055361557751894,
0.01789109595119953,
0.04100774973630905,
0.04136230796575546,
-0.012455142103135586,
0.02240644209086895,
0.08614026755094528,
0.037431925535202026,
-0.011811153031885624,
0.020215189084410667,
0.051706183701753616,
0.005083975847810507,
0.02512532... |
https://github.com/scikit-learn/scikit-learn/issues/22855 | [
"Performance",
"module:linear_model"
] | The fit performance of LinearRegression is sub-optimal
It seems that the performance of Linear Regression is sub-optimal when the number of samples is very large.
[sklearn_benchmarks](https://github.com/mbatoul/sklearn_benchmarks) measures a [speedup of 48](https://mbatoul.github.io/sklearn_benchmarks/results/gith... | 22,855 | [
-0.01595933735370636,
0.055361557751894,
0.01789109595119953,
0.04100774973630905,
0.04136230796575546,
-0.012455142103135586,
0.02240644209086895,
0.08614026755094528,
0.037431925535202026,
-0.011811153031885624,
0.020215189084410667,
0.051706183701753616,
0.005083975847810507,
0.02512532... |
https://github.com/scikit-learn/scikit-learn/issues/22855 | [
"Performance",
"module:linear_model"
] | The fit performance of LinearRegression is sub-optimal
It seems that the performance of Linear Regression is sub-optimal when the number of samples is very large.
[sklearn_benchmarks](https://github.com/mbatoul/sklearn_benchmarks) measures a [speedup of 48](https://mbatoul.github.io/sklearn_benchmarks/results/gith... | 22,855 | [
-0.01595933735370636,
0.055361557751894,
0.01789109595119953,
0.04100774973630905,
0.04136230796575546,
-0.012455142103135586,
0.02240644209086895,
0.08614026755094528,
0.037431925535202026,
-0.011811153031885624,
0.020215189084410667,
0.051706183701753616,
0.005083975847810507,
0.02512532... |
https://github.com/scikit-learn/scikit-learn/issues/22855 | [
"Performance",
"module:linear_model"
] | The fit performance of LinearRegression is sub-optimal
It seems that the performance of Linear Regression is sub-optimal when the number of samples is very large.
[sklearn_benchmarks](https://github.com/mbatoul/sklearn_benchmarks) measures a [speedup of 48](https://mbatoul.github.io/sklearn_benchmarks/results/gith... | 22,855 | [
-0.01595933735370636,
0.055361557751894,
0.01789109595119953,
0.04100774973630905,
0.04136230796575546,
-0.012455142103135586,
0.02240644209086895,
0.08614026755094528,
0.037431925535202026,
-0.011811153031885624,
0.020215189084410667,
0.051706183701753616,
0.005083975847810507,
0.02512532... |
https://github.com/scikit-learn/scikit-learn/issues/22855 | [
"Performance",
"module:linear_model"
] | The fit performance of LinearRegression is sub-optimal
It seems that the performance of Linear Regression is sub-optimal when the number of samples is very large.
[sklearn_benchmarks](https://github.com/mbatoul/sklearn_benchmarks) measures a [speedup of 48](https://mbatoul.github.io/sklearn_benchmarks/results/gith... | 22,855 | [
-0.01595933735370636,
0.055361557751894,
0.01789109595119953,
0.04100774973630905,
0.04136230796575546,
-0.012455142103135586,
0.02240644209086895,
0.08614026755094528,
0.037431925535202026,
-0.011811153031885624,
0.020215189084410667,
0.051706183701753616,
0.005083975847810507,
0.02512532... |
https://github.com/scikit-learn/scikit-learn/issues/22855 | [
"Performance",
"module:linear_model"
] | The fit performance of LinearRegression is sub-optimal
It seems that the performance of Linear Regression is sub-optimal when the number of samples is very large.
[sklearn_benchmarks](https://github.com/mbatoul/sklearn_benchmarks) measures a [speedup of 48](https://mbatoul.github.io/sklearn_benchmarks/results/gith... | 22,855 | [
-0.01595933735370636,
0.055361557751894,
0.01789109595119953,
0.04100774973630905,
0.04136230796575546,
-0.012455142103135586,
0.02240644209086895,
0.08614026755094528,
0.037431925535202026,
-0.011811153031885624,
0.020215189084410667,
0.051706183701753616,
0.005083975847810507,
0.02512532... |
https://github.com/scikit-learn/scikit-learn/issues/22855 | [
"Performance",
"module:linear_model"
] | The fit performance of LinearRegression is sub-optimal
It seems that the performance of Linear Regression is sub-optimal when the number of samples is very large.
[sklearn_benchmarks](https://github.com/mbatoul/sklearn_benchmarks) measures a [speedup of 48](https://mbatoul.github.io/sklearn_benchmarks/results/gith... | 22,855 | [
-0.01595933735370636,
0.055361557751894,
0.01789109595119953,
0.04100774973630905,
0.04136230796575546,
-0.012455142103135586,
0.02240644209086895,
0.08614026755094528,
0.037431925535202026,
-0.011811153031885624,
0.020215189084410667,
0.051706183701753616,
0.005083975847810507,
0.02512532... |
https://github.com/scikit-learn/scikit-learn/issues/22855 | [
"Performance",
"module:linear_model"
] | The fit performance of LinearRegression is sub-optimal
It seems that the performance of Linear Regression is sub-optimal when the number of samples is very large.
[sklearn_benchmarks](https://github.com/mbatoul/sklearn_benchmarks) measures a [speedup of 48](https://mbatoul.github.io/sklearn_benchmarks/results/gith... | 22,855 | [
-0.01595933735370636,
0.055361557751894,
0.01789109595119953,
0.04100774973630905,
0.04136230796575546,
-0.012455142103135586,
0.02240644209086895,
0.08614026755094528,
0.037431925535202026,
-0.011811153031885624,
0.020215189084410667,
0.051706183701753616,
0.005083975847810507,
0.02512532... |
https://github.com/scikit-learn/scikit-learn/issues/22855 | [
"Performance",
"module:linear_model"
] | The fit performance of LinearRegression is sub-optimal
It seems that the performance of Linear Regression is sub-optimal when the number of samples is very large.
[sklearn_benchmarks](https://github.com/mbatoul/sklearn_benchmarks) measures a [speedup of 48](https://mbatoul.github.io/sklearn_benchmarks/results/gith... | 22,855 | [
-0.01595933735370636,
0.055361557751894,
0.01789109595119953,
0.04100774973630905,
0.04136230796575546,
-0.012455142103135586,
0.02240644209086895,
0.08614026755094528,
0.037431925535202026,
-0.011811153031885624,
0.020215189084410667,
0.051706183701753616,
0.005083975847810507,
0.02512532... |
https://github.com/scikit-learn/scikit-learn/issues/22855 | [
"Performance",
"module:linear_model"
] | The fit performance of LinearRegression is sub-optimal
It seems that the performance of Linear Regression is sub-optimal when the number of samples is very large.
[sklearn_benchmarks](https://github.com/mbatoul/sklearn_benchmarks) measures a [speedup of 48](https://mbatoul.github.io/sklearn_benchmarks/results/gith... | 22,855 | [
-0.01595933735370636,
0.055361557751894,
0.01789109595119953,
0.04100774973630905,
0.04136230796575546,
-0.012455142103135586,
0.02240644209086895,
0.08614026755094528,
0.037431925535202026,
-0.011811153031885624,
0.020215189084410667,
0.051706183701753616,
0.005083975847810507,
0.02512532... |
https://github.com/scikit-learn/scikit-learn/issues/22855 | [
"Performance",
"module:linear_model"
] | The fit performance of LinearRegression is sub-optimal
It seems that the performance of Linear Regression is sub-optimal when the number of samples is very large.
[sklearn_benchmarks](https://github.com/mbatoul/sklearn_benchmarks) measures a [speedup of 48](https://mbatoul.github.io/sklearn_benchmarks/results/gith... | 22,855 | [
-0.01595933735370636,
0.055361557751894,
0.01789109595119953,
0.04100774973630905,
0.04136230796575546,
-0.012455142103135586,
0.02240644209086895,
0.08614026755094528,
0.037431925535202026,
-0.011811153031885624,
0.020215189084410667,
0.051706183701753616,
0.005083975847810507,
0.02512532... |
https://github.com/scikit-learn/scikit-learn/issues/22855 | [
"Performance",
"module:linear_model"
] | The fit performance of LinearRegression is sub-optimal
It seems that the performance of Linear Regression is sub-optimal when the number of samples is very large.
[sklearn_benchmarks](https://github.com/mbatoul/sklearn_benchmarks) measures a [speedup of 48](https://mbatoul.github.io/sklearn_benchmarks/results/gith... | 22,855 | [
-0.01595933735370636,
0.055361557751894,
0.01789109595119953,
0.04100774973630905,
0.04136230796575546,
-0.012455142103135586,
0.02240644209086895,
0.08614026755094528,
0.037431925535202026,
-0.011811153031885624,
0.020215189084410667,
0.051706183701753616,
0.005083975847810507,
0.02512532... |
https://github.com/scikit-learn/scikit-learn/issues/22855 | [
"Performance",
"module:linear_model"
] | The fit performance of LinearRegression is sub-optimal
It seems that the performance of Linear Regression is sub-optimal when the number of samples is very large.
[sklearn_benchmarks](https://github.com/mbatoul/sklearn_benchmarks) measures a [speedup of 48](https://mbatoul.github.io/sklearn_benchmarks/results/gith... | 22,855 | [
-0.01595933735370636,
0.055361557751894,
0.01789109595119953,
0.04100774973630905,
0.04136230796575546,
-0.012455142103135586,
0.02240644209086895,
0.08614026755094528,
0.037431925535202026,
-0.011811153031885624,
0.020215189084410667,
0.051706183701753616,
0.005083975847810507,
0.02512532... |
https://github.com/scikit-learn/scikit-learn/issues/22855 | [
"Performance",
"module:linear_model"
] | The fit performance of LinearRegression is sub-optimal
It seems that the performance of Linear Regression is sub-optimal when the number of samples is very large.
[sklearn_benchmarks](https://github.com/mbatoul/sklearn_benchmarks) measures a [speedup of 48](https://mbatoul.github.io/sklearn_benchmarks/results/gith... | 22,855 | [
-0.01595933735370636,
0.055361557751894,
0.01789109595119953,
0.04100774973630905,
0.04136230796575546,
-0.012455142103135586,
0.02240644209086895,
0.08614026755094528,
0.037431925535202026,
-0.011811153031885624,
0.020215189084410667,
0.051706183701753616,
0.005083975847810507,
0.02512532... |
https://github.com/scikit-learn/scikit-learn/issues/22855 | [
"Performance",
"module:linear_model"
] | The fit performance of LinearRegression is sub-optimal
It seems that the performance of Linear Regression is sub-optimal when the number of samples is very large.
[sklearn_benchmarks](https://github.com/mbatoul/sklearn_benchmarks) measures a [speedup of 48](https://mbatoul.github.io/sklearn_benchmarks/results/gith... | 22,855 | [
-0.01595933735370636,
0.055361557751894,
0.01789109595119953,
0.04100774973630905,
0.04136230796575546,
-0.012455142103135586,
0.02240644209086895,
0.08614026755094528,
0.037431925535202026,
-0.011811153031885624,
0.020215189084410667,
0.051706183701753616,
0.005083975847810507,
0.02512532... |
https://github.com/scikit-learn/scikit-learn/issues/22855 | [
"Performance",
"module:linear_model"
] | The fit performance of LinearRegression is sub-optimal
It seems that the performance of Linear Regression is sub-optimal when the number of samples is very large.
[sklearn_benchmarks](https://github.com/mbatoul/sklearn_benchmarks) measures a [speedup of 48](https://mbatoul.github.io/sklearn_benchmarks/results/gith... | 22,855 | [
-0.01595933735370636,
0.055361557751894,
0.01789109595119953,
0.04100774973630905,
0.04136230796575546,
-0.012455142103135586,
0.02240644209086895,
0.08614026755094528,
0.037431925535202026,
-0.011811153031885624,
0.020215189084410667,
0.051706183701753616,
0.005083975847810507,
0.02512532... |
https://github.com/scikit-learn/scikit-learn/issues/22855 | [
"Performance",
"module:linear_model"
] | The fit performance of LinearRegression is sub-optimal
It seems that the performance of Linear Regression is sub-optimal when the number of samples is very large.
[sklearn_benchmarks](https://github.com/mbatoul/sklearn_benchmarks) measures a [speedup of 48](https://mbatoul.github.io/sklearn_benchmarks/results/gith... | 22,855 | [
-0.01595933735370636,
0.055361557751894,
0.01789109595119953,
0.04100774973630905,
0.04136230796575546,
-0.012455142103135586,
0.02240644209086895,
0.08614026755094528,
0.037431925535202026,
-0.011811153031885624,
0.020215189084410667,
0.051706183701753616,
0.005083975847810507,
0.02512532... |
https://github.com/scikit-learn/scikit-learn/issues/22854 | [
"Bug",
"module:cluster"
] | Birch is not finding clusters correctly
### Describe the bug
Birch do not correctly find clusters if the number of samples of one cluster is much larger than another cluster even if the distance between clusters is much larger than threshold.
### Steps/Code to Reproduce
```python
from sklearn.datasets import... | 22,854 | [
0.014128658920526505,
-0.13125446438789368,
-0.009700923226773739,
0.040759291499853134,
0.04966798424720764,
-0.037800997495651245,
-0.00010608160664560273,
0.030743174254894257,
0.04124242067337036,
0.03086843527853489,
0.003091713646426797,
0.029888520017266273,
-0.025059321895241737,
0... |
https://github.com/scikit-learn/scikit-learn/issues/22854 | [
"Bug",
"module:cluster"
] | Birch is not finding clusters correctly
### Describe the bug
Birch do not correctly find clusters if the number of samples of one cluster is much larger than another cluster even if the distance between clusters is much larger than threshold.
### Steps/Code to Reproduce
```python
from sklearn.datasets import... | 22,854 | [
0.014128658920526505,
-0.13125446438789368,
-0.009700923226773739,
0.040759291499853134,
0.04966798424720764,
-0.037800997495651245,
-0.00010608160664560273,
0.030743174254894257,
0.04124242067337036,
0.03086843527853489,
0.003091713646426797,
0.029888520017266273,
-0.025059321895241737,
0... |
https://github.com/scikit-learn/scikit-learn/issues/22854 | [
"Bug",
"module:cluster"
] | Birch is not finding clusters correctly
### Describe the bug
Birch do not correctly find clusters if the number of samples of one cluster is much larger than another cluster even if the distance between clusters is much larger than threshold.
### Steps/Code to Reproduce
```python
from sklearn.datasets import... | 22,854 | [
0.014128658920526505,
-0.13125446438789368,
-0.009700923226773739,
0.040759291499853134,
0.04966798424720764,
-0.037800997495651245,
-0.00010608160664560273,
0.030743174254894257,
0.04124242067337036,
0.03086843527853489,
0.003091713646426797,
0.029888520017266273,
-0.025059321895241737,
0... |
https://github.com/scikit-learn/scikit-learn/issues/22854 | [
"Bug",
"module:cluster"
] | Birch is not finding clusters correctly
### Describe the bug
Birch do not correctly find clusters if the number of samples of one cluster is much larger than another cluster even if the distance between clusters is much larger than threshold.
### Steps/Code to Reproduce
```python
from sklearn.datasets import... | 22,854 | [
0.014128658920526505,
-0.13125446438789368,
-0.009700923226773739,
0.040759291499853134,
0.04966798424720764,
-0.037800997495651245,
-0.00010608160664560273,
0.030743174254894257,
0.04124242067337036,
0.03086843527853489,
0.003091713646426797,
0.029888520017266273,
-0.025059321895241737,
0... |
https://github.com/scikit-learn/scikit-learn/issues/22854 | [
"Bug",
"module:cluster"
] | Birch is not finding clusters correctly
### Describe the bug
Birch do not correctly find clusters if the number of samples of one cluster is much larger than another cluster even if the distance between clusters is much larger than threshold.
### Steps/Code to Reproduce
```python
from sklearn.datasets import... | 22,854 | [
0.014128658920526505,
-0.13125446438789368,
-0.009700923226773739,
0.040759291499853134,
0.04966798424720764,
-0.037800997495651245,
-0.00010608160664560273,
0.030743174254894257,
0.04124242067337036,
0.03086843527853489,
0.003091713646426797,
0.029888520017266273,
-0.025059321895241737,
0... |
https://github.com/scikit-learn/scikit-learn/issues/22854 | [
"Bug",
"module:cluster"
] | Birch is not finding clusters correctly
### Describe the bug
Birch do not correctly find clusters if the number of samples of one cluster is much larger than another cluster even if the distance between clusters is much larger than threshold.
### Steps/Code to Reproduce
```python
from sklearn.datasets import... | 22,854 | [
0.014128658920526505,
-0.13125446438789368,
-0.009700923226773739,
0.040759291499853134,
0.04966798424720764,
-0.037800997495651245,
-0.00010608160664560273,
0.030743174254894257,
0.04124242067337036,
0.03086843527853489,
0.003091713646426797,
0.029888520017266273,
-0.025059321895241737,
0... |
https://github.com/scikit-learn/scikit-learn/issues/22853 | [
"Build / CI",
"RFC"
] | RFC isort as linter and import sorter
What do we think of [`isort`](https://github.com/PyCQA/isort)? I've seen it in other projects and seems like a sane tool.
We could add it to our linter and pre-commit hooks if others think it's a good thing. It does look nice to me.
Looking at the import section of `test_com... | 22,853 | [
0.00193729845341295,
0.06226644665002823,
0.01023793499916792,
-0.01613743044435978,
-0.0173028651624918,
-0.0008934984798543155,
0.053621191531419754,
0.0389251708984375,
0.03628338873386383,
-0.03318507969379425,
0.010379445739090443,
0.02348955161869526,
-0.027401570230722427,
0.0709133... |
https://github.com/scikit-learn/scikit-learn/issues/22853 | [
"Build / CI",
"RFC"
] | RFC isort as linter and import sorter
What do we think of [`isort`](https://github.com/PyCQA/isort)? I've seen it in other projects and seems like a sane tool.
We could add it to our linter and pre-commit hooks if others think it's a good thing. It does look nice to me.
Looking at the import section of `test_com... | 22,853 | [
0.00193729845341295,
0.06226644665002823,
0.01023793499916792,
-0.01613743044435978,
-0.0173028651624918,
-0.0008934984798543155,
0.053621191531419754,
0.0389251708984375,
0.03628338873386383,
-0.03318507969379425,
0.010379445739090443,
0.02348955161869526,
-0.027401570230722427,
0.0709133... |
https://github.com/scikit-learn/scikit-learn/issues/22853 | [
"Build / CI",
"RFC"
] | RFC isort as linter and import sorter
What do we think of [`isort`](https://github.com/PyCQA/isort)? I've seen it in other projects and seems like a sane tool.
We could add it to our linter and pre-commit hooks if others think it's a good thing. It does look nice to me.
Looking at the import section of `test_com... | 22,853 | [
0.00193729845341295,
0.06226644665002823,
0.01023793499916792,
-0.01613743044435978,
-0.0173028651624918,
-0.0008934984798543155,
0.053621191531419754,
0.0389251708984375,
0.03628338873386383,
-0.03318507969379425,
0.010379445739090443,
0.02348955161869526,
-0.027401570230722427,
0.0709133... |
https://github.com/scikit-learn/scikit-learn/issues/22853 | [
"Build / CI",
"RFC"
] | RFC isort as linter and import sorter
What do we think of [`isort`](https://github.com/PyCQA/isort)? I've seen it in other projects and seems like a sane tool.
We could add it to our linter and pre-commit hooks if others think it's a good thing. It does look nice to me.
Looking at the import section of `test_com... | 22,853 | [
0.00193729845341295,
0.06226644665002823,
0.01023793499916792,
-0.01613743044435978,
-0.0173028651624918,
-0.0008934984798543155,
0.053621191531419754,
0.0389251708984375,
0.03628338873386383,
-0.03318507969379425,
0.010379445739090443,
0.02348955161869526,
-0.027401570230722427,
0.0709133... |
https://github.com/scikit-learn/scikit-learn/issues/22853 | [
"Build / CI",
"RFC"
] | RFC isort as linter and import sorter
What do we think of [`isort`](https://github.com/PyCQA/isort)? I've seen it in other projects and seems like a sane tool.
We could add it to our linter and pre-commit hooks if others think it's a good thing. It does look nice to me.
Looking at the import section of `test_com... | 22,853 | [
0.00193729845341295,
0.06226644665002823,
0.01023793499916792,
-0.01613743044435978,
-0.0173028651624918,
-0.0008934984798543155,
0.053621191531419754,
0.0389251708984375,
0.03628338873386383,
-0.03318507969379425,
0.010379445739090443,
0.02348955161869526,
-0.027401570230722427,
0.0709133... |
https://github.com/scikit-learn/scikit-learn/issues/22853 | [
"Build / CI",
"RFC"
] | RFC isort as linter and import sorter
What do we think of [`isort`](https://github.com/PyCQA/isort)? I've seen it in other projects and seems like a sane tool.
We could add it to our linter and pre-commit hooks if others think it's a good thing. It does look nice to me.
Looking at the import section of `test_com... | 22,853 | [
0.00193729845341295,
0.06226644665002823,
0.01023793499916792,
-0.01613743044435978,
-0.0173028651624918,
-0.0008934984798543155,
0.053621191531419754,
0.0389251708984375,
0.03628338873386383,
-0.03318507969379425,
0.010379445739090443,
0.02348955161869526,
-0.027401570230722427,
0.0709133... |
https://github.com/scikit-learn/scikit-learn/issues/22853 | [
"Build / CI",
"RFC"
] | RFC isort as linter and import sorter
What do we think of [`isort`](https://github.com/PyCQA/isort)? I've seen it in other projects and seems like a sane tool.
We could add it to our linter and pre-commit hooks if others think it's a good thing. It does look nice to me.
Looking at the import section of `test_com... | 22,853 | [
0.00193729845341295,
0.06226644665002823,
0.01023793499916792,
-0.01613743044435978,
-0.0173028651624918,
-0.0008934984798543155,
0.053621191531419754,
0.0389251708984375,
0.03628338873386383,
-0.03318507969379425,
0.010379445739090443,
0.02348955161869526,
-0.027401570230722427,
0.0709133... |
https://github.com/scikit-learn/scikit-learn/issues/22853 | [
"Build / CI",
"RFC"
] | RFC isort as linter and import sorter
What do we think of [`isort`](https://github.com/PyCQA/isort)? I've seen it in other projects and seems like a sane tool.
We could add it to our linter and pre-commit hooks if others think it's a good thing. It does look nice to me.
Looking at the import section of `test_com... | 22,853 | [
0.00193729845341295,
0.06226644665002823,
0.01023793499916792,
-0.01613743044435978,
-0.0173028651624918,
-0.0008934984798543155,
0.053621191531419754,
0.0389251708984375,
0.03628338873386383,
-0.03318507969379425,
0.010379445739090443,
0.02348955161869526,
-0.027401570230722427,
0.0709133... |
https://github.com/scikit-learn/scikit-learn/issues/22853 | [
"Build / CI",
"RFC"
] | RFC isort as linter and import sorter
What do we think of [`isort`](https://github.com/PyCQA/isort)? I've seen it in other projects and seems like a sane tool.
We could add it to our linter and pre-commit hooks if others think it's a good thing. It does look nice to me.
Looking at the import section of `test_com... | 22,853 | [
0.00193729845341295,
0.06226644665002823,
0.01023793499916792,
-0.01613743044435978,
-0.0173028651624918,
-0.0008934984798543155,
0.053621191531419754,
0.0389251708984375,
0.03628338873386383,
-0.03318507969379425,
0.010379445739090443,
0.02348955161869526,
-0.027401570230722427,
0.0709133... |
https://github.com/scikit-learn/scikit-learn/issues/22853 | [
"Build / CI",
"RFC"
] | RFC isort as linter and import sorter
What do we think of [`isort`](https://github.com/PyCQA/isort)? I've seen it in other projects and seems like a sane tool.
We could add it to our linter and pre-commit hooks if others think it's a good thing. It does look nice to me.
Looking at the import section of `test_com... | 22,853 | [
0.00193729845341295,
0.06226644665002823,
0.01023793499916792,
-0.01613743044435978,
-0.0173028651624918,
-0.0008934984798543155,
0.053621191531419754,
0.0389251708984375,
0.03628338873386383,
-0.03318507969379425,
0.010379445739090443,
0.02348955161869526,
-0.027401570230722427,
0.0709133... |
https://github.com/scikit-learn/scikit-learn/issues/22853 | [
"Build / CI",
"RFC"
] | RFC isort as linter and import sorter
What do we think of [`isort`](https://github.com/PyCQA/isort)? I've seen it in other projects and seems like a sane tool.
We could add it to our linter and pre-commit hooks if others think it's a good thing. It does look nice to me.
Looking at the import section of `test_com... | 22,853 | [
0.00193729845341295,
0.06226644665002823,
0.01023793499916792,
-0.01613743044435978,
-0.0173028651624918,
-0.0008934984798543155,
0.053621191531419754,
0.0389251708984375,
0.03628338873386383,
-0.03318507969379425,
0.010379445739090443,
0.02348955161869526,
-0.027401570230722427,
0.0709133... |
https://github.com/scikit-learn/scikit-learn/issues/22853 | [
"Build / CI",
"RFC"
] | RFC isort as linter and import sorter
What do we think of [`isort`](https://github.com/PyCQA/isort)? I've seen it in other projects and seems like a sane tool.
We could add it to our linter and pre-commit hooks if others think it's a good thing. It does look nice to me.
Looking at the import section of `test_com... | 22,853 | [
0.00193729845341295,
0.06226644665002823,
0.01023793499916792,
-0.01613743044435978,
-0.0173028651624918,
-0.0008934984798543155,
0.053621191531419754,
0.0389251708984375,
0.03628338873386383,
-0.03318507969379425,
0.010379445739090443,
0.02348955161869526,
-0.027401570230722427,
0.0709133... |
https://github.com/scikit-learn/scikit-learn/issues/22853 | [
"Build / CI",
"RFC"
] | RFC isort as linter and import sorter
What do we think of [`isort`](https://github.com/PyCQA/isort)? I've seen it in other projects and seems like a sane tool.
We could add it to our linter and pre-commit hooks if others think it's a good thing. It does look nice to me.
Looking at the import section of `test_com... | 22,853 | [
0.00193729845341295,
0.06226644665002823,
0.01023793499916792,
-0.01613743044435978,
-0.0173028651624918,
-0.0008934984798543155,
0.053621191531419754,
0.0389251708984375,
0.03628338873386383,
-0.03318507969379425,
0.010379445739090443,
0.02348955161869526,
-0.027401570230722427,
0.0709133... |
https://github.com/scikit-learn/scikit-learn/issues/22853 | [
"Build / CI",
"RFC"
] | RFC isort as linter and import sorter
What do we think of [`isort`](https://github.com/PyCQA/isort)? I've seen it in other projects and seems like a sane tool.
We could add it to our linter and pre-commit hooks if others think it's a good thing. It does look nice to me.
Looking at the import section of `test_com... | 22,853 | [
0.00193729845341295,
0.06226644665002823,
0.01023793499916792,
-0.01613743044435978,
-0.0173028651624918,
-0.0008934984798543155,
0.053621191531419754,
0.0389251708984375,
0.03628338873386383,
-0.03318507969379425,
0.010379445739090443,
0.02348955161869526,
-0.027401570230722427,
0.0709133... |
https://github.com/scikit-learn/scikit-learn/issues/22853 | [
"Build / CI",
"RFC"
] | RFC isort as linter and import sorter
What do we think of [`isort`](https://github.com/PyCQA/isort)? I've seen it in other projects and seems like a sane tool.
We could add it to our linter and pre-commit hooks if others think it's a good thing. It does look nice to me.
Looking at the import section of `test_com... | 22,853 | [
0.00193729845341295,
0.06226644665002823,
0.01023793499916792,
-0.01613743044435978,
-0.0173028651624918,
-0.0008934984798543155,
0.053621191531419754,
0.0389251708984375,
0.03628338873386383,
-0.03318507969379425,
0.010379445739090443,
0.02348955161869526,
-0.027401570230722427,
0.0709133... |
https://github.com/scikit-learn/scikit-learn/issues/22853 | [
"Build / CI",
"RFC"
] | RFC isort as linter and import sorter
What do we think of [`isort`](https://github.com/PyCQA/isort)? I've seen it in other projects and seems like a sane tool.
We could add it to our linter and pre-commit hooks if others think it's a good thing. It does look nice to me.
Looking at the import section of `test_com... | 22,853 | [
0.00193729845341295,
0.06226644665002823,
0.01023793499916792,
-0.01613743044435978,
-0.0173028651624918,
-0.0008934984798543155,
0.053621191531419754,
0.0389251708984375,
0.03628338873386383,
-0.03318507969379425,
0.010379445739090443,
0.02348955161869526,
-0.027401570230722427,
0.0709133... |
https://github.com/scikit-learn/scikit-learn/issues/22853 | [
"Build / CI",
"RFC"
] | RFC isort as linter and import sorter
What do we think of [`isort`](https://github.com/PyCQA/isort)? I've seen it in other projects and seems like a sane tool.
We could add it to our linter and pre-commit hooks if others think it's a good thing. It does look nice to me.
Looking at the import section of `test_com... | 22,853 | [
0.00193729845341295,
0.06226644665002823,
0.01023793499916792,
-0.01613743044435978,
-0.0173028651624918,
-0.0008934984798543155,
0.053621191531419754,
0.0389251708984375,
0.03628338873386383,
-0.03318507969379425,
0.010379445739090443,
0.02348955161869526,
-0.027401570230722427,
0.0709133... |
https://github.com/scikit-learn/scikit-learn/issues/22849 | [
"Bug",
"module:model_selection",
"Needs Investigation"
] | Verbosity option is not working in GridSearchCV (Jupyter notebook)
### Describe the bug
So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) respon... | 22,849 | [
-0.010656674392521381,
-0.005562886595726013,
0.0047599077224731445,
0.012024560011923313,
0.029358087107539177,
-0.03818982094526291,
0.013727138750255108,
0.053780052810907364,
0.015587331727147102,
0.02820076234638691,
0.05128288269042969,
0.034039586782455444,
-0.01790706440806389,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/22849 | [
"Bug",
"module:model_selection",
"Needs Investigation"
] | Verbosity option is not working in GridSearchCV (Jupyter notebook)
### Describe the bug
So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) respon... | 22,849 | [
-0.010656674392521381,
-0.005562886595726013,
0.0047599077224731445,
0.012024560011923313,
0.029358087107539177,
-0.03818982094526291,
0.013727138750255108,
0.053780052810907364,
0.015587331727147102,
0.02820076234638691,
0.05128288269042969,
0.034039586782455444,
-0.01790706440806389,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/22849 | [
"Bug",
"module:model_selection",
"Needs Investigation"
] | Verbosity option is not working in GridSearchCV (Jupyter notebook)
### Describe the bug
So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) respon... | 22,849 | [
-0.010656674392521381,
-0.005562886595726013,
0.0047599077224731445,
0.012024560011923313,
0.029358087107539177,
-0.03818982094526291,
0.013727138750255108,
0.053780052810907364,
0.015587331727147102,
0.02820076234638691,
0.05128288269042969,
0.034039586782455444,
-0.01790706440806389,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/22849 | [
"Bug",
"module:model_selection",
"Needs Investigation"
] | Verbosity option is not working in GridSearchCV (Jupyter notebook)
### Describe the bug
So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) respon... | 22,849 | [
-0.010656674392521381,
-0.005562886595726013,
0.0047599077224731445,
0.012024560011923313,
0.029358087107539177,
-0.03818982094526291,
0.013727138750255108,
0.053780052810907364,
0.015587331727147102,
0.02820076234638691,
0.05128288269042969,
0.034039586782455444,
-0.01790706440806389,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/22849 | [
"Bug",
"module:model_selection",
"Needs Investigation"
] | Verbosity option is not working in GridSearchCV (Jupyter notebook)
### Describe the bug
So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) respon... | 22,849 | [
-0.010656674392521381,
-0.005562886595726013,
0.0047599077224731445,
0.012024560011923313,
0.029358087107539177,
-0.03818982094526291,
0.013727138750255108,
0.053780052810907364,
0.015587331727147102,
0.02820076234638691,
0.05128288269042969,
0.034039586782455444,
-0.01790706440806389,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/22849 | [
"Bug",
"module:model_selection",
"Needs Investigation"
] | Verbosity option is not working in GridSearchCV (Jupyter notebook)
### Describe the bug
So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) respon... | 22,849 | [
-0.010656674392521381,
-0.005562886595726013,
0.0047599077224731445,
0.012024560011923313,
0.029358087107539177,
-0.03818982094526291,
0.013727138750255108,
0.053780052810907364,
0.015587331727147102,
0.02820076234638691,
0.05128288269042969,
0.034039586782455444,
-0.01790706440806389,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/22849 | [
"Bug",
"module:model_selection",
"Needs Investigation"
] | Verbosity option is not working in GridSearchCV (Jupyter notebook)
### Describe the bug
So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) respon... | 22,849 | [
-0.010656674392521381,
-0.005562886595726013,
0.0047599077224731445,
0.012024560011923313,
0.029358087107539177,
-0.03818982094526291,
0.013727138750255108,
0.053780052810907364,
0.015587331727147102,
0.02820076234638691,
0.05128288269042969,
0.034039586782455444,
-0.01790706440806389,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/22849 | [
"Bug",
"module:model_selection",
"Needs Investigation"
] | Verbosity option is not working in GridSearchCV (Jupyter notebook)
### Describe the bug
So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) respon... | 22,849 | [
-0.010656674392521381,
-0.005562886595726013,
0.0047599077224731445,
0.012024560011923313,
0.029358087107539177,
-0.03818982094526291,
0.013727138750255108,
0.053780052810907364,
0.015587331727147102,
0.02820076234638691,
0.05128288269042969,
0.034039586782455444,
-0.01790706440806389,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/22849 | [
"Bug",
"module:model_selection",
"Needs Investigation"
] | Verbosity option is not working in GridSearchCV (Jupyter notebook)
### Describe the bug
So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) respon... | 22,849 | [
-0.010656674392521381,
-0.005562886595726013,
0.0047599077224731445,
0.012024560011923313,
0.029358087107539177,
-0.03818982094526291,
0.013727138750255108,
0.053780052810907364,
0.015587331727147102,
0.02820076234638691,
0.05128288269042969,
0.034039586782455444,
-0.01790706440806389,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/22849 | [
"Bug",
"module:model_selection",
"Needs Investigation"
] | Verbosity option is not working in GridSearchCV (Jupyter notebook)
### Describe the bug
So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) respon... | 22,849 | [
-0.010656674392521381,
-0.005562886595726013,
0.0047599077224731445,
0.012024560011923313,
0.029358087107539177,
-0.03818982094526291,
0.013727138750255108,
0.053780052810907364,
0.015587331727147102,
0.02820076234638691,
0.05128288269042969,
0.034039586782455444,
-0.01790706440806389,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/22849 | [
"Bug",
"module:model_selection",
"Needs Investigation"
] | Verbosity option is not working in GridSearchCV (Jupyter notebook)
### Describe the bug
So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) respon... | 22,849 | [
-0.010656674392521381,
-0.005562886595726013,
0.0047599077224731445,
0.012024560011923313,
0.029358087107539177,
-0.03818982094526291,
0.013727138750255108,
0.053780052810907364,
0.015587331727147102,
0.02820076234638691,
0.05128288269042969,
0.034039586782455444,
-0.01790706440806389,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/22849 | [
"Bug",
"module:model_selection",
"Needs Investigation"
] | Verbosity option is not working in GridSearchCV (Jupyter notebook)
### Describe the bug
So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) respon... | 22,849 | [
-0.010656674392521381,
-0.005562886595726013,
0.0047599077224731445,
0.012024560011923313,
0.029358087107539177,
-0.03818982094526291,
0.013727138750255108,
0.053780052810907364,
0.015587331727147102,
0.02820076234638691,
0.05128288269042969,
0.034039586782455444,
-0.01790706440806389,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/22849 | [
"Bug",
"module:model_selection",
"Needs Investigation"
] | Verbosity option is not working in GridSearchCV (Jupyter notebook)
### Describe the bug
So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) respon... | 22,849 | [
-0.010656674392521381,
-0.005562886595726013,
0.0047599077224731445,
0.012024560011923313,
0.029358087107539177,
-0.03818982094526291,
0.013727138750255108,
0.053780052810907364,
0.015587331727147102,
0.02820076234638691,
0.05128288269042969,
0.034039586782455444,
-0.01790706440806389,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/22849 | [
"Bug",
"module:model_selection",
"Needs Investigation"
] | Verbosity option is not working in GridSearchCV (Jupyter notebook)
### Describe the bug
So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) respon... | 22,849 | [
-0.010656674392521381,
-0.005562886595726013,
0.0047599077224731445,
0.012024560011923313,
0.029358087107539177,
-0.03818982094526291,
0.013727138750255108,
0.053780052810907364,
0.015587331727147102,
0.02820076234638691,
0.05128288269042969,
0.034039586782455444,
-0.01790706440806389,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/22849 | [
"Bug",
"module:model_selection",
"Needs Investigation"
] | Verbosity option is not working in GridSearchCV (Jupyter notebook)
### Describe the bug
So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) respon... | 22,849 | [
-0.010656674392521381,
-0.005562886595726013,
0.0047599077224731445,
0.012024560011923313,
0.029358087107539177,
-0.03818982094526291,
0.013727138750255108,
0.053780052810907364,
0.015587331727147102,
0.02820076234638691,
0.05128288269042969,
0.034039586782455444,
-0.01790706440806389,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/22849 | [
"Bug",
"module:model_selection",
"Needs Investigation"
] | Verbosity option is not working in GridSearchCV (Jupyter notebook)
### Describe the bug
So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) respon... | 22,849 | [
-0.010656674392521381,
-0.005562886595726013,
0.0047599077224731445,
0.012024560011923313,
0.029358087107539177,
-0.03818982094526291,
0.013727138750255108,
0.053780052810907364,
0.015587331727147102,
0.02820076234638691,
0.05128288269042969,
0.034039586782455444,
-0.01790706440806389,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/22849 | [
"Bug",
"module:model_selection",
"Needs Investigation"
] | Verbosity option is not working in GridSearchCV (Jupyter notebook)
### Describe the bug
So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) respon... | 22,849 | [
-0.010656674392521381,
-0.005562886595726013,
0.0047599077224731445,
0.012024560011923313,
0.029358087107539177,
-0.03818982094526291,
0.013727138750255108,
0.053780052810907364,
0.015587331727147102,
0.02820076234638691,
0.05128288269042969,
0.034039586782455444,
-0.01790706440806389,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/22849 | [
"Bug",
"module:model_selection",
"Needs Investigation"
] | Verbosity option is not working in GridSearchCV (Jupyter notebook)
### Describe the bug
So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) respon... | 22,849 | [
-0.010656674392521381,
-0.005562886595726013,
0.0047599077224731445,
0.012024560011923313,
0.029358087107539177,
-0.03818982094526291,
0.013727138750255108,
0.053780052810907364,
0.015587331727147102,
0.02820076234638691,
0.05128288269042969,
0.034039586782455444,
-0.01790706440806389,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/22849 | [
"Bug",
"module:model_selection",
"Needs Investigation"
] | Verbosity option is not working in GridSearchCV (Jupyter notebook)
### Describe the bug
So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) respon... | 22,849 | [
-0.010656674392521381,
-0.005562886595726013,
0.0047599077224731445,
0.012024560011923313,
0.029358087107539177,
-0.03818982094526291,
0.013727138750255108,
0.053780052810907364,
0.015587331727147102,
0.02820076234638691,
0.05128288269042969,
0.034039586782455444,
-0.01790706440806389,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/22849 | [
"Bug",
"module:model_selection",
"Needs Investigation"
] | Verbosity option is not working in GridSearchCV (Jupyter notebook)
### Describe the bug
So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) respon... | 22,849 | [
-0.010656674392521381,
-0.005562886595726013,
0.0047599077224731445,
0.012024560011923313,
0.029358087107539177,
-0.03818982094526291,
0.013727138750255108,
0.053780052810907364,
0.015587331727147102,
0.02820076234638691,
0.05128288269042969,
0.034039586782455444,
-0.01790706440806389,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/22849 | [
"Bug",
"module:model_selection",
"Needs Investigation"
] | Verbosity option is not working in GridSearchCV (Jupyter notebook)
### Describe the bug
So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) respon... | 22,849 | [
-0.010656674392521381,
-0.005562886595726013,
0.0047599077224731445,
0.012024560011923313,
0.029358087107539177,
-0.03818982094526291,
0.013727138750255108,
0.053780052810907364,
0.015587331727147102,
0.02820076234638691,
0.05128288269042969,
0.034039586782455444,
-0.01790706440806389,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/22849 | [
"Bug",
"module:model_selection",
"Needs Investigation"
] | Verbosity option is not working in GridSearchCV (Jupyter notebook)
### Describe the bug
So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) respon... | 22,849 | [
-0.010656674392521381,
-0.005562886595726013,
0.0047599077224731445,
0.012024560011923313,
0.029358087107539177,
-0.03818982094526291,
0.013727138750255108,
0.053780052810907364,
0.015587331727147102,
0.02820076234638691,
0.05128288269042969,
0.034039586782455444,
-0.01790706440806389,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/22849 | [
"Bug",
"module:model_selection",
"Needs Investigation"
] | Verbosity option is not working in GridSearchCV (Jupyter notebook)
### Describe the bug
So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) respon... | 22,849 | [
-0.010656674392521381,
-0.005562886595726013,
0.0047599077224731445,
0.012024560011923313,
0.029358087107539177,
-0.03818982094526291,
0.013727138750255108,
0.053780052810907364,
0.015587331727147102,
0.02820076234638691,
0.05128288269042969,
0.034039586782455444,
-0.01790706440806389,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/22848 | [
"Documentation",
"Moderate",
"module:model_selection"
] | KFold splitter falsely claims it supports groups
@thomasjpfan : (taken from https://github.com/scikit-learn/scikit-learn/pull/22765/files#r825487547)
> My mind is a little blown. So the current API for KFold.split has a groups parameter it never uses. Because of the inheritance structure, the [API docs for KFold.sp... | 22,848 | [
0.016218701377511024,
0.04098896682262421,
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0.02955120988190174,
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0.08353368937969208,
0.01579519920051098,
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0.001977920066565275,
0.018356667831540108,
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0.... |
https://github.com/scikit-learn/scikit-learn/issues/22848 | [
"Documentation",
"Moderate",
"module:model_selection"
] | KFold splitter falsely claims it supports groups
@thomasjpfan : (taken from https://github.com/scikit-learn/scikit-learn/pull/22765/files#r825487547)
> My mind is a little blown. So the current API for KFold.split has a groups parameter it never uses. Because of the inheritance structure, the [API docs for KFold.sp... | 22,848 | [
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0.030069468542933464,
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0.024408545345067978,
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0.025007303804159164,
0.0023394885938614607,
... |
https://github.com/scikit-learn/scikit-learn/issues/22848 | [
"Documentation",
"Moderate",
"module:model_selection"
] | KFold splitter falsely claims it supports groups
@thomasjpfan : (taken from https://github.com/scikit-learn/scikit-learn/pull/22765/files#r825487547)
> My mind is a little blown. So the current API for KFold.split has a groups parameter it never uses. Because of the inheritance structure, the [API docs for KFold.sp... | 22,848 | [
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0.02894599735736847,
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0.008953450247645378,
0.02232315205037594,
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0... |
https://github.com/scikit-learn/scikit-learn/issues/22848 | [
"Documentation",
"Moderate",
"module:model_selection"
] | KFold splitter falsely claims it supports groups
@thomasjpfan : (taken from https://github.com/scikit-learn/scikit-learn/pull/22765/files#r825487547)
> My mind is a little blown. So the current API for KFold.split has a groups parameter it never uses. Because of the inheritance structure, the [API docs for KFold.sp... | 22,848 | [
0.01964263617992401,
0.02018747292459011,
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0.... |
https://github.com/scikit-learn/scikit-learn/issues/22848 | [
"Documentation",
"Moderate",
"module:model_selection"
] | KFold splitter falsely claims it supports groups
@thomasjpfan : (taken from https://github.com/scikit-learn/scikit-learn/pull/22765/files#r825487547)
> My mind is a little blown. So the current API for KFold.split has a groups parameter it never uses. Because of the inheritance structure, the [API docs for KFold.sp... | 22,848 | [
0.020151281729340553,
0.027666453272104263,
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0.01940445601940155,
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0.006727384869009256,
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... |
https://github.com/scikit-learn/scikit-learn/issues/22848 | [
"Documentation",
"Moderate",
"module:model_selection"
] | KFold splitter falsely claims it supports groups
@thomasjpfan : (taken from https://github.com/scikit-learn/scikit-learn/pull/22765/files#r825487547)
> My mind is a little blown. So the current API for KFold.split has a groups parameter it never uses. Because of the inheritance structure, the [API docs for KFold.sp... | 22,848 | [
0.0025025419890880585,
0.028440216556191444,
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0.01866208203136921,
0.020681720227003098,
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0.08606555312871933,
0.016361868008971214,
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0.02490047924220562,
0.018077949061989784,
-0.013395681045949459,
0.... |
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