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/30339 | [
"Documentation"
] | DOC: clarify the documentation for the loss functions used in GBRT, and Absolute Error in particular.
### Describe the bug
From my understanding, currently there is no way to minimize the MAE (Mean Absolute Error). Quantile regression with quantile=0.5 will optimize for the Median Absolute Error. This would be diff... | 30,339 | [
0.009657524526119232,
0.01976901851594448,
0.019382908940315247,
-0.03308308124542236,
0.039128199219703674,
0.020444270223379135,
-0.024539494886994362,
0.06466154009103775,
-0.02437586337327957,
0.02551424503326416,
0.045189566910266876,
-0.017183378338813782,
0.0026089660823345184,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/30339 | [
"Documentation"
] | DOC: clarify the documentation for the loss functions used in GBRT, and Absolute Error in particular.
### Describe the bug
From my understanding, currently there is no way to minimize the MAE (Mean Absolute Error). Quantile regression with quantile=0.5 will optimize for the Median Absolute Error. This would be diff... | 30,339 | [
0.009657524526119232,
0.01976901851594448,
0.019382908940315247,
-0.03308308124542236,
0.039128199219703674,
0.020444270223379135,
-0.024539494886994362,
0.06466154009103775,
-0.02437586337327957,
0.02551424503326416,
0.045189566910266876,
-0.017183378338813782,
0.0026089660823345184,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/30339 | [
"Documentation"
] | DOC: clarify the documentation for the loss functions used in GBRT, and Absolute Error in particular.
### Describe the bug
From my understanding, currently there is no way to minimize the MAE (Mean Absolute Error). Quantile regression with quantile=0.5 will optimize for the Median Absolute Error. This would be diff... | 30,339 | [
0.009657524526119232,
0.01976901851594448,
0.019382908940315247,
-0.03308308124542236,
0.039128199219703674,
0.020444270223379135,
-0.024539494886994362,
0.06466154009103775,
-0.02437586337327957,
0.02551424503326416,
0.045189566910266876,
-0.017183378338813782,
0.0026089660823345184,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/30339 | [
"Documentation"
] | DOC: clarify the documentation for the loss functions used in GBRT, and Absolute Error in particular.
### Describe the bug
From my understanding, currently there is no way to minimize the MAE (Mean Absolute Error). Quantile regression with quantile=0.5 will optimize for the Median Absolute Error. This would be diff... | 30,339 | [
0.009657524526119232,
0.01976901851594448,
0.019382908940315247,
-0.03308308124542236,
0.039128199219703674,
0.020444270223379135,
-0.024539494886994362,
0.06466154009103775,
-0.02437586337327957,
0.02551424503326416,
0.045189566910266876,
-0.017183378338813782,
0.0026089660823345184,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/30339 | [
"Documentation"
] | DOC: clarify the documentation for the loss functions used in GBRT, and Absolute Error in particular.
### Describe the bug
From my understanding, currently there is no way to minimize the MAE (Mean Absolute Error). Quantile regression with quantile=0.5 will optimize for the Median Absolute Error. This would be diff... | 30,339 | [
0.009657524526119232,
0.01976901851594448,
0.019382908940315247,
-0.03308308124542236,
0.039128199219703674,
0.020444270223379135,
-0.024539494886994362,
0.06466154009103775,
-0.02437586337327957,
0.02551424503326416,
0.045189566910266876,
-0.017183378338813782,
0.0026089660823345184,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/30339 | [
"Documentation"
] | DOC: clarify the documentation for the loss functions used in GBRT, and Absolute Error in particular.
### Describe the bug
From my understanding, currently there is no way to minimize the MAE (Mean Absolute Error). Quantile regression with quantile=0.5 will optimize for the Median Absolute Error. This would be diff... | 30,339 | [
0.009657524526119232,
0.01976901851594448,
0.019382908940315247,
-0.03308308124542236,
0.039128199219703674,
0.020444270223379135,
-0.024539494886994362,
0.06466154009103775,
-0.02437586337327957,
0.02551424503326416,
0.045189566910266876,
-0.017183378338813782,
0.0026089660823345184,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/30339 | [
"Documentation"
] | DOC: clarify the documentation for the loss functions used in GBRT, and Absolute Error in particular.
### Describe the bug
From my understanding, currently there is no way to minimize the MAE (Mean Absolute Error). Quantile regression with quantile=0.5 will optimize for the Median Absolute Error. This would be diff... | 30,339 | [
0.009657524526119232,
0.01976901851594448,
0.019382908940315247,
-0.03308308124542236,
0.039128199219703674,
0.020444270223379135,
-0.024539494886994362,
0.06466154009103775,
-0.02437586337327957,
0.02551424503326416,
0.045189566910266876,
-0.017183378338813782,
0.0026089660823345184,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/30339 | [
"Documentation"
] | DOC: clarify the documentation for the loss functions used in GBRT, and Absolute Error in particular.
### Describe the bug
From my understanding, currently there is no way to minimize the MAE (Mean Absolute Error). Quantile regression with quantile=0.5 will optimize for the Median Absolute Error. This would be diff... | 30,339 | [
0.009657524526119232,
0.01976901851594448,
0.019382908940315247,
-0.03308308124542236,
0.039128199219703674,
0.020444270223379135,
-0.024539494886994362,
0.06466154009103775,
-0.02437586337327957,
0.02551424503326416,
0.045189566910266876,
-0.017183378338813782,
0.0026089660823345184,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/30339 | [
"Documentation"
] | DOC: clarify the documentation for the loss functions used in GBRT, and Absolute Error in particular.
### Describe the bug
From my understanding, currently there is no way to minimize the MAE (Mean Absolute Error). Quantile regression with quantile=0.5 will optimize for the Median Absolute Error. This would be diff... | 30,339 | [
0.009657524526119232,
0.01976901851594448,
0.019382908940315247,
-0.03308308124542236,
0.039128199219703674,
0.020444270223379135,
-0.024539494886994362,
0.06466154009103775,
-0.02437586337327957,
0.02551424503326416,
0.045189566910266876,
-0.017183378338813782,
0.0026089660823345184,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/30339 | [
"Documentation"
] | DOC: clarify the documentation for the loss functions used in GBRT, and Absolute Error in particular.
### Describe the bug
From my understanding, currently there is no way to minimize the MAE (Mean Absolute Error). Quantile regression with quantile=0.5 will optimize for the Median Absolute Error. This would be diff... | 30,339 | [
0.009657524526119232,
0.01976901851594448,
0.019382908940315247,
-0.03308308124542236,
0.039128199219703674,
0.020444270223379135,
-0.024539494886994362,
0.06466154009103775,
-0.02437586337327957,
0.02551424503326416,
0.045189566910266876,
-0.017183378338813782,
0.0026089660823345184,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/30339 | [
"Documentation"
] | DOC: clarify the documentation for the loss functions used in GBRT, and Absolute Error in particular.
### Describe the bug
From my understanding, currently there is no way to minimize the MAE (Mean Absolute Error). Quantile regression with quantile=0.5 will optimize for the Median Absolute Error. This would be diff... | 30,339 | [
0.009657524526119232,
0.01976901851594448,
0.019382908940315247,
-0.03308308124542236,
0.039128199219703674,
0.020444270223379135,
-0.024539494886994362,
0.06466154009103775,
-0.02437586337327957,
0.02551424503326416,
0.045189566910266876,
-0.017183378338813782,
0.0026089660823345184,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/30339 | [
"Documentation"
] | DOC: clarify the documentation for the loss functions used in GBRT, and Absolute Error in particular.
### Describe the bug
From my understanding, currently there is no way to minimize the MAE (Mean Absolute Error). Quantile regression with quantile=0.5 will optimize for the Median Absolute Error. This would be diff... | 30,339 | [
0.009657524526119232,
0.01976901851594448,
0.019382908940315247,
-0.03308308124542236,
0.039128199219703674,
0.020444270223379135,
-0.024539494886994362,
0.06466154009103775,
-0.02437586337327957,
0.02551424503326416,
0.045189566910266876,
-0.017183378338813782,
0.0026089660823345184,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/30338 | [
"Bug",
"Needs Triage"
] | LabelBinarizer() throws TypeError: '<' not supported between instances of 'str' and 'float'
### Describe the bug
As I understand it, LabelBinarizer is meant to have a categorical string as an input. I input a y dependent variable as a categorical of dtype "category" with values "apple", "orange", or "pear":
```
y... | 30,338 | [
0.023576097562909126,
-0.013324405066668987,
0.03470075875520706,
-0.028126927092671394,
0.14466282725334167,
0.027828894555568695,
0.04818588122725487,
0.04055146500468254,
-0.04037975147366524,
-0.030042696744203568,
0.009535214863717556,
0.01657254993915558,
0.05350607633590698,
0.00849... |
https://github.com/scikit-learn/scikit-learn/issues/30338 | [
"Bug",
"Needs Triage"
] | LabelBinarizer() throws TypeError: '<' not supported between instances of 'str' and 'float'
### Describe the bug
As I understand it, LabelBinarizer is meant to have a categorical string as an input. I input a y dependent variable as a categorical of dtype "category" with values "apple", "orange", or "pear":
```
y... | 30,338 | [
0.023576097562909126,
-0.013324405066668987,
0.03470075875520706,
-0.028126927092671394,
0.14466282725334167,
0.027828894555568695,
0.04818588122725487,
0.04055146500468254,
-0.04037975147366524,
-0.030042696744203568,
0.009535214863717556,
0.01657254993915558,
0.05350607633590698,
0.00849... |
https://github.com/scikit-learn/scikit-learn/issues/30334 | [
"Bug",
"Needs Triage"
] | ValueError: Target is multiclass but average='binary'. Please choose another average setting, one of [None, 'micro', 'macro', 'weighted'].
### Describe the bug
I will be succinct. I am training a binary classification dataset on "rain" or "not rain". This is a binary target. Yet scikit-learn throws an error stating... | 30,334 | [
-0.01726698689162731,
-0.04040492698550224,
0.0323265865445137,
0.0015410855412483215,
0.07775625586509705,
0.005278570577502251,
0.042998552322387695,
-0.02377748116850853,
0.0026989218313246965,
-0.004189813509583473,
0.0347379632294178,
0.0175190232694149,
0.003911043517291546,
0.054149... |
https://github.com/scikit-learn/scikit-learn/issues/30334 | [
"Bug",
"Needs Triage"
] | ValueError: Target is multiclass but average='binary'. Please choose another average setting, one of [None, 'micro', 'macro', 'weighted'].
### Describe the bug
I will be succinct. I am training a binary classification dataset on "rain" or "not rain". This is a binary target. Yet scikit-learn throws an error stating... | 30,334 | [
-0.01726698689162731,
-0.04040492698550224,
0.0323265865445137,
0.0015410855412483215,
0.07775625586509705,
0.005278570577502251,
0.042998552322387695,
-0.02377748116850853,
0.0026989218313246965,
-0.004189813509583473,
0.0347379632294178,
0.0175190232694149,
0.003911043517291546,
0.054149... |
https://github.com/scikit-learn/scikit-learn/issues/30334 | [
"Bug",
"Needs Triage"
] | ValueError: Target is multiclass but average='binary'. Please choose another average setting, one of [None, 'micro', 'macro', 'weighted'].
### Describe the bug
I will be succinct. I am training a binary classification dataset on "rain" or "not rain". This is a binary target. Yet scikit-learn throws an error stating... | 30,334 | [
-0.01726698689162731,
-0.04040492698550224,
0.0323265865445137,
0.0015410855412483215,
0.07775625586509705,
0.005278570577502251,
0.042998552322387695,
-0.02377748116850853,
0.0026989218313246965,
-0.004189813509583473,
0.0347379632294178,
0.0175190232694149,
0.003911043517291546,
0.054149... |
https://github.com/scikit-learn/scikit-learn/issues/30334 | [
"Bug",
"Needs Triage"
] | ValueError: Target is multiclass but average='binary'. Please choose another average setting, one of [None, 'micro', 'macro', 'weighted'].
### Describe the bug
I will be succinct. I am training a binary classification dataset on "rain" or "not rain". This is a binary target. Yet scikit-learn throws an error stating... | 30,334 | [
-0.01726698689162731,
-0.04040492698550224,
0.0323265865445137,
0.0015410855412483215,
0.07775625586509705,
0.005278570577502251,
0.042998552322387695,
-0.02377748116850853,
0.0026989218313246965,
-0.004189813509583473,
0.0347379632294178,
0.0175190232694149,
0.003911043517291546,
0.054149... |
https://github.com/scikit-learn/scikit-learn/issues/30334 | [
"Bug",
"Needs Triage"
] | ValueError: Target is multiclass but average='binary'. Please choose another average setting, one of [None, 'micro', 'macro', 'weighted'].
### Describe the bug
I will be succinct. I am training a binary classification dataset on "rain" or "not rain". This is a binary target. Yet scikit-learn throws an error stating... | 30,334 | [
-0.01726698689162731,
-0.04040492698550224,
0.0323265865445137,
0.0015410855412483215,
0.07775625586509705,
0.005278570577502251,
0.042998552322387695,
-0.02377748116850853,
0.0026989218313246965,
-0.004189813509583473,
0.0347379632294178,
0.0175190232694149,
0.003911043517291546,
0.054149... |
https://github.com/scikit-learn/scikit-learn/issues/30332 | [
"Bug",
"Needs Investigation"
] | NuSVC argument `class_weight` is not used
### Describe the bug
Like `SVC`, the class `NuSVC` takes argument `class_weight`. However, it looks like this argument is not used. After a quick look at the libsvm C code within sklearn as well as [libsvm's original documentation](https://www.csie.ntu.edu.tw/~cjlin/libsvm/... | 30,332 | [
0.03401012346148491,
-0.03262713924050331,
0.025543035939335823,
0.02843816578388214,
0.08483066409826279,
-0.0036084242165088654,
0.005564945284277201,
-0.02486550807952881,
-0.017367638647556305,
0.019703024998307228,
0.048083312809467316,
0.04708476364612579,
0.04278675094246864,
-0.044... |
https://github.com/scikit-learn/scikit-learn/issues/30332 | [
"Bug",
"Needs Investigation"
] | NuSVC argument `class_weight` is not used
### Describe the bug
Like `SVC`, the class `NuSVC` takes argument `class_weight`. However, it looks like this argument is not used. After a quick look at the libsvm C code within sklearn as well as [libsvm's original documentation](https://www.csie.ntu.edu.tw/~cjlin/libsvm/... | 30,332 | [
0.03401012346148491,
-0.03262713924050331,
0.025543035939335823,
0.02843816578388214,
0.08483066409826279,
-0.0036084242165088654,
0.005564945284277201,
-0.02486550807952881,
-0.017367638647556305,
0.019703024998307228,
0.048083312809467316,
0.04708476364612579,
0.04278675094246864,
-0.044... |
https://github.com/scikit-learn/scikit-learn/issues/30332 | [
"Bug",
"Needs Investigation"
] | NuSVC argument `class_weight` is not used
### Describe the bug
Like `SVC`, the class `NuSVC` takes argument `class_weight`. However, it looks like this argument is not used. After a quick look at the libsvm C code within sklearn as well as [libsvm's original documentation](https://www.csie.ntu.edu.tw/~cjlin/libsvm/... | 30,332 | [
0.03401012346148491,
-0.03262713924050331,
0.025543035939335823,
0.02843816578388214,
0.08483066409826279,
-0.0036084242165088654,
0.005564945284277201,
-0.02486550807952881,
-0.017367638647556305,
0.019703024998307228,
0.048083312809467316,
0.04708476364612579,
0.04278675094246864,
-0.044... |
https://github.com/scikit-learn/scikit-learn/issues/30332 | [
"Bug",
"Needs Investigation"
] | NuSVC argument `class_weight` is not used
### Describe the bug
Like `SVC`, the class `NuSVC` takes argument `class_weight`. However, it looks like this argument is not used. After a quick look at the libsvm C code within sklearn as well as [libsvm's original documentation](https://www.csie.ntu.edu.tw/~cjlin/libsvm/... | 30,332 | [
0.03401012346148491,
-0.03262713924050331,
0.025543035939335823,
0.02843816578388214,
0.08483066409826279,
-0.0036084242165088654,
0.005564945284277201,
-0.02486550807952881,
-0.017367638647556305,
0.019703024998307228,
0.048083312809467316,
0.04708476364612579,
0.04278675094246864,
-0.044... |
https://github.com/scikit-learn/scikit-learn/issues/30332 | [
"Bug",
"Needs Investigation"
] | NuSVC argument `class_weight` is not used
### Describe the bug
Like `SVC`, the class `NuSVC` takes argument `class_weight`. However, it looks like this argument is not used. After a quick look at the libsvm C code within sklearn as well as [libsvm's original documentation](https://www.csie.ntu.edu.tw/~cjlin/libsvm/... | 30,332 | [
0.03401012346148491,
-0.03262713924050331,
0.025543035939335823,
0.02843816578388214,
0.08483066409826279,
-0.0036084242165088654,
0.005564945284277201,
-0.02486550807952881,
-0.017367638647556305,
0.019703024998307228,
0.048083312809467316,
0.04708476364612579,
0.04278675094246864,
-0.044... |
https://github.com/scikit-learn/scikit-learn/issues/30332 | [
"Bug",
"Needs Investigation"
] | NuSVC argument `class_weight` is not used
### Describe the bug
Like `SVC`, the class `NuSVC` takes argument `class_weight`. However, it looks like this argument is not used. After a quick look at the libsvm C code within sklearn as well as [libsvm's original documentation](https://www.csie.ntu.edu.tw/~cjlin/libsvm/... | 30,332 | [
0.03401012346148491,
-0.03262713924050331,
0.025543035939335823,
0.02843816578388214,
0.08483066409826279,
-0.0036084242165088654,
0.005564945284277201,
-0.02486550807952881,
-0.017367638647556305,
0.019703024998307228,
0.048083312809467316,
0.04708476364612579,
0.04278675094246864,
-0.044... |
https://github.com/scikit-learn/scikit-learn/issues/30332 | [
"Bug",
"Needs Investigation"
] | NuSVC argument `class_weight` is not used
### Describe the bug
Like `SVC`, the class `NuSVC` takes argument `class_weight`. However, it looks like this argument is not used. After a quick look at the libsvm C code within sklearn as well as [libsvm's original documentation](https://www.csie.ntu.edu.tw/~cjlin/libsvm/... | 30,332 | [
0.03401012346148491,
-0.03262713924050331,
0.025543035939335823,
0.02843816578388214,
0.08483066409826279,
-0.0036084242165088654,
0.005564945284277201,
-0.02486550807952881,
-0.017367638647556305,
0.019703024998307228,
0.048083312809467316,
0.04708476364612579,
0.04278675094246864,
-0.044... |
https://github.com/scikit-learn/scikit-learn/issues/30332 | [
"Bug",
"Needs Investigation"
] | NuSVC argument `class_weight` is not used
### Describe the bug
Like `SVC`, the class `NuSVC` takes argument `class_weight`. However, it looks like this argument is not used. After a quick look at the libsvm C code within sklearn as well as [libsvm's original documentation](https://www.csie.ntu.edu.tw/~cjlin/libsvm/... | 30,332 | [
0.03401012346148491,
-0.03262713924050331,
0.025543035939335823,
0.02843816578388214,
0.08483066409826279,
-0.0036084242165088654,
0.005564945284277201,
-0.02486550807952881,
-0.017367638647556305,
0.019703024998307228,
0.048083312809467316,
0.04708476364612579,
0.04278675094246864,
-0.044... |
https://github.com/scikit-learn/scikit-learn/issues/30332 | [
"Bug",
"Needs Investigation"
] | NuSVC argument `class_weight` is not used
### Describe the bug
Like `SVC`, the class `NuSVC` takes argument `class_weight`. However, it looks like this argument is not used. After a quick look at the libsvm C code within sklearn as well as [libsvm's original documentation](https://www.csie.ntu.edu.tw/~cjlin/libsvm/... | 30,332 | [
0.03401012346148491,
-0.03262713924050331,
0.025543035939335823,
0.02843816578388214,
0.08483066409826279,
-0.0036084242165088654,
0.005564945284277201,
-0.02486550807952881,
-0.017367638647556305,
0.019703024998307228,
0.048083312809467316,
0.04708476364612579,
0.04278675094246864,
-0.044... |
https://github.com/scikit-learn/scikit-learn/issues/30332 | [
"Bug",
"Needs Investigation"
] | NuSVC argument `class_weight` is not used
### Describe the bug
Like `SVC`, the class `NuSVC` takes argument `class_weight`. However, it looks like this argument is not used. After a quick look at the libsvm C code within sklearn as well as [libsvm's original documentation](https://www.csie.ntu.edu.tw/~cjlin/libsvm/... | 30,332 | [
0.03401012346148491,
-0.03262713924050331,
0.025543035939335823,
0.02843816578388214,
0.08483066409826279,
-0.0036084242165088654,
0.005564945284277201,
-0.02486550807952881,
-0.017367638647556305,
0.019703024998307228,
0.048083312809467316,
0.04708476364612579,
0.04278675094246864,
-0.044... |
https://github.com/scikit-learn/scikit-learn/issues/30332 | [
"Bug",
"Needs Investigation"
] | NuSVC argument `class_weight` is not used
### Describe the bug
Like `SVC`, the class `NuSVC` takes argument `class_weight`. However, it looks like this argument is not used. After a quick look at the libsvm C code within sklearn as well as [libsvm's original documentation](https://www.csie.ntu.edu.tw/~cjlin/libsvm/... | 30,332 | [
0.03401012346148491,
-0.03262713924050331,
0.025543035939335823,
0.02843816578388214,
0.08483066409826279,
-0.0036084242165088654,
0.005564945284277201,
-0.02486550807952881,
-0.017367638647556305,
0.019703024998307228,
0.048083312809467316,
0.04708476364612579,
0.04278675094246864,
-0.044... |
https://github.com/scikit-learn/scikit-learn/issues/30332 | [
"Bug",
"Needs Investigation"
] | NuSVC argument `class_weight` is not used
### Describe the bug
Like `SVC`, the class `NuSVC` takes argument `class_weight`. However, it looks like this argument is not used. After a quick look at the libsvm C code within sklearn as well as [libsvm's original documentation](https://www.csie.ntu.edu.tw/~cjlin/libsvm/... | 30,332 | [
0.03401012346148491,
-0.03262713924050331,
0.025543035939335823,
0.02843816578388214,
0.08483066409826279,
-0.0036084242165088654,
0.005564945284277201,
-0.02486550807952881,
-0.017367638647556305,
0.019703024998307228,
0.048083312809467316,
0.04708476364612579,
0.04278675094246864,
-0.044... |
https://github.com/scikit-learn/scikit-learn/issues/30332 | [
"Bug",
"Needs Investigation"
] | NuSVC argument `class_weight` is not used
### Describe the bug
Like `SVC`, the class `NuSVC` takes argument `class_weight`. However, it looks like this argument is not used. After a quick look at the libsvm C code within sklearn as well as [libsvm's original documentation](https://www.csie.ntu.edu.tw/~cjlin/libsvm/... | 30,332 | [
0.03401012346148491,
-0.03262713924050331,
0.025543035939335823,
0.02843816578388214,
0.08483066409826279,
-0.0036084242165088654,
0.005564945284277201,
-0.02486550807952881,
-0.017367638647556305,
0.019703024998307228,
0.048083312809467316,
0.04708476364612579,
0.04278675094246864,
-0.044... |
https://github.com/scikit-learn/scikit-learn/issues/30332 | [
"Bug",
"Needs Investigation"
] | NuSVC argument `class_weight` is not used
### Describe the bug
Like `SVC`, the class `NuSVC` takes argument `class_weight`. However, it looks like this argument is not used. After a quick look at the libsvm C code within sklearn as well as [libsvm's original documentation](https://www.csie.ntu.edu.tw/~cjlin/libsvm/... | 30,332 | [
0.03401012346148491,
-0.03262713924050331,
0.025543035939335823,
0.02843816578388214,
0.08483066409826279,
-0.0036084242165088654,
0.005564945284277201,
-0.02486550807952881,
-0.017367638647556305,
0.019703024998307228,
0.048083312809467316,
0.04708476364612579,
0.04278675094246864,
-0.044... |
https://github.com/scikit-learn/scikit-learn/issues/30332 | [
"Bug",
"Needs Investigation"
] | NuSVC argument `class_weight` is not used
### Describe the bug
Like `SVC`, the class `NuSVC` takes argument `class_weight`. However, it looks like this argument is not used. After a quick look at the libsvm C code within sklearn as well as [libsvm's original documentation](https://www.csie.ntu.edu.tw/~cjlin/libsvm/... | 30,332 | [
0.03401012346148491,
-0.03262713924050331,
0.025543035939335823,
0.02843816578388214,
0.08483066409826279,
-0.0036084242165088654,
0.005564945284277201,
-0.02486550807952881,
-0.017367638647556305,
0.019703024998307228,
0.048083312809467316,
0.04708476364612579,
0.04278675094246864,
-0.044... |
https://github.com/scikit-learn/scikit-learn/issues/30325 | [
"Enhancement"
] | Classification report, digits variable
### Describe the workflow you want to enable
Hi, as of right now the digits variable which limits how many numbers are shown after the decimal point does not apply to the support column for the classification report. Support normally does not have decimals, but that happens when... | 30,325 | [
-0.02009100280702114,
0.008109115064144135,
0.025724010542035103,
-0.022074498236179352,
0.09095247834920883,
-0.004359094426035881,
0.04912858456373215,
-0.000395565148210153,
-0.05973473936319351,
-0.008846140466630459,
0.016207823529839516,
0.01801069639623165,
0.0026128923054784536,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/30325 | [
"Enhancement"
] | Classification report, digits variable
### Describe the workflow you want to enable
Hi, as of right now the digits variable which limits how many numbers are shown after the decimal point does not apply to the support column for the classification report. Support normally does not have decimals, but that happens when... | 30,325 | [
-0.0451798178255558,
0.003926335833966732,
-0.0077438559383153915,
-0.055108364671468735,
0.05089963972568512,
0.002979831537231803,
0.02417478896677494,
0.0013507219264283776,
-0.03172877058386803,
-0.0005307973478920758,
0.0347016267478466,
0.016463199630379677,
-0.0025556080508977175,
0... |
https://github.com/scikit-learn/scikit-learn/issues/30325 | [
"Enhancement"
] | Classification report, digits variable
### Describe the workflow you want to enable
Hi, as of right now the digits variable which limits how many numbers are shown after the decimal point does not apply to the support column for the classification report. Support normally does not have decimals, but that happens when... | 30,325 | [
-0.04675693437457085,
0.025418465957045555,
-0.0006319601670838892,
-0.041071951389312744,
0.045015592128038406,
0.002216957276687026,
0.04010741412639618,
0.008895193226635456,
-0.03239064663648605,
-0.0014273404376581311,
0.03922340273857117,
0.025035202503204346,
-0.01045256108045578,
0... |
https://github.com/scikit-learn/scikit-learn/issues/30325 | [
"Enhancement"
] | Classification report, digits variable
### Describe the workflow you want to enable
Hi, as of right now the digits variable which limits how many numbers are shown after the decimal point does not apply to the support column for the classification report. Support normally does not have decimals, but that happens when... | 30,325 | [
-0.05201929435133934,
0.018573230132460594,
-0.020222537219524384,
-0.043376557528972626,
0.028526904061436653,
-0.01823313534259796,
0.01145500410348177,
0.007412117440253496,
-0.07942669093608856,
0.00761062977835536,
0.05484706163406372,
0.00004750131847686134,
0.005430625285953283,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/30324 | [
"Bug"
] | Regression in SelectorMixin in 1.6.0rc1
### Describe the bug
Using the estimator tag `allow_nan` doesn't work with `SelectorMixin` in the release candidate.
A first skim suggests maybe `ensure_all_finite` is inconsistently expected to be `False` and other times `"allow-nan"`? In particular at https://github.com... | 30,324 | [
-0.00025552973966114223,
0.03508547693490982,
0.02587558515369892,
-0.026600107550621033,
0.06457073241472244,
-0.05223020911216736,
0.08261227607727051,
0.039126284420490265,
0.03552759066224098,
-0.013692790642380714,
0.04525906965136528,
0.04325848072767258,
-0.010565669275820255,
0.014... |
https://github.com/scikit-learn/scikit-learn/issues/30324 | [
"Bug"
] | Regression in SelectorMixin in 1.6.0rc1
### Describe the bug
Using the estimator tag `allow_nan` doesn't work with `SelectorMixin` in the release candidate.
A first skim suggests maybe `ensure_all_finite` is inconsistently expected to be `False` and other times `"allow-nan"`? In particular at https://github.com... | 30,324 | [
-0.00025552973966114223,
0.03508547693490982,
0.02587558515369892,
-0.026600107550621033,
0.06457073241472244,
-0.05223020911216736,
0.08261227607727051,
0.039126284420490265,
0.03552759066224098,
-0.013692790642380714,
0.04525906965136528,
0.04325848072767258,
-0.010565669275820255,
0.014... |
https://github.com/scikit-learn/scikit-learn/issues/30323 | [
"Documentation"
] | DOC Example on model selection for Gaussian Mixture Models
### Describe the issue linked to the documentation
We have an example that illustrates how to use the BIC score to tune the number of components and the type of covariance matrix parametrization here:
https://scikit-learn.org/stable/auto_examples/mixture... | 30,323 | [
0.012006654404103756,
0.004258283413946629,
0.04862373694777489,
-0.025436880066990852,
0.05940869078040123,
0.017742926254868507,
0.03850084915757179,
-0.008149242028594017,
0.03397297486662865,
0.006041588727384806,
0.02425680309534073,
0.020471639931201935,
0.04763225466012955,
0.011570... |
https://github.com/scikit-learn/scikit-learn/issues/30323 | [
"Documentation"
] | DOC Example on model selection for Gaussian Mixture Models
### Describe the issue linked to the documentation
We have an example that illustrates how to use the BIC score to tune the number of components and the type of covariance matrix parametrization here:
https://scikit-learn.org/stable/auto_examples/mixture... | 30,323 | [
0.012006654404103756,
0.004258283413946629,
0.04862373694777489,
-0.025436880066990852,
0.05940869078040123,
0.017742926254868507,
0.03850084915757179,
-0.008149242028594017,
0.03397297486662865,
0.006041588727384806,
0.02425680309534073,
0.020471639931201935,
0.04763225466012955,
0.011570... |
https://github.com/scikit-learn/scikit-learn/issues/30323 | [
"Documentation"
] | DOC Example on model selection for Gaussian Mixture Models
### Describe the issue linked to the documentation
We have an example that illustrates how to use the BIC score to tune the number of components and the type of covariance matrix parametrization here:
https://scikit-learn.org/stable/auto_examples/mixture... | 30,323 | [
0.012006654404103756,
0.004258283413946629,
0.04862373694777489,
-0.025436880066990852,
0.05940869078040123,
0.017742926254868507,
0.03850084915757179,
-0.008149242028594017,
0.03397297486662865,
0.006041588727384806,
0.02425680309534073,
0.020471639931201935,
0.04763225466012955,
0.011570... |
https://github.com/scikit-learn/scikit-learn/issues/30323 | [
"Documentation"
] | DOC Example on model selection for Gaussian Mixture Models
### Describe the issue linked to the documentation
We have an example that illustrates how to use the BIC score to tune the number of components and the type of covariance matrix parametrization here:
https://scikit-learn.org/stable/auto_examples/mixture... | 30,323 | [
0.012006654404103756,
0.004258283413946629,
0.04862373694777489,
-0.025436880066990852,
0.05940869078040123,
0.017742926254868507,
0.03850084915757179,
-0.008149242028594017,
0.03397297486662865,
0.006041588727384806,
0.02425680309534073,
0.020471639931201935,
0.04763225466012955,
0.011570... |
https://github.com/scikit-learn/scikit-learn/issues/30323 | [
"Documentation"
] | DOC Example on model selection for Gaussian Mixture Models
### Describe the issue linked to the documentation
We have an example that illustrates how to use the BIC score to tune the number of components and the type of covariance matrix parametrization here:
https://scikit-learn.org/stable/auto_examples/mixture... | 30,323 | [
0.012006654404103756,
0.004258283413946629,
0.04862373694777489,
-0.025436880066990852,
0.05940869078040123,
0.017742926254868507,
0.03850084915757179,
-0.008149242028594017,
0.03397297486662865,
0.006041588727384806,
0.02425680309534073,
0.020471639931201935,
0.04763225466012955,
0.011570... |
https://github.com/scikit-learn/scikit-learn/issues/30323 | [
"Documentation"
] | DOC Example on model selection for Gaussian Mixture Models
### Describe the issue linked to the documentation
We have an example that illustrates how to use the BIC score to tune the number of components and the type of covariance matrix parametrization here:
https://scikit-learn.org/stable/auto_examples/mixture... | 30,323 | [
0.012006654404103756,
0.004258283413946629,
0.04862373694777489,
-0.025436880066990852,
0.05940869078040123,
0.017742926254868507,
0.03850084915757179,
-0.008149242028594017,
0.03397297486662865,
0.006041588727384806,
0.02425680309534073,
0.020471639931201935,
0.04763225466012955,
0.011570... |
https://github.com/scikit-learn/scikit-learn/issues/30323 | [
"Documentation"
] | DOC Example on model selection for Gaussian Mixture Models
### Describe the issue linked to the documentation
We have an example that illustrates how to use the BIC score to tune the number of components and the type of covariance matrix parametrization here:
https://scikit-learn.org/stable/auto_examples/mixture... | 30,323 | [
0.012006654404103756,
0.004258283413946629,
0.04862373694777489,
-0.025436880066990852,
0.05940869078040123,
0.017742926254868507,
0.03850084915757179,
-0.008149242028594017,
0.03397297486662865,
0.006041588727384806,
0.02425680309534073,
0.020471639931201935,
0.04763225466012955,
0.011570... |
https://github.com/scikit-learn/scikit-learn/issues/30323 | [
"Documentation"
] | DOC Example on model selection for Gaussian Mixture Models
### Describe the issue linked to the documentation
We have an example that illustrates how to use the BIC score to tune the number of components and the type of covariance matrix parametrization here:
https://scikit-learn.org/stable/auto_examples/mixture... | 30,323 | [
0.012006654404103756,
0.004258283413946629,
0.04862373694777489,
-0.025436880066990852,
0.05940869078040123,
0.017742926254868507,
0.03850084915757179,
-0.008149242028594017,
0.03397297486662865,
0.006041588727384806,
0.02425680309534073,
0.020471639931201935,
0.04763225466012955,
0.011570... |
https://github.com/scikit-learn/scikit-learn/issues/30323 | [
"Documentation"
] | DOC Example on model selection for Gaussian Mixture Models
### Describe the issue linked to the documentation
We have an example that illustrates how to use the BIC score to tune the number of components and the type of covariance matrix parametrization here:
https://scikit-learn.org/stable/auto_examples/mixture... | 30,323 | [
0.012006654404103756,
0.004258283413946629,
0.04862373694777489,
-0.025436880066990852,
0.05940869078040123,
0.017742926254868507,
0.03850084915757179,
-0.008149242028594017,
0.03397297486662865,
0.006041588727384806,
0.02425680309534073,
0.020471639931201935,
0.04763225466012955,
0.011570... |
https://github.com/scikit-learn/scikit-learn/issues/30321 | [
"Bug",
"Needs Triage"
] | Error in impute/_base.py _most_frequent when array contains None
### Describe the bug
TypeError: '<' not supported between instances of 'NoneType' and 'str'
when calculating min in impute/_base.py
most_frequent_value = min(
value
for value, count in counter.items()
... | 30,321 | [
0.05395742878317833,
-0.05910959839820862,
-0.005856923758983612,
-0.031677134335041046,
0.06237725913524628,
-0.00018997119332198054,
0.04398871958255768,
0.001903707510791719,
0.015249431133270264,
-0.023804977536201477,
0.01425829529762268,
0.016844410449266434,
0.0015981853939592838,
0... |
https://github.com/scikit-learn/scikit-learn/issues/30321 | [
"Bug",
"Needs Triage"
] | Error in impute/_base.py _most_frequent when array contains None
### Describe the bug
TypeError: '<' not supported between instances of 'NoneType' and 'str'
when calculating min in impute/_base.py
most_frequent_value = min(
value
for value, count in counter.items()
... | 30,321 | [
0.05395742878317833,
-0.05910959839820862,
-0.005856923758983612,
-0.031677134335041046,
0.06237725913524628,
-0.00018997119332198054,
0.04398871958255768,
0.001903707510791719,
0.015249431133270264,
-0.023804977536201477,
0.01425829529762268,
0.016844410449266434,
0.0015981853939592838,
0... |
https://github.com/scikit-learn/scikit-learn/issues/30315 | [
"Bug"
] | ⚠️ CI failed on Linux_Nightly.pylatest_pip_scipy_dev (last failure: Dec 05, 2024) ⚠️
**CI is still failing on [Linux_Nightly.pylatest_pip_scipy_dev](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=72598&view=logs&j=dfe99b15-50db-5d7b-b1e9-4105c42527cf)** (Dec 05, 2024)
- test_partial_dependence_... | 30,315 | [
-0.01027614064514637,
0.0366501547396183,
0.004565318115055561,
-0.051477789878845215,
0.08165831863880157,
0.03308429569005966,
0.048459939658641815,
0.0614619255065918,
0.018142832443118095,
-0.017193827778100967,
0.03938795253634453,
0.01925761066377163,
-0.009717787615954876,
0.0940233... |
https://github.com/scikit-learn/scikit-learn/issues/30315 | [
"Bug"
] | ⚠️ CI failed on Linux_Nightly.pylatest_pip_scipy_dev (last failure: Dec 05, 2024) ⚠️
**CI is still failing on [Linux_Nightly.pylatest_pip_scipy_dev](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=72598&view=logs&j=dfe99b15-50db-5d7b-b1e9-4105c42527cf)** (Dec 05, 2024)
- test_partial_dependence_... | 30,315 | [
-0.02400059439241886,
0.031230689957737923,
-0.014287601225078106,
-0.053452521562576294,
0.03924258425831795,
0.010861675255000591,
0.04209151491522789,
0.04791209474205971,
0.021647531539201736,
0.027913173660635948,
0.0699150487780571,
0.004868050571531057,
-0.010616353712975979,
0.1055... |
https://github.com/scikit-learn/scikit-learn/issues/30315 | [
"Bug"
] | ⚠️ CI failed on Linux_Nightly.pylatest_pip_scipy_dev (last failure: Dec 05, 2024) ⚠️
**CI is still failing on [Linux_Nightly.pylatest_pip_scipy_dev](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=72598&view=logs&j=dfe99b15-50db-5d7b-b1e9-4105c42527cf)** (Dec 05, 2024)
- test_partial_dependence_... | 30,315 | [
-0.008962936699390411,
0.024662215262651443,
-0.006337881553918123,
-0.05237686634063721,
0.041209641844034195,
0.005650307517498732,
0.03165746480226517,
0.0422670915722847,
0.028110681101679802,
0.027243074029684067,
0.09553135931491852,
0.005476254969835281,
-0.004935943055897951,
0.092... |
https://github.com/scikit-learn/scikit-learn/issues/30315 | [
"Bug"
] | ⚠️ CI failed on Linux_Nightly.pylatest_pip_scipy_dev (last failure: Dec 05, 2024) ⚠️
**CI is still failing on [Linux_Nightly.pylatest_pip_scipy_dev](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=72598&view=logs&j=dfe99b15-50db-5d7b-b1e9-4105c42527cf)** (Dec 05, 2024)
- test_partial_dependence_... | 30,315 | [
-0.027186617255210876,
0.021472254768013954,
-0.0213072020560503,
-0.011524247005581856,
0.04025693237781525,
0.042208150029182434,
0.014051440171897411,
0.04580408334732056,
0.01949584297835827,
0.014465713873505592,
0.08894775062799454,
0.029929080978035927,
-0.010396644473075867,
0.0676... |
https://github.com/scikit-learn/scikit-learn/issues/30315 | [
"Bug"
] | ⚠️ CI failed on Linux_Nightly.pylatest_pip_scipy_dev (last failure: Dec 05, 2024) ⚠️
**CI is still failing on [Linux_Nightly.pylatest_pip_scipy_dev](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=72598&view=logs&j=dfe99b15-50db-5d7b-b1e9-4105c42527cf)** (Dec 05, 2024)
- test_partial_dependence_... | 30,315 | [
-0.0288814939558506,
0.028407050296664238,
-0.006481308955699205,
-0.040883082896471024,
0.03600278124213219,
0.003249362576752901,
0.047089844942092896,
0.04926885664463043,
0.039812054485082626,
0.02042250707745552,
0.06464698165655136,
-0.00407060980796814,
-0.006965878419578075,
0.0756... |
https://github.com/scikit-learn/scikit-learn/issues/30315 | [
"Bug"
] | ⚠️ CI failed on Linux_Nightly.pylatest_pip_scipy_dev (last failure: Dec 05, 2024) ⚠️
**CI is still failing on [Linux_Nightly.pylatest_pip_scipy_dev](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=72598&view=logs&j=dfe99b15-50db-5d7b-b1e9-4105c42527cf)** (Dec 05, 2024)
- test_partial_dependence_... | 30,315 | [
-0.028986215591430664,
0.024472853168845177,
-0.0035345980431884527,
-0.034674257040023804,
0.05051710084080696,
-0.003839016193524003,
0.03330152854323387,
0.03986632078886032,
0.0198940671980381,
0.0029297336004674435,
0.06089423969388008,
0.020078402012586594,
-0.014974058605730534,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/30315 | [
"Bug"
] | ⚠️ CI failed on Linux_Nightly.pylatest_pip_scipy_dev (last failure: Dec 05, 2024) ⚠️
**CI is still failing on [Linux_Nightly.pylatest_pip_scipy_dev](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=72598&view=logs&j=dfe99b15-50db-5d7b-b1e9-4105c42527cf)** (Dec 05, 2024)
- test_partial_dependence_... | 30,315 | [
-0.02785077504813671,
0.02548842877149582,
-0.013051891699433327,
-0.04513460025191307,
0.03919602185487747,
0.010641510598361492,
0.03894120827317238,
0.05617383494973183,
0.03187593072652817,
0.01883106119930744,
0.05297297611832619,
0.013123386539518833,
-0.005384216085076332,
0.0731362... |
https://github.com/scikit-learn/scikit-learn/issues/30315 | [
"Bug"
] | ⚠️ CI failed on Linux_Nightly.pylatest_pip_scipy_dev (last failure: Dec 05, 2024) ⚠️
**CI is still failing on [Linux_Nightly.pylatest_pip_scipy_dev](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=72598&view=logs&j=dfe99b15-50db-5d7b-b1e9-4105c42527cf)** (Dec 05, 2024)
- test_partial_dependence_... | 30,315 | [
-0.024827726185321808,
0.023030661046504974,
-0.010514568537473679,
-0.047887641936540604,
0.03995681554079056,
0.006470941007137299,
0.04419373348355293,
0.05443321168422699,
0.03152128681540489,
0.02041628584265709,
0.055248238146305084,
0.010794221423566341,
-0.00914302933961153,
0.0849... |
https://github.com/scikit-learn/scikit-learn/issues/30310 | [
"Bug",
"Enhancement"
] | Error with set_output(transform='pandas') in ColumnTransformer when using OneHotEncoder with sparse output in intermediate steps
### Describe the bug
**Explanation**
Using the ColumnTransformer with set_output(transform='pandas') raises an error when there is a sparse intermediate output, even if the final outpu... | 30,310 | [
0.0015908057102933526,
0.014737265184521675,
0.05371950939297676,
-0.05371849238872528,
0.09674056619405746,
0.023494651541113853,
0.0702114999294281,
0.08227953314781189,
-0.053447164595127106,
0.014288903214037418,
0.04874768108129501,
-0.019077245146036148,
0.05744233354926109,
0.046590... |
https://github.com/scikit-learn/scikit-learn/issues/30310 | [
"Bug",
"Enhancement"
] | Error with set_output(transform='pandas') in ColumnTransformer when using OneHotEncoder with sparse output in intermediate steps
### Describe the bug
**Explanation**
Using the ColumnTransformer with set_output(transform='pandas') raises an error when there is a sparse intermediate output, even if the final outpu... | 30,310 | [
0.0015908057102933526,
0.014737265184521675,
0.05371950939297676,
-0.05371849238872528,
0.09674056619405746,
0.023494651541113853,
0.0702114999294281,
0.08227953314781189,
-0.053447164595127106,
0.014288903214037418,
0.04874768108129501,
-0.019077245146036148,
0.05744233354926109,
0.046590... |
https://github.com/scikit-learn/scikit-learn/issues/30310 | [
"Bug",
"Enhancement"
] | Error with set_output(transform='pandas') in ColumnTransformer when using OneHotEncoder with sparse output in intermediate steps
### Describe the bug
**Explanation**
Using the ColumnTransformer with set_output(transform='pandas') raises an error when there is a sparse intermediate output, even if the final outpu... | 30,310 | [
0.0015908057102933526,
0.014737265184521675,
0.05371950939297676,
-0.05371849238872528,
0.09674056619405746,
0.023494651541113853,
0.0702114999294281,
0.08227953314781189,
-0.053447164595127106,
0.014288903214037418,
0.04874768108129501,
-0.019077245146036148,
0.05744233354926109,
0.046590... |
https://github.com/scikit-learn/scikit-learn/issues/30309 | [
"Documentation",
"Moderate"
] | 'Section Navigation' bar missing from stable documentation website on several pages
### Describe the issue linked to the documentation
When on the stable version of the documentation website the 'Section Navigation' header on the left side of the page remains present, but the navigation bar contents disappear. Whil... | 30,309 | [
0.04913625866174698,
0.0008400139631703496,
-0.02777981199324131,
-0.04021713137626648,
0.035451650619506836,
0.004113757982850075,
0.029293594881892204,
0.073246069252491,
-0.006697410251945257,
-0.009585218504071236,
-0.013894067145884037,
-0.015519610606133938,
0.04824512079358101,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/30309 | [
"Documentation",
"Moderate"
] | 'Section Navigation' bar missing from stable documentation website on several pages
### Describe the issue linked to the documentation
When on the stable version of the documentation website the 'Section Navigation' header on the left side of the page remains present, but the navigation bar contents disappear. Whil... | 30,309 | [
0.04913625866174698,
0.0008400139631703496,
-0.02777981199324131,
-0.04021713137626648,
0.035451650619506836,
0.004113757982850075,
0.029293594881892204,
0.073246069252491,
-0.006697410251945257,
-0.009585218504071236,
-0.013894067145884037,
-0.015519610606133938,
0.04824512079358101,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/30309 | [
"Documentation",
"Moderate"
] | 'Section Navigation' bar missing from stable documentation website on several pages
### Describe the issue linked to the documentation
When on the stable version of the documentation website the 'Section Navigation' header on the left side of the page remains present, but the navigation bar contents disappear. Whil... | 30,309 | [
0.04913625866174698,
0.0008400139631703496,
-0.02777981199324131,
-0.04021713137626648,
0.035451650619506836,
0.004113757982850075,
0.029293594881892204,
0.073246069252491,
-0.006697410251945257,
-0.009585218504071236,
-0.013894067145884037,
-0.015519610606133938,
0.04824512079358101,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/30309 | [
"Documentation",
"Moderate"
] | 'Section Navigation' bar missing from stable documentation website on several pages
### Describe the issue linked to the documentation
When on the stable version of the documentation website the 'Section Navigation' header on the left side of the page remains present, but the navigation bar contents disappear. Whil... | 30,309 | [
0.04913625866174698,
0.0008400139631703496,
-0.02777981199324131,
-0.04021713137626648,
0.035451650619506836,
0.004113757982850075,
0.029293594881892204,
0.073246069252491,
-0.006697410251945257,
-0.009585218504071236,
-0.013894067145884037,
-0.015519610606133938,
0.04824512079358101,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/30309 | [
"Documentation",
"Moderate"
] | 'Section Navigation' bar missing from stable documentation website on several pages
### Describe the issue linked to the documentation
When on the stable version of the documentation website the 'Section Navigation' header on the left side of the page remains present, but the navigation bar contents disappear. Whil... | 30,309 | [
0.04913625866174698,
0.0008400139631703496,
-0.02777981199324131,
-0.04021713137626648,
0.035451650619506836,
0.004113757982850075,
0.029293594881892204,
0.073246069252491,
-0.006697410251945257,
-0.009585218504071236,
-0.013894067145884037,
-0.015519610606133938,
0.04824512079358101,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/30309 | [
"Documentation",
"Moderate"
] | 'Section Navigation' bar missing from stable documentation website on several pages
### Describe the issue linked to the documentation
When on the stable version of the documentation website the 'Section Navigation' header on the left side of the page remains present, but the navigation bar contents disappear. Whil... | 30,309 | [
0.04913625866174698,
0.0008400139631703496,
-0.02777981199324131,
-0.04021713137626648,
0.035451650619506836,
0.004113757982850075,
0.029293594881892204,
0.073246069252491,
-0.006697410251945257,
-0.009585218504071236,
-0.013894067145884037,
-0.015519610606133938,
0.04824512079358101,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/30309 | [
"Documentation",
"Moderate"
] | 'Section Navigation' bar missing from stable documentation website on several pages
### Describe the issue linked to the documentation
When on the stable version of the documentation website the 'Section Navigation' header on the left side of the page remains present, but the navigation bar contents disappear. Whil... | 30,309 | [
0.04913625866174698,
0.0008400139631703496,
-0.02777981199324131,
-0.04021713137626648,
0.035451650619506836,
0.004113757982850075,
0.029293594881892204,
0.073246069252491,
-0.006697410251945257,
-0.009585218504071236,
-0.013894067145884037,
-0.015519610606133938,
0.04824512079358101,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/30309 | [
"Documentation",
"Moderate"
] | 'Section Navigation' bar missing from stable documentation website on several pages
### Describe the issue linked to the documentation
When on the stable version of the documentation website the 'Section Navigation' header on the left side of the page remains present, but the navigation bar contents disappear. Whil... | 30,309 | [
0.04913625866174698,
0.0008400139631703496,
-0.02777981199324131,
-0.04021713137626648,
0.035451650619506836,
0.004113757982850075,
0.029293594881892204,
0.073246069252491,
-0.006697410251945257,
-0.009585218504071236,
-0.013894067145884037,
-0.015519610606133938,
0.04824512079358101,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/30309 | [
"Documentation",
"Moderate"
] | 'Section Navigation' bar missing from stable documentation website on several pages
### Describe the issue linked to the documentation
When on the stable version of the documentation website the 'Section Navigation' header on the left side of the page remains present, but the navigation bar contents disappear. Whil... | 30,309 | [
0.04913625866174698,
0.0008400139631703496,
-0.02777981199324131,
-0.04021713137626648,
0.035451650619506836,
0.004113757982850075,
0.029293594881892204,
0.073246069252491,
-0.006697410251945257,
-0.009585218504071236,
-0.013894067145884037,
-0.015519610606133938,
0.04824512079358101,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/30309 | [
"Documentation",
"Moderate"
] | 'Section Navigation' bar missing from stable documentation website on several pages
### Describe the issue linked to the documentation
When on the stable version of the documentation website the 'Section Navigation' header on the left side of the page remains present, but the navigation bar contents disappear. Whil... | 30,309 | [
0.04913625866174698,
0.0008400139631703496,
-0.02777981199324131,
-0.04021713137626648,
0.035451650619506836,
0.004113757982850075,
0.029293594881892204,
0.073246069252491,
-0.006697410251945257,
-0.009585218504071236,
-0.013894067145884037,
-0.015519610606133938,
0.04824512079358101,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/30309 | [
"Documentation",
"Moderate"
] | 'Section Navigation' bar missing from stable documentation website on several pages
### Describe the issue linked to the documentation
When on the stable version of the documentation website the 'Section Navigation' header on the left side of the page remains present, but the navigation bar contents disappear. Whil... | 30,309 | [
0.04913625866174698,
0.0008400139631703496,
-0.02777981199324131,
-0.04021713137626648,
0.035451650619506836,
0.004113757982850075,
0.029293594881892204,
0.073246069252491,
-0.006697410251945257,
-0.009585218504071236,
-0.013894067145884037,
-0.015519610606133938,
0.04824512079358101,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/30309 | [
"Documentation",
"Moderate"
] | 'Section Navigation' bar missing from stable documentation website on several pages
### Describe the issue linked to the documentation
When on the stable version of the documentation website the 'Section Navigation' header on the left side of the page remains present, but the navigation bar contents disappear. Whil... | 30,309 | [
0.04913625866174698,
0.0008400139631703496,
-0.02777981199324131,
-0.04021713137626648,
0.035451650619506836,
0.004113757982850075,
0.029293594881892204,
0.073246069252491,
-0.006697410251945257,
-0.009585218504071236,
-0.013894067145884037,
-0.015519610606133938,
0.04824512079358101,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/30309 | [
"Documentation",
"Moderate"
] | 'Section Navigation' bar missing from stable documentation website on several pages
### Describe the issue linked to the documentation
When on the stable version of the documentation website the 'Section Navigation' header on the left side of the page remains present, but the navigation bar contents disappear. Whil... | 30,309 | [
0.04913625866174698,
0.0008400139631703496,
-0.02777981199324131,
-0.04021713137626648,
0.035451650619506836,
0.004113757982850075,
0.029293594881892204,
0.073246069252491,
-0.006697410251945257,
-0.009585218504071236,
-0.013894067145884037,
-0.015519610606133938,
0.04824512079358101,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/30308 | [
"Documentation",
"Needs Decision",
"module:linear_model"
] | LogisticRegression's regularization is scaled by the dataset size
### Describe the workflow you want to enable
Other linear models on https://scikit-learn.org/1.5/modules/linear_model.html have regularization that doesn't depend on the dataset size
### Describe your proposed solution
It would be good to either chan... | 30,308 | [
0.011779696680605412,
0.09485457092523575,
0.029478440061211586,
-0.016453469172120094,
0.0419241301715374,
0.007019203156232834,
0.04797818511724472,
0.03231700509786606,
0.046015121042728424,
0.05674920231103897,
0.05494512617588043,
0.010518022812902927,
-0.029478788375854492,
0.0516829... |
https://github.com/scikit-learn/scikit-learn/issues/30308 | [
"Documentation",
"Needs Decision",
"module:linear_model"
] | LogisticRegression's regularization is scaled by the dataset size
### Describe the workflow you want to enable
Other linear models on https://scikit-learn.org/1.5/modules/linear_model.html have regularization that doesn't depend on the dataset size
### Describe your proposed solution
It would be good to either chan... | 30,308 | [
0.013729400932788849,
0.07315853983163834,
0.04010680690407753,
-0.012533933855593204,
0.0639471560716629,
0.006394384428858757,
0.04322042316198349,
0.03989529237151146,
0.045912183821201324,
0.06103837117552757,
0.03853701800107956,
0.031224040314555168,
-0.017278682440519333,
0.02559049... |
https://github.com/scikit-learn/scikit-learn/issues/30308 | [
"Documentation",
"Needs Decision",
"module:linear_model"
] | LogisticRegression's regularization is scaled by the dataset size
### Describe the workflow you want to enable
Other linear models on https://scikit-learn.org/1.5/modules/linear_model.html have regularization that doesn't depend on the dataset size
### Describe your proposed solution
It would be good to either chan... | 30,308 | [
0.01556793786585331,
0.08019150793552399,
0.01802172139286995,
-0.014855055138468742,
0.03753691911697388,
0.005779172293841839,
0.051385071128606796,
0.035624910145998,
0.03871380537748337,
0.05005265027284622,
0.04695041477680206,
0.011699234135448933,
-0.023182164877653122,
0.0404518097... |
https://github.com/scikit-learn/scikit-learn/issues/30308 | [
"Documentation",
"Needs Decision",
"module:linear_model"
] | LogisticRegression's regularization is scaled by the dataset size
### Describe the workflow you want to enable
Other linear models on https://scikit-learn.org/1.5/modules/linear_model.html have regularization that doesn't depend on the dataset size
### Describe your proposed solution
It would be good to either chan... | 30,308 | [
0.007625865750014782,
0.08108694851398468,
0.02802876941859722,
-0.016711030155420303,
0.04783114790916443,
0.0005548698827624321,
0.046727702021598816,
0.034407831728458405,
0.052376896142959595,
0.05260428413748741,
0.04847124218940735,
0.006012666039168835,
-0.026281021535396576,
0.0494... |
https://github.com/scikit-learn/scikit-learn/issues/30308 | [
"Documentation",
"Needs Decision",
"module:linear_model"
] | LogisticRegression's regularization is scaled by the dataset size
### Describe the workflow you want to enable
Other linear models on https://scikit-learn.org/1.5/modules/linear_model.html have regularization that doesn't depend on the dataset size
### Describe your proposed solution
It would be good to either chan... | 30,308 | [
0.018327703699469566,
0.0759238600730896,
0.028230059891939163,
-0.010403227992355824,
0.04885334149003029,
-0.0010509317507967353,
0.058511607348918915,
0.04022340476512909,
0.043547410517930984,
0.044707175344228745,
0.04657597467303276,
0.022867562249302864,
-0.020016154274344444,
0.023... |
https://github.com/scikit-learn/scikit-learn/issues/30308 | [
"Documentation",
"Needs Decision",
"module:linear_model"
] | LogisticRegression's regularization is scaled by the dataset size
### Describe the workflow you want to enable
Other linear models on https://scikit-learn.org/1.5/modules/linear_model.html have regularization that doesn't depend on the dataset size
### Describe your proposed solution
It would be good to either chan... | 30,308 | [
0.017698392271995544,
0.08216698467731476,
0.027616508305072784,
-0.019925223663449287,
0.05758842080831528,
0.009337297640740871,
0.02334320917725563,
0.05158073082566261,
0.018601397052407265,
0.02713702991604805,
0.047514453530311584,
0.016791198402643204,
-0.043030597269535065,
0.03751... |
https://github.com/scikit-learn/scikit-learn/issues/30308 | [
"Documentation",
"Needs Decision",
"module:linear_model"
] | LogisticRegression's regularization is scaled by the dataset size
### Describe the workflow you want to enable
Other linear models on https://scikit-learn.org/1.5/modules/linear_model.html have regularization that doesn't depend on the dataset size
### Describe your proposed solution
It would be good to either chan... | 30,308 | [
0.01066717691719532,
0.04539846256375313,
0.023474715650081635,
-0.020106248557567596,
0.03278527781367302,
0.009449408389627934,
0.03932313248515129,
0.018738524988293648,
-0.009306445717811584,
0.035681143403053284,
0.07973220944404602,
-0.012323908507823944,
-0.006528361234813929,
0.050... |
https://github.com/scikit-learn/scikit-learn/issues/30305 | [
"API",
"RFC"
] | RFC deprecation warnings only when user is affected
While reviewing https://github.com/scikit-learn/scikit-learn/pull/29288, I realised we're raising deprecation warnings to users, while most of them are not affected by the change, since the change only occurs when a division by zero is happenings.
So I was wonderi... | 30,305 | [
-0.010608837939798832,
0.07279873639345169,
0.00041549126035533845,
-0.04573969915509224,
0.03189017251133919,
-0.01273234561085701,
0.01237901858985424,
0.013583720661699772,
-0.01676371321082115,
-0.009488953277468681,
0.10447321087121964,
0.02142105996608734,
-0.05061803013086319,
-0.01... |
https://github.com/scikit-learn/scikit-learn/issues/30305 | [
"API",
"RFC"
] | RFC deprecation warnings only when user is affected
While reviewing https://github.com/scikit-learn/scikit-learn/pull/29288, I realised we're raising deprecation warnings to users, while most of them are not affected by the change, since the change only occurs when a division by zero is happenings.
So I was wonderi... | 30,305 | [
0.00022436230210587382,
0.06888266652822495,
0.0032780312467366457,
-0.057808104902505875,
0.009704039432108402,
-0.029257168993353844,
-0.014219596982002258,
0.012410236522555351,
-0.01419274602085352,
-0.004995008930563927,
0.09680803120136261,
0.02613281086087227,
-0.056168802082538605,
... |
https://github.com/scikit-learn/scikit-learn/issues/30305 | [
"API",
"RFC"
] | RFC deprecation warnings only when user is affected
While reviewing https://github.com/scikit-learn/scikit-learn/pull/29288, I realised we're raising deprecation warnings to users, while most of them are not affected by the change, since the change only occurs when a division by zero is happenings.
So I was wonderi... | 30,305 | [
-0.005755784921348095,
0.055782485753297806,
-0.0009416936081834137,
-0.051988083869218826,
0.01095305010676384,
-0.013467477634549141,
-0.012045390903949738,
0.007880632765591145,
-0.016476500779390335,
-0.00967065803706646,
0.09925869852304459,
0.03291764855384827,
-0.04138042405247688,
... |
https://github.com/scikit-learn/scikit-learn/issues/30305 | [
"API",
"RFC"
] | RFC deprecation warnings only when user is affected
While reviewing https://github.com/scikit-learn/scikit-learn/pull/29288, I realised we're raising deprecation warnings to users, while most of them are not affected by the change, since the change only occurs when a division by zero is happenings.
So I was wonderi... | 30,305 | [
-0.009192869998514652,
0.06592334806919098,
-0.002742585726082325,
-0.04698453098535538,
0.017335768789052963,
-0.016720520332455635,
-0.0009401840507052839,
0.005085894837975502,
-0.03286764770746231,
-0.02180560864508152,
0.09499329328536987,
0.03601996973156929,
-0.043017372488975525,
-... |
https://github.com/scikit-learn/scikit-learn/issues/30305 | [
"API",
"RFC"
] | RFC deprecation warnings only when user is affected
While reviewing https://github.com/scikit-learn/scikit-learn/pull/29288, I realised we're raising deprecation warnings to users, while most of them are not affected by the change, since the change only occurs when a division by zero is happenings.
So I was wonderi... | 30,305 | [
-0.012550926767289639,
0.06212134286761284,
0.005286438390612602,
-0.051144640892744064,
0.011501645669341087,
-0.0187403354793787,
0.0071349237114191055,
-0.0031850452069193125,
-0.022086597979068756,
-0.012430781498551369,
0.09983539581298828,
0.02924523875117302,
-0.04448257014155388,
-... |
https://github.com/scikit-learn/scikit-learn/issues/30305 | [
"API",
"RFC"
] | RFC deprecation warnings only when user is affected
While reviewing https://github.com/scikit-learn/scikit-learn/pull/29288, I realised we're raising deprecation warnings to users, while most of them are not affected by the change, since the change only occurs when a division by zero is happenings.
So I was wonderi... | 30,305 | [
0.0018412520876154304,
0.046836938709020615,
0.0005785682005807757,
-0.04798655956983566,
0.012575673870742321,
-0.010278343223035336,
-0.007203476969152689,
-0.0016174368793144822,
-0.020118065178394318,
-0.012449881993234158,
0.10219939798116684,
0.03915807977318764,
-0.038494229316711426,... |
https://github.com/scikit-learn/scikit-learn/issues/30304 | [
"New Feature",
"Needs Info"
] | Factor out `EmptyRequest`
### Describe the workflow you want to enable
At the moment, SKL creates the `EmptyRequest` at run time [here](https://github.com/scikit-learn/scikit-learn/blob/4adafd9ceb8e67467b81654c3632cd99c203df40/sklearn/utils/_metadata_requests.py#L1565). That makes it difficult to test properly if an ... | 30,304 | [
0.037055302411317825,
0.05383361876010895,
0.05424261838197708,
0.017198439687490463,
0.03220102936029434,
-0.03446221351623535,
-0.012758439406752586,
-0.011396163143217564,
0.0010209879837930202,
0.008835211396217346,
0.05329033359885216,
0.03508281335234642,
-0.05783023685216904,
0.0032... |
https://github.com/scikit-learn/scikit-learn/issues/30304 | [
"New Feature",
"Needs Info"
] | Factor out `EmptyRequest`
### Describe the workflow you want to enable
At the moment, SKL creates the `EmptyRequest` at run time [here](https://github.com/scikit-learn/scikit-learn/blob/4adafd9ceb8e67467b81654c3632cd99c203df40/sklearn/utils/_metadata_requests.py#L1565). That makes it difficult to test properly if an ... | 30,304 | [
0.045414626598358154,
0.03960198909044266,
0.04743848741054535,
0.00892369169741869,
0.030971037223935127,
-0.02243170700967312,
-0.006522440817207098,
-0.01836138777434826,
0.005458480212837458,
0.0069212764501571655,
0.050731685012578964,
0.03783688694238663,
-0.05689692497253418,
0.0230... |
https://github.com/scikit-learn/scikit-learn/issues/30304 | [
"New Feature",
"Needs Info"
] | Factor out `EmptyRequest`
### Describe the workflow you want to enable
At the moment, SKL creates the `EmptyRequest` at run time [here](https://github.com/scikit-learn/scikit-learn/blob/4adafd9ceb8e67467b81654c3632cd99c203df40/sklearn/utils/_metadata_requests.py#L1565). That makes it difficult to test properly if an ... | 30,304 | [
0.028894763439893723,
0.05750308185815811,
0.048551350831985474,
0.015918340533971786,
0.026020634919404984,
-0.03195679932832718,
0.00610155425965786,
-0.014569309540092945,
-0.03352164849638939,
-0.002906280104070902,
0.052541300654411316,
0.009927474893629551,
-0.07135499268770218,
0.02... |
https://github.com/scikit-learn/scikit-learn/issues/30304 | [
"New Feature",
"Needs Info"
] | Factor out `EmptyRequest`
### Describe the workflow you want to enable
At the moment, SKL creates the `EmptyRequest` at run time [here](https://github.com/scikit-learn/scikit-learn/blob/4adafd9ceb8e67467b81654c3632cd99c203df40/sklearn/utils/_metadata_requests.py#L1565). That makes it difficult to test properly if an ... | 30,304 | [
0.041122715920209885,
0.04087056219577789,
0.050658948719501495,
0.008007308468222618,
0.03791552037000656,
-0.02991992048919201,
-0.009850306436419487,
-0.00456111179664731,
-0.0022193712648004293,
-0.009633787907660007,
0.04495573416352272,
0.03631307929754257,
-0.049221448600292206,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/30304 | [
"New Feature",
"Needs Info"
] | Factor out `EmptyRequest`
### Describe the workflow you want to enable
At the moment, SKL creates the `EmptyRequest` at run time [here](https://github.com/scikit-learn/scikit-learn/blob/4adafd9ceb8e67467b81654c3632cd99c203df40/sklearn/utils/_metadata_requests.py#L1565). That makes it difficult to test properly if an ... | 30,304 | [
0.026246974244713783,
0.0551287904381752,
0.049961548298597336,
0.004714404232800007,
0.01409187726676464,
-0.03956780210137367,
-0.01927608996629715,
-0.008371636271476746,
0.0011355254100635648,
0.0102201784029603,
0.06270702183246613,
0.009653961285948753,
-0.03576340898871422,
0.033370... |
https://github.com/scikit-learn/scikit-learn/issues/30304 | [
"New Feature",
"Needs Info"
] | Factor out `EmptyRequest`
### Describe the workflow you want to enable
At the moment, SKL creates the `EmptyRequest` at run time [here](https://github.com/scikit-learn/scikit-learn/blob/4adafd9ceb8e67467b81654c3632cd99c203df40/sklearn/utils/_metadata_requests.py#L1565). That makes it difficult to test properly if an ... | 30,304 | [
0.05132418870925903,
0.038138046860694885,
0.059859566390514374,
0.007735237944871187,
0.027289314195513725,
-0.02589387632906437,
-0.015570997260510921,
-0.02014043740928173,
0.003091153223067522,
0.008739486336708069,
0.05424482002854347,
0.027001265436410904,
-0.06062779575586319,
0.018... |
https://github.com/scikit-learn/scikit-learn/issues/30304 | [
"New Feature",
"Needs Info"
] | Factor out `EmptyRequest`
### Describe the workflow you want to enable
At the moment, SKL creates the `EmptyRequest` at run time [here](https://github.com/scikit-learn/scikit-learn/blob/4adafd9ceb8e67467b81654c3632cd99c203df40/sklearn/utils/_metadata_requests.py#L1565). That makes it difficult to test properly if an ... | 30,304 | [
0.0019770150538533926,
0.07724814862012863,
0.02333858236670494,
0.009647700004279613,
0.02256184071302414,
-0.045561064034700394,
0.040941063314676285,
-0.002252341480925679,
0.00865123886615038,
-0.021850021556019783,
0.05761462077498436,
0.005996592342853546,
-0.027366459369659424,
0.02... |
https://github.com/scikit-learn/scikit-learn/issues/30304 | [
"New Feature",
"Needs Info"
] | Factor out `EmptyRequest`
### Describe the workflow you want to enable
At the moment, SKL creates the `EmptyRequest` at run time [here](https://github.com/scikit-learn/scikit-learn/blob/4adafd9ceb8e67467b81654c3632cd99c203df40/sklearn/utils/_metadata_requests.py#L1565). That makes it difficult to test properly if an ... | 30,304 | [
0.03575235605239868,
0.08584249764680862,
0.04460128769278526,
0.013009171932935715,
0.043099869042634964,
-0.00692042475566268,
0.049327295273542404,
-0.012906432151794434,
0.01294736284762621,
-0.001876855967566371,
0.026899781078100204,
0.029525578022003174,
-0.02426435612142086,
0.0203... |
https://github.com/scikit-learn/scikit-learn/issues/30304 | [
"New Feature",
"Needs Info"
] | Factor out `EmptyRequest`
### Describe the workflow you want to enable
At the moment, SKL creates the `EmptyRequest` at run time [here](https://github.com/scikit-learn/scikit-learn/blob/4adafd9ceb8e67467b81654c3632cd99c203df40/sklearn/utils/_metadata_requests.py#L1565). That makes it difficult to test properly if an ... | 30,304 | [
0.04209139198064804,
0.07114970684051514,
0.03791521489620209,
0.013361466117203236,
0.022977003827691078,
-0.02501773089170456,
0.026400571689009666,
-0.00011275088036200032,
-0.029047008603811264,
-0.0018791878828778863,
0.03939240425825119,
0.049874477088451385,
-0.04897790029644966,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/30298 | [
"Blocker"
] | Make transition from 1.5 to 1.6 easier for third-party library using scikit-learn utilities
In 1.6, we introduced several breaking changes:
- `self._validate_data` became `sklearn.utils.validation.validate_data`
- `self._check_n_features` became `sklearn.utils.validation.check_n_features`
- `self._check_feature_n... | 30,298 | [
0.03493405878543854,
0.10055939108133316,
0.013236576691269875,
-0.04432135075330734,
0.0026361665222793818,
-0.009854842908680439,
0.05361507833003998,
-0.0021719124633818865,
0.0670732781291008,
-0.037424780428409576,
0.014290795661509037,
0.08759193867444992,
-0.013059183955192566,
0.06... |
https://github.com/scikit-learn/scikit-learn/issues/30291 | [
"Needs Triage"
] | ⚠️ CI failed on macOS.pylatest_conda_forge_mkl (last failure: Nov 18, 2024) ⚠️
**CI failed on [macOS.pylatest_conda_forge_mkl](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=72102&view=logs&j=97641769-79fb-5590-9088-a30ce9b850b9)** (Nov 18, 2024)
Unable to find junit file. Please see link for d... | 30,291 | [
-0.010866602882742882,
0.004353811033070087,
-0.045158751308918,
-0.08057717978954315,
0.04562711343169212,
0.001224973937496543,
0.006074101198464632,
0.05145006626844406,
0.017676208168268204,
0.012107753194868565,
0.029116198420524597,
0.05320824310183525,
-0.01721811108291149,
0.067278... |
https://github.com/scikit-learn/scikit-learn/issues/30286 | [
"Bug",
"Needs Triage"
] | Cython error while installing development version on MacOS M2 chip
### Describe the bug
Hello - While working on #16236 , I am getting a Cython error .
I pulled the latest version of Scikit Learn from the main branch . I am following the instructions here to install the development version of Scikit learn ... | 30,286 | [
0.005261719226837158,
-0.007454973645508289,
-0.04846322536468506,
-0.0491238497197628,
0.03389010205864906,
0.03902728110551834,
0.012088457122445107,
0.01057502068579197,
0.012381969951093197,
-0.034480977803468704,
0.013580036349594593,
0.06771764904260635,
-0.020751776173710823,
0.0269... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.