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/32987 | [
"Bug",
"module:linear_model",
"module:test-suite"
] | CI : Numerical flakiness in test_enet_ols_consistency
### Describe the bug
While working on another scikit-learn PR (**#32368**), CI intermittently failed in `sklearn/linear_model/tests/test_coordinate_descent.py::test_enet_ols_consistency`.It came from a strict numerical ordering assertion on the squared error:
```... | 32,987 | [
-0.04953416436910629,
0.04842507094144821,
0.01561347022652626,
0.03160390630364418,
0.0807425007224083,
-0.00096272979862988,
-0.008100507780909538,
0.045252665877342224,
0.019665738567709923,
0.03857962787151337,
0.04935724288225174,
-0.0011156407417729497,
0.014752774499356747,
0.003484... |
https://github.com/scikit-learn/scikit-learn/issues/32987 | [
"Bug",
"module:linear_model",
"module:test-suite"
] | CI : Numerical flakiness in test_enet_ols_consistency
### Describe the bug
While working on another scikit-learn PR (**#32368**), CI intermittently failed in `sklearn/linear_model/tests/test_coordinate_descent.py::test_enet_ols_consistency`.It came from a strict numerical ordering assertion on the squared error:
```... | 32,987 | [
-0.04953416436910629,
0.04842507094144821,
0.01561347022652626,
0.03160390630364418,
0.0807425007224083,
-0.00096272979862988,
-0.008100507780909538,
0.045252665877342224,
0.019665738567709923,
0.03857962787151337,
0.04935724288225174,
-0.0011156407417729497,
0.014752774499356747,
0.003484... |
https://github.com/scikit-learn/scikit-learn/issues/32987 | [
"Bug",
"module:linear_model",
"module:test-suite"
] | CI : Numerical flakiness in test_enet_ols_consistency
### Describe the bug
While working on another scikit-learn PR (**#32368**), CI intermittently failed in `sklearn/linear_model/tests/test_coordinate_descent.py::test_enet_ols_consistency`.It came from a strict numerical ordering assertion on the squared error:
```... | 32,987 | [
-0.04953416436910629,
0.04842507094144821,
0.01561347022652626,
0.03160390630364418,
0.0807425007224083,
-0.00096272979862988,
-0.008100507780909538,
0.045252665877342224,
0.019665738567709923,
0.03857962787151337,
0.04935724288225174,
-0.0011156407417729497,
0.014752774499356747,
0.003484... |
https://github.com/scikit-learn/scikit-learn/issues/32978 | [
"Bug"
] | janitor module conflicts with sklearn cross_val_score
### Describe the bug
Importing janitor when using LeaveOneOut() with cross_val_score() causing warning.
### Steps/Code to Reproduce
```
from sklearn.model_selection import LeaveOneOut, KFold, cross_val_score
import janitor #cannot be used with cross_val_score si... | 32,978 | [
0.000030852348572807387,
-0.025421610102057457,
0.02245662733912468,
-0.02588825114071369,
0.08300504088401794,
0.025996878743171692,
0.03968454897403717,
0.02542918361723423,
0.05963809788227081,
-0.013030403293669224,
0.020124146714806557,
0.09837298095226288,
-0.024447523057460785,
0.07... |
https://github.com/scikit-learn/scikit-learn/issues/32978 | [
"Bug"
] | janitor module conflicts with sklearn cross_val_score
### Describe the bug
Importing janitor when using LeaveOneOut() with cross_val_score() causing warning.
### Steps/Code to Reproduce
```
from sklearn.model_selection import LeaveOneOut, KFold, cross_val_score
import janitor #cannot be used with cross_val_score si... | 32,978 | [
0.000030852348572807387,
-0.025421610102057457,
0.02245662733912468,
-0.02588825114071369,
0.08300504088401794,
0.025996878743171692,
0.03968454897403717,
0.02542918361723423,
0.05963809788227081,
-0.013030403293669224,
0.020124146714806557,
0.09837298095226288,
-0.024447523057460785,
0.07... |
https://github.com/scikit-learn/scikit-learn/issues/32961 | [
"Bug"
] | Consistent HTTP 403 Figshare error since December 27
Seems to be failing since December 27 around 13:00 UTC, see https://github.com/lesteve/test-figshare-fetchers/actions.
I can reproduce locally:
```
❯ curl https://figshare.com/ndownloader/files/5976078
<html>
<head><title>403 Forbidden</title></head>
<b... | 32,961 | [
0.008958356454968452,
0.05082738399505615,
-0.014958844520151615,
-0.0036849549505859613,
0.0033359031658619642,
0.0009534612181596458,
0.016445951536297798,
0.049593206495046616,
-0.011524852365255356,
0.012199100106954575,
-0.033765729516744614,
-0.03463439270853996,
0.023046625778079033,
... |
https://github.com/scikit-learn/scikit-learn/issues/32961 | [
"Bug"
] | Consistent HTTP 403 Figshare error since December 27
Seems to be failing since December 27 around 13:00 UTC, see https://github.com/lesteve/test-figshare-fetchers/actions.
I can reproduce locally:
```
❯ curl https://figshare.com/ndownloader/files/5976078
<html>
<head><title>403 Forbidden</title></head>
<b... | 32,961 | [
0.023453950881958008,
0.03570440784096718,
-0.022065846249461174,
-0.0025270746555179358,
-0.01059426087886095,
-0.0019058993784710765,
0.016616836190223694,
0.0471792034804821,
-0.009555676952004433,
0.022691313177347183,
-0.028467563912272453,
-0.041417334228754044,
0.01981074921786785,
... |
https://github.com/scikit-learn/scikit-learn/issues/32961 | [
"Bug"
] | Consistent HTTP 403 Figshare error since December 27
Seems to be failing since December 27 around 13:00 UTC, see https://github.com/lesteve/test-figshare-fetchers/actions.
I can reproduce locally:
```
❯ curl https://figshare.com/ndownloader/files/5976078
<html>
<head><title>403 Forbidden</title></head>
<b... | 32,961 | [
0.008329533040523529,
0.02905837632715702,
-0.015248342417180538,
0.008298893459141254,
-0.003041369840502739,
-0.005483637563884258,
0.023840997368097305,
0.034504346549510956,
-0.021467603743076324,
0.023156506940722466,
-0.01879861205816269,
-0.04416784644126892,
0.015058344230055809,
0... |
https://github.com/scikit-learn/scikit-learn/issues/32958 | [
"Needs Triage"
] | ⚠️ CI failed on macOS.pylatest_conda_forge_mkl_no_openmp (last failure: Dec 28, 2025) ⚠️
**CI failed on [macOS.pylatest_conda_forge_mkl_no_openmp](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=83721&view=logs&j=8b4d29c4-7356-5617-94d6-7bef17a56394)** (Dec 28, 2025)
Unable to find junit file. P... | 32,958 | [
-0.011856688186526299,
0.0234272088855505,
-0.04899651184678078,
-0.06914073973894119,
0.02904042787849903,
0.00878999289125204,
0.010556652210652828,
0.04948097839951515,
0.0036213945131748915,
0.01664370857179165,
0.013898581266403198,
0.05995917320251465,
-0.013562561012804508,
0.072411... |
https://github.com/scikit-learn/scikit-learn/issues/32958 | [
"Needs Triage"
] | ⚠️ CI failed on macOS.pylatest_conda_forge_mkl_no_openmp (last failure: Dec 28, 2025) ⚠️
**CI failed on [macOS.pylatest_conda_forge_mkl_no_openmp](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=83721&view=logs&j=8b4d29c4-7356-5617-94d6-7bef17a56394)** (Dec 28, 2025)
Unable to find junit file. P... | 32,958 | [
-0.01396624743938446,
0.009465719573199749,
-0.051512785255908966,
-0.0770154744386673,
0.03730184584856033,
0.003996598534286022,
0.002357169520109892,
0.0437997542321682,
-0.008771470747888088,
0.022086532786488533,
0.014387167058885098,
0.0643199235200882,
-0.0010882574133574963,
0.0477... |
https://github.com/scikit-learn/scikit-learn/issues/32957 | [
"Documentation"
] | DOC: First example for SimpleImputer is unclear
### Describe the issue linked to the documentation
The first example for SimpleImputer in 7.4.2. Univariate feature imputation (https://scikit-learn.org/stable/modules/impute.html#univariate-feature-imputation) is bit unclear. While the imputation is done on an array me... | 32,957 | [
0.010583925060927868,
-0.05945399031043053,
0.0029388524126261473,
-0.030821634456515312,
0.009235749021172523,
0.01599813997745514,
0.15256687998771667,
0.00028732349164783955,
0.0317760668694973,
0.0025044416543096304,
0.018113136291503906,
0.016354365274310112,
0.09326720237731934,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32957 | [
"Documentation"
] | DOC: First example for SimpleImputer is unclear
### Describe the issue linked to the documentation
The first example for SimpleImputer in 7.4.2. Univariate feature imputation (https://scikit-learn.org/stable/modules/impute.html#univariate-feature-imputation) is bit unclear. While the imputation is done on an array me... | 32,957 | [
-0.003064557211473584,
-0.046975161880254745,
0.013610380701720715,
-0.023140858858823776,
0.014996626414358616,
0.011339705437421799,
0.14371006190776825,
0.015856044366955757,
0.032853178679943085,
0.020021677017211914,
0.006661511491984129,
0.01886996626853943,
0.09215573221445084,
0.00... |
https://github.com/scikit-learn/scikit-learn/issues/32952 | [
"New Feature",
"Needs Triage"
] | Add Net Benefit for classifications metrics
### Describe the workflow you want to enable
Net benefit is defined as a decision-analytic measure that quantifies the clinical value of a prediction model, test, or marker by putting its benefits and harms on the same scale. This is done by specifying an exchange rate—a cl... | 32,952 | [
-0.03593060374259949,
0.10690997540950775,
0.016158495098352432,
-0.037823982536792755,
-0.0003942419425584376,
0.02575860358774662,
0.012529829517006874,
0.026531493291258812,
-0.014130021445453167,
-0.0009956930298358202,
0.026007961481809616,
-0.004584323614835739,
-0.038538359105587006,
... |
https://github.com/scikit-learn/scikit-learn/issues/32949 | [
"Needs Triage"
] | BUG: HuberRegressor fails with boolean feature matrix
### Summary
`HuberRegressor.fit` raises a `TypeError` when the feature matrix is boolean because the internal gradient helper negates a boolean mask with the `-` operator. In NumPy >=1.13 this triggers `TypeError: The numpy boolean negative, the '-' operator, is no... | 32,949 | [
-0.033142246305942535,
-0.0010184599086642265,
0.009453453123569489,
-0.01714838668704033,
0.05717819556593895,
-0.004704043734818697,
0.05062893033027649,
0.02942950464785099,
0.04698815941810608,
-0.01327090710401535,
0.03559489920735359,
0.06394099444150925,
0.008872794918715954,
0.0377... |
https://github.com/scikit-learn/scikit-learn/issues/32947 | [
"Needs Triage"
] | clone: treat class-valued parameters as non-estimators (avoid TypeError) [swev-id: scikit-learn__scikit-learn-12585]
## User request
Clone fails for parameters that are estimator types.
Key: clone should not error when a parameter is a class; adjust clone to treat classes as non-estimators (e.g., check isinstance(est... | 32,947 | [
0.00395727576687932,
0.09195386618375778,
0.033786945044994354,
0.024641485884785652,
0.05301801487803459,
-0.007405505981296301,
0.04808334633708,
0.02659902162849903,
-0.006000826600939035,
0.000019000643078470603,
0.01656915992498398,
0.06200605630874634,
-0.0063339038752019405,
0.00284... |
https://github.com/scikit-learn/scikit-learn/issues/32946 | [
"Documentation"
] | GridSearchCV.verbose documentation does not match actual behavior (values >3, >10)
### Describe the issue linked to the documentation
[`GridSearchCV` docs ](https://scikit-learn.org/1.7/modules/generated/sklearn.model_selection.GridSearchCV.html) state
> **verbose** int
> Controls the verbosity: the higher, the more... | 32,946 | [
-0.009779700078070164,
-0.06023668497800827,
0.0044284723699092865,
0.010798363015055656,
0.021071074530482292,
-0.010827405378222466,
0.012586713768541813,
0.02707671746611595,
0.017857195809483528,
0.02725336328148842,
0.04997609928250313,
0.055209871381521225,
0.000913943920750171,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32946 | [
"Documentation"
] | GridSearchCV.verbose documentation does not match actual behavior (values >3, >10)
### Describe the issue linked to the documentation
[`GridSearchCV` docs ](https://scikit-learn.org/1.7/modules/generated/sklearn.model_selection.GridSearchCV.html) state
> **verbose** int
> Controls the verbosity: the higher, the more... | 32,946 | [
-0.009779700078070164,
-0.06023668497800827,
0.0044284723699092865,
0.010798363015055656,
0.021071074530482292,
-0.010827405378222466,
0.012586713768541813,
0.02707671746611595,
0.017857195809483528,
0.02725336328148842,
0.04997609928250313,
0.055209871381521225,
0.000913943920750171,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32946 | [
"Documentation"
] | GridSearchCV.verbose documentation does not match actual behavior (values >3, >10)
### Describe the issue linked to the documentation
[`GridSearchCV` docs ](https://scikit-learn.org/1.7/modules/generated/sklearn.model_selection.GridSearchCV.html) state
> **verbose** int
> Controls the verbosity: the higher, the more... | 32,946 | [
-0.009779700078070164,
-0.06023668497800827,
0.0044284723699092865,
0.010798363015055656,
0.021071074530482292,
-0.010827405378222466,
0.012586713768541813,
0.02707671746611595,
0.017857195809483528,
0.02725336328148842,
0.04997609928250313,
0.055209871381521225,
0.000913943920750171,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32946 | [
"Documentation"
] | GridSearchCV.verbose documentation does not match actual behavior (values >3, >10)
### Describe the issue linked to the documentation
[`GridSearchCV` docs ](https://scikit-learn.org/1.7/modules/generated/sklearn.model_selection.GridSearchCV.html) state
> **verbose** int
> Controls the verbosity: the higher, the more... | 32,946 | [
-0.009779700078070164,
-0.06023668497800827,
0.0044284723699092865,
0.010798363015055656,
0.021071074530482292,
-0.010827405378222466,
0.012586713768541813,
0.02707671746611595,
0.017857195809483528,
0.02725336328148842,
0.04997609928250313,
0.055209871381521225,
0.000913943920750171,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32946 | [
"Documentation"
] | GridSearchCV.verbose documentation does not match actual behavior (values >3, >10)
### Describe the issue linked to the documentation
[`GridSearchCV` docs ](https://scikit-learn.org/1.7/modules/generated/sklearn.model_selection.GridSearchCV.html) state
> **verbose** int
> Controls the verbosity: the higher, the more... | 32,946 | [
-0.009779700078070164,
-0.06023668497800827,
0.0044284723699092865,
0.010798363015055656,
0.021071074530482292,
-0.010827405378222466,
0.012586713768541813,
0.02707671746611595,
0.017857195809483528,
0.02725336328148842,
0.04997609928250313,
0.055209871381521225,
0.000913943920750171,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32946 | [
"Documentation"
] | GridSearchCV.verbose documentation does not match actual behavior (values >3, >10)
### Describe the issue linked to the documentation
[`GridSearchCV` docs ](https://scikit-learn.org/1.7/modules/generated/sklearn.model_selection.GridSearchCV.html) state
> **verbose** int
> Controls the verbosity: the higher, the more... | 32,946 | [
-0.009779700078070164,
-0.06023668497800827,
0.0044284723699092865,
0.010798363015055656,
0.021071074530482292,
-0.010827405378222466,
0.012586713768541813,
0.02707671746611595,
0.017857195809483528,
0.02725336328148842,
0.04997609928250313,
0.055209871381521225,
0.000913943920750171,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32946 | [
"Documentation"
] | GridSearchCV.verbose documentation does not match actual behavior (values >3, >10)
### Describe the issue linked to the documentation
[`GridSearchCV` docs ](https://scikit-learn.org/1.7/modules/generated/sklearn.model_selection.GridSearchCV.html) state
> **verbose** int
> Controls the verbosity: the higher, the more... | 32,946 | [
-0.009779700078070164,
-0.06023668497800827,
0.0044284723699092865,
0.010798363015055656,
0.021071074530482292,
-0.010827405378222466,
0.012586713768541813,
0.02707671746611595,
0.017857195809483528,
0.02725336328148842,
0.04997609928250313,
0.055209871381521225,
0.000913943920750171,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32946 | [
"Documentation"
] | GridSearchCV.verbose documentation does not match actual behavior (values >3, >10)
### Describe the issue linked to the documentation
[`GridSearchCV` docs ](https://scikit-learn.org/1.7/modules/generated/sklearn.model_selection.GridSearchCV.html) state
> **verbose** int
> Controls the verbosity: the higher, the more... | 32,946 | [
-0.009779700078070164,
-0.06023668497800827,
0.0044284723699092865,
0.010798363015055656,
0.021071074530482292,
-0.010827405378222466,
0.012586713768541813,
0.02707671746611595,
0.017857195809483528,
0.02725336328148842,
0.04997609928250313,
0.055209871381521225,
0.000913943920750171,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32946 | [
"Documentation"
] | GridSearchCV.verbose documentation does not match actual behavior (values >3, >10)
### Describe the issue linked to the documentation
[`GridSearchCV` docs ](https://scikit-learn.org/1.7/modules/generated/sklearn.model_selection.GridSearchCV.html) state
> **verbose** int
> Controls the verbosity: the higher, the more... | 32,946 | [
-0.009779700078070164,
-0.06023668497800827,
0.0044284723699092865,
0.010798363015055656,
0.021071074530482292,
-0.010827405378222466,
0.012586713768541813,
0.02707671746611595,
0.017857195809483528,
0.02725336328148842,
0.04997609928250313,
0.055209871381521225,
0.000913943920750171,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32946 | [
"Documentation"
] | GridSearchCV.verbose documentation does not match actual behavior (values >3, >10)
### Describe the issue linked to the documentation
[`GridSearchCV` docs ](https://scikit-learn.org/1.7/modules/generated/sklearn.model_selection.GridSearchCV.html) state
> **verbose** int
> Controls the verbosity: the higher, the more... | 32,946 | [
-0.009779700078070164,
-0.06023668497800827,
0.0044284723699092865,
0.010798363015055656,
0.021071074530482292,
-0.010827405378222466,
0.012586713768541813,
0.02707671746611595,
0.017857195809483528,
0.02725336328148842,
0.04997609928250313,
0.055209871381521225,
0.000913943920750171,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32946 | [
"Documentation"
] | GridSearchCV.verbose documentation does not match actual behavior (values >3, >10)
### Describe the issue linked to the documentation
[`GridSearchCV` docs ](https://scikit-learn.org/1.7/modules/generated/sklearn.model_selection.GridSearchCV.html) state
> **verbose** int
> Controls the verbosity: the higher, the more... | 32,946 | [
-0.009779700078070164,
-0.06023668497800827,
0.0044284723699092865,
0.010798363015055656,
0.021071074530482292,
-0.010827405378222466,
0.012586713768541813,
0.02707671746611595,
0.017857195809483528,
0.02725336328148842,
0.04997609928250313,
0.055209871381521225,
0.000913943920750171,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32930 | [
"RFC"
] | DOC Supervised clustering metrics specify array input dtype
Several of our supervised clustering metrics specify/suggest (??) that the array input should be of type `int` or `integral`, e.g.:
`pair_confusion_matrix`:
https://github.com/scikit-learn/scikit-learn/blob/b0ba8b029c298e0cc545206d2df4757be0ec2ac2/sklearn/m... | 32,930 | [
-0.04556876793503761,
-0.07160882651805878,
-0.0012911552330479026,
0.01229992974549532,
0.07844536006450653,
0.030839331448078156,
0.03535199910402298,
0.017517637461423874,
0.026458846405148506,
-0.027030114084482193,
-0.0234561488032341,
0.012665705755352974,
-0.024663247168064117,
0.04... |
https://github.com/scikit-learn/scikit-learn/issues/32930 | [
"RFC"
] | DOC Supervised clustering metrics specify array input dtype
Several of our supervised clustering metrics specify/suggest (??) that the array input should be of type `int` or `integral`, e.g.:
`pair_confusion_matrix`:
https://github.com/scikit-learn/scikit-learn/blob/b0ba8b029c298e0cc545206d2df4757be0ec2ac2/sklearn/m... | 32,930 | [
-0.04556876793503761,
-0.07160882651805878,
-0.0012911552330479026,
0.01229992974549532,
0.07844536006450653,
0.030839331448078156,
0.03535199910402298,
0.017517637461423874,
0.026458846405148506,
-0.027030114084482193,
-0.0234561488032341,
0.012665705755352974,
-0.024663247168064117,
0.04... |
https://github.com/scikit-learn/scikit-learn/issues/32930 | [
"RFC"
] | DOC Supervised clustering metrics specify array input dtype
Several of our supervised clustering metrics specify/suggest (??) that the array input should be of type `int` or `integral`, e.g.:
`pair_confusion_matrix`:
https://github.com/scikit-learn/scikit-learn/blob/b0ba8b029c298e0cc545206d2df4757be0ec2ac2/sklearn/m... | 32,930 | [
-0.04556876793503761,
-0.07160882651805878,
-0.0012911552330479026,
0.01229992974549532,
0.07844536006450653,
0.030839331448078156,
0.03535199910402298,
0.017517637461423874,
0.026458846405148506,
-0.027030114084482193,
-0.0234561488032341,
0.012665705755352974,
-0.024663247168064117,
0.04... |
https://github.com/scikit-learn/scikit-learn/issues/32930 | [
"RFC"
] | DOC Supervised clustering metrics specify array input dtype
Several of our supervised clustering metrics specify/suggest (??) that the array input should be of type `int` or `integral`, e.g.:
`pair_confusion_matrix`:
https://github.com/scikit-learn/scikit-learn/blob/b0ba8b029c298e0cc545206d2df4757be0ec2ac2/sklearn/m... | 32,930 | [
-0.04556876793503761,
-0.07160882651805878,
-0.0012911552330479026,
0.01229992974549532,
0.07844536006450653,
0.030839331448078156,
0.03535199910402298,
0.017517637461423874,
0.026458846405148506,
-0.027030114084482193,
-0.0234561488032341,
0.012665705755352974,
-0.024663247168064117,
0.04... |
https://github.com/scikit-learn/scikit-learn/issues/32930 | [
"RFC"
] | DOC Supervised clustering metrics specify array input dtype
Several of our supervised clustering metrics specify/suggest (??) that the array input should be of type `int` or `integral`, e.g.:
`pair_confusion_matrix`:
https://github.com/scikit-learn/scikit-learn/blob/b0ba8b029c298e0cc545206d2df4757be0ec2ac2/sklearn/m... | 32,930 | [
-0.04556876793503761,
-0.07160882651805878,
-0.0012911552330479026,
0.01229992974549532,
0.07844536006450653,
0.030839331448078156,
0.03535199910402298,
0.017517637461423874,
0.026458846405148506,
-0.027030114084482193,
-0.0234561488032341,
0.012665705755352974,
-0.024663247168064117,
0.04... |
https://github.com/scikit-learn/scikit-learn/issues/32930 | [
"RFC"
] | DOC Supervised clustering metrics specify array input dtype
Several of our supervised clustering metrics specify/suggest (??) that the array input should be of type `int` or `integral`, e.g.:
`pair_confusion_matrix`:
https://github.com/scikit-learn/scikit-learn/blob/b0ba8b029c298e0cc545206d2df4757be0ec2ac2/sklearn/m... | 32,930 | [
-0.04556876793503761,
-0.07160882651805878,
-0.0012911552330479026,
0.01229992974549532,
0.07844536006450653,
0.030839331448078156,
0.03535199910402298,
0.017517637461423874,
0.026458846405148506,
-0.027030114084482193,
-0.0234561488032341,
0.012665705755352974,
-0.024663247168064117,
0.04... |
https://github.com/scikit-learn/scikit-learn/issues/32930 | [
"RFC"
] | DOC Supervised clustering metrics specify array input dtype
Several of our supervised clustering metrics specify/suggest (??) that the array input should be of type `int` or `integral`, e.g.:
`pair_confusion_matrix`:
https://github.com/scikit-learn/scikit-learn/blob/b0ba8b029c298e0cc545206d2df4757be0ec2ac2/sklearn/m... | 32,930 | [
-0.04556876793503761,
-0.07160882651805878,
-0.0012911552330479026,
0.01229992974549532,
0.07844536006450653,
0.030839331448078156,
0.03535199910402298,
0.017517637461423874,
0.026458846405148506,
-0.027030114084482193,
-0.0234561488032341,
0.012665705755352974,
-0.024663247168064117,
0.04... |
https://github.com/scikit-learn/scikit-learn/issues/32930 | [
"RFC"
] | DOC Supervised clustering metrics specify array input dtype
Several of our supervised clustering metrics specify/suggest (??) that the array input should be of type `int` or `integral`, e.g.:
`pair_confusion_matrix`:
https://github.com/scikit-learn/scikit-learn/blob/b0ba8b029c298e0cc545206d2df4757be0ec2ac2/sklearn/m... | 32,930 | [
-0.04556876793503761,
-0.07160882651805878,
-0.0012911552330479026,
0.01229992974549532,
0.07844536006450653,
0.030839331448078156,
0.03535199910402298,
0.017517637461423874,
0.026458846405148506,
-0.027030114084482193,
-0.0234561488032341,
0.012665705755352974,
-0.024663247168064117,
0.04... |
https://github.com/scikit-learn/scikit-learn/issues/32930 | [
"RFC"
] | DOC Supervised clustering metrics specify array input dtype
Several of our supervised clustering metrics specify/suggest (??) that the array input should be of type `int` or `integral`, e.g.:
`pair_confusion_matrix`:
https://github.com/scikit-learn/scikit-learn/blob/b0ba8b029c298e0cc545206d2df4757be0ec2ac2/sklearn/m... | 32,930 | [
-0.04556876793503761,
-0.07160882651805878,
-0.0012911552330479026,
0.01229992974549532,
0.07844536006450653,
0.030839331448078156,
0.03535199910402298,
0.017517637461423874,
0.026458846405148506,
-0.027030114084482193,
-0.0234561488032341,
0.012665705755352974,
-0.024663247168064117,
0.04... |
https://github.com/scikit-learn/scikit-learn/issues/32929 | [
"Bug",
"Needs Reproducible Code"
] | [Solved] Picard library modifies sklearn FastICA causing it to reject a default value for the `fun` parameter
### Describe the bug
I wrote some code that did not specify a `fun` parameter to FastICA and somehow this default value was rejected
```
File "/home/louis/dev/arxiv_explorer/benchmark_ica_impls.py", line 8... | 32,929 | [
-0.0017518358072265983,
0.009544174186885357,
0.01507040299475193,
0.018230587244033813,
0.11245769262313843,
-0.0031659139785915613,
0.00908780749887228,
-0.0033814588095992804,
-0.006822153925895691,
0.005537073127925396,
0.019131746143102646,
0.04455578327178955,
0.009550902061164379,
0... |
https://github.com/scikit-learn/scikit-learn/issues/32929 | [
"Bug",
"Needs Reproducible Code"
] | [Solved] Picard library modifies sklearn FastICA causing it to reject a default value for the `fun` parameter
### Describe the bug
I wrote some code that did not specify a `fun` parameter to FastICA and somehow this default value was rejected
```
File "/home/louis/dev/arxiv_explorer/benchmark_ica_impls.py", line 8... | 32,929 | [
-0.0017518358072265983,
0.009544174186885357,
0.01507040299475193,
0.018230587244033813,
0.11245769262313843,
-0.0031659139785915613,
0.00908780749887228,
-0.0033814588095992804,
-0.006822153925895691,
0.005537073127925396,
0.019131746143102646,
0.04455578327178955,
0.009550902061164379,
0... |
https://github.com/scikit-learn/scikit-learn/issues/32927 | [
"Bug"
] | `LogisticRegression`: Conflicting warnings when following deprecation advice for `penalty=None` (sklearn 1.8.0)
### Describe the bug
I am encountering a catch-22 situation with `LogisticRegression` warnings in scikit-learn 1.8.0.
When I use `LogisticRegression(penalty=None)`, I get a `FutureWarning` advising me to u... | 32,927 | [
0.006873808801174164,
0.05926556512713432,
0.04481958970427513,
-0.008841360919177532,
0.08840090036392212,
0.019288444891572,
0.015847602859139442,
0.02406025119125843,
0.041782572865486145,
0.008517214097082615,
0.07963430881500244,
0.04248065873980522,
-0.010747276246547699,
-0.04638900... |
https://github.com/scikit-learn/scikit-learn/issues/32927 | [
"Bug"
] | `LogisticRegression`: Conflicting warnings when following deprecation advice for `penalty=None` (sklearn 1.8.0)
### Describe the bug
I am encountering a catch-22 situation with `LogisticRegression` warnings in scikit-learn 1.8.0.
When I use `LogisticRegression(penalty=None)`, I get a `FutureWarning` advising me to u... | 32,927 | [
0.006873808801174164,
0.05926556512713432,
0.04481958970427513,
-0.008841360919177532,
0.08840090036392212,
0.019288444891572,
0.015847602859139442,
0.02406025119125843,
0.041782572865486145,
0.008517214097082615,
0.07963430881500244,
0.04248065873980522,
-0.010747276246547699,
-0.04638900... |
https://github.com/scikit-learn/scikit-learn/issues/32927 | [
"Bug"
] | `LogisticRegression`: Conflicting warnings when following deprecation advice for `penalty=None` (sklearn 1.8.0)
### Describe the bug
I am encountering a catch-22 situation with `LogisticRegression` warnings in scikit-learn 1.8.0.
When I use `LogisticRegression(penalty=None)`, I get a `FutureWarning` advising me to u... | 32,927 | [
0.006873808801174164,
0.05926556512713432,
0.04481958970427513,
-0.008841360919177532,
0.08840090036392212,
0.019288444891572,
0.015847602859139442,
0.02406025119125843,
0.041782572865486145,
0.008517214097082615,
0.07963430881500244,
0.04248065873980522,
-0.010747276246547699,
-0.04638900... |
https://github.com/scikit-learn/scikit-learn/issues/32924 | [
"Array API"
] | Array API spec for `unique_values` does not specify order of unique elements
Noticed when working on #32923
I don't think we need to do anything about this, (and indeed all our tests pass), I just wanted to document this for posterity, in case we encounter any problems later.
Array API spec for `unique_values` does ... | 32,924 | [
-0.001307550584897399,
0.014551691710948944,
0.02986299991607666,
0.01664011739194393,
0.04767413064837456,
0.03330961987376213,
0.03766166791319847,
-0.025579657405614853,
-0.042221613228321075,
-0.0259084589779377,
0.06852106750011444,
0.013387245126068592,
0.037228308618068695,
0.017949... |
https://github.com/scikit-learn/scikit-learn/issues/32924 | [
"Array API"
] | Array API spec for `unique_values` does not specify order of unique elements
Noticed when working on #32923
I don't think we need to do anything about this, (and indeed all our tests pass), I just wanted to document this for posterity, in case we encounter any problems later.
Array API spec for `unique_values` does ... | 32,924 | [
-0.0025962169747799635,
0.011635714210569859,
0.030089763924479485,
0.01586185395717621,
0.0481143593788147,
0.031586211174726486,
0.035778798162937164,
-0.024390429258346558,
-0.041512392461299896,
-0.02716108411550522,
0.06826253235340118,
0.011015568859875202,
0.03635166957974434,
0.014... |
https://github.com/scikit-learn/scikit-learn/issues/32924 | [
"Array API"
] | Array API spec for `unique_values` does not specify order of unique elements
Noticed when working on #32923
I don't think we need to do anything about this, (and indeed all our tests pass), I just wanted to document this for posterity, in case we encounter any problems later.
Array API spec for `unique_values` does ... | 32,924 | [
0.0007541203522123396,
0.01431330293416977,
0.030033987015485764,
0.015298311598598957,
0.04878250136971474,
0.03475863113999367,
0.040346741676330566,
-0.026119498535990715,
-0.04065544903278351,
-0.029000820592045784,
0.06252256035804749,
0.01673295721411705,
0.040528200566768646,
0.0118... |
https://github.com/scikit-learn/scikit-learn/issues/32924 | [
"Array API"
] | Array API spec for `unique_values` does not specify order of unique elements
Noticed when working on #32923
I don't think we need to do anything about this, (and indeed all our tests pass), I just wanted to document this for posterity, in case we encounter any problems later.
Array API spec for `unique_values` does ... | 32,924 | [
-0.0012619916815310717,
0.012443941086530685,
0.030019091442227364,
0.018253935500979424,
0.04868854954838753,
0.021692320704460144,
0.0321568064391613,
-0.03086700662970543,
-0.04543181508779526,
-0.030093122273683548,
0.06732548773288727,
0.01375323161482811,
0.04132719337940216,
0.01609... |
https://github.com/scikit-learn/scikit-learn/issues/32924 | [
"Array API"
] | Array API spec for `unique_values` does not specify order of unique elements
Noticed when working on #32923
I don't think we need to do anything about this, (and indeed all our tests pass), I just wanted to document this for posterity, in case we encounter any problems later.
Array API spec for `unique_values` does ... | 32,924 | [
-0.0008951187483035028,
0.01817360147833824,
0.029521826654672623,
0.01937095634639263,
0.05222180485725403,
0.0313466414809227,
0.03709658235311508,
-0.02258150279521942,
-0.04162045568227768,
-0.025808366015553474,
0.0656711533665657,
0.013334769755601883,
0.03611478582024574,
0.01951085... |
https://github.com/scikit-learn/scikit-learn/issues/32924 | [
"Array API"
] | Array API spec for `unique_values` does not specify order of unique elements
Noticed when working on #32923
I don't think we need to do anything about this, (and indeed all our tests pass), I just wanted to document this for posterity, in case we encounter any problems later.
Array API spec for `unique_values` does ... | 32,924 | [
-0.0028980292845517397,
0.015084892511367798,
0.03054303117096424,
0.016319332644343376,
0.04581940919160843,
0.0309783685952425,
0.03863712027668953,
-0.02546515315771103,
-0.04227733984589577,
-0.02664504572749138,
0.06869528442621231,
0.011487689800560474,
0.03777601942420006,
0.0190028... |
https://github.com/scikit-learn/scikit-learn/issues/32924 | [
"Array API"
] | Array API spec for `unique_values` does not specify order of unique elements
Noticed when working on #32923
I don't think we need to do anything about this, (and indeed all our tests pass), I just wanted to document this for posterity, in case we encounter any problems later.
Array API spec for `unique_values` does ... | 32,924 | [
-0.0030800006352365017,
0.020097071304917336,
0.02838585525751114,
0.012441174127161503,
0.050841428339481354,
0.033040180802345276,
0.04136314615607262,
-0.022068234160542488,
-0.04149635136127472,
-0.025188416242599487,
0.06950614601373672,
0.013335887342691422,
0.032391536980867386,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32924 | [
"Array API"
] | Array API spec for `unique_values` does not specify order of unique elements
Noticed when working on #32923
I don't think we need to do anything about this, (and indeed all our tests pass), I just wanted to document this for posterity, in case we encounter any problems later.
Array API spec for `unique_values` does ... | 32,924 | [
-0.005156501196324825,
0.00838235393166542,
0.02460169792175293,
0.013298805803060532,
0.04243197664618492,
0.03739098832011223,
0.03884045407176018,
-0.02190963365137577,
-0.031100556254386902,
-0.02509109303355217,
0.06356291472911835,
0.012772394344210625,
0.0370757058262825,
0.02480080... |
https://github.com/scikit-learn/scikit-learn/issues/32919 | [
"Bug",
"Needs Triage"
] | Kernel crash on BayesianGaussianMixture
### Describe the bug
I learn BayesianGaussianMixture right now and get kernel crash on sklearn documentation example.
The error is 100% reproducible and wont go away after OS restrat, kernel restrat. I even try to read Goodfellow, no effect.
Initially i got the error on versio... | 32,919 | [
-0.0438179075717926,
0.0032727629877626896,
-0.0016806103521957994,
-0.008264406584203243,
0.04090908542275429,
0.006393284071236849,
-0.016577741131186485,
0.05346925929188728,
0.025162294507026672,
-0.02007816545665264,
0.046080026775598526,
0.05108686909079552,
0.015329317189753056,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32919 | [
"Bug",
"Needs Triage"
] | Kernel crash on BayesianGaussianMixture
### Describe the bug
I learn BayesianGaussianMixture right now and get kernel crash on sklearn documentation example.
The error is 100% reproducible and wont go away after OS restrat, kernel restrat. I even try to read Goodfellow, no effect.
Initially i got the error on versio... | 32,919 | [
-0.0438179075717926,
0.0032727629877626896,
-0.0016806103521957994,
-0.008264406584203243,
0.04090908542275429,
0.006393284071236849,
-0.016577741131186485,
0.05346925929188728,
0.025162294507026672,
-0.02007816545665264,
0.046080026775598526,
0.05108686909079552,
0.015329317189753056,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32919 | [
"Bug",
"Needs Triage"
] | Kernel crash on BayesianGaussianMixture
### Describe the bug
I learn BayesianGaussianMixture right now and get kernel crash on sklearn documentation example.
The error is 100% reproducible and wont go away after OS restrat, kernel restrat. I even try to read Goodfellow, no effect.
Initially i got the error on versio... | 32,919 | [
-0.0438179075717926,
0.0032727629877626896,
-0.0016806103521957994,
-0.008264406584203243,
0.04090908542275429,
0.006393284071236849,
-0.016577741131186485,
0.05346925929188728,
0.025162294507026672,
-0.02007816545665264,
0.046080026775598526,
0.05108686909079552,
0.015329317189753056,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32919 | [
"Bug",
"Needs Triage"
] | Kernel crash on BayesianGaussianMixture
### Describe the bug
I learn BayesianGaussianMixture right now and get kernel crash on sklearn documentation example.
The error is 100% reproducible and wont go away after OS restrat, kernel restrat. I even try to read Goodfellow, no effect.
Initially i got the error on versio... | 32,919 | [
-0.0438179075717926,
0.0032727629877626896,
-0.0016806103521957994,
-0.008264406584203243,
0.04090908542275429,
0.006393284071236849,
-0.016577741131186485,
0.05346925929188728,
0.025162294507026672,
-0.02007816545665264,
0.046080026775598526,
0.05108686909079552,
0.015329317189753056,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32915 | [
"Documentation"
] | [for discussion]: adding link to Contributing Guide to top menu
### Describe the issue linked to the documentation
This issue is a **discussion** item.
## Questions:
1. Can we add a link to "Contributing" to the top level menu? It seems a bit hidden, and the questions on contributing come up quite often.
- Con... | 32,915 | [
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https://github.com/scikit-learn/scikit-learn/issues/32915 | [
"Documentation"
] | [for discussion]: adding link to Contributing Guide to top menu
### Describe the issue linked to the documentation
This issue is a **discussion** item.
## Questions:
1. Can we add a link to "Contributing" to the top level menu? It seems a bit hidden, and the questions on contributing come up quite often.
- Con... | 32,915 | [
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https://github.com/scikit-learn/scikit-learn/issues/32915 | [
"Documentation"
] | [for discussion]: adding link to Contributing Guide to top menu
### Describe the issue linked to the documentation
This issue is a **discussion** item.
## Questions:
1. Can we add a link to "Contributing" to the top level menu? It seems a bit hidden, and the questions on contributing come up quite often.
- Con... | 32,915 | [
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https://github.com/scikit-learn/scikit-learn/issues/32915 | [
"Documentation"
] | [for discussion]: adding link to Contributing Guide to top menu
### Describe the issue linked to the documentation
This issue is a **discussion** item.
## Questions:
1. Can we add a link to "Contributing" to the top level menu? It seems a bit hidden, and the questions on contributing come up quite often.
- Con... | 32,915 | [
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https://github.com/scikit-learn/scikit-learn/issues/32915 | [
"Documentation"
] | [for discussion]: adding link to Contributing Guide to top menu
### Describe the issue linked to the documentation
This issue is a **discussion** item.
## Questions:
1. Can we add a link to "Contributing" to the top level menu? It seems a bit hidden, and the questions on contributing come up quite often.
- Con... | 32,915 | [
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https://github.com/scikit-learn/scikit-learn/issues/32914 | [
"New Feature",
"Needs Triage"
] | Addressed: FastICA logcosh bottleneck
### Describe the workflow you want to enable
For: sklearn/decomposition/_fastica.py
Hello,
Firstly thank you for the amazing library :D
I see in the FastICA there was a bottleneck that was messing a lot with my run time, so i optimized it and compared my implementation with th... | 32,914 | [
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0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32914 | [
"New Feature",
"Needs Triage"
] | Addressed: FastICA logcosh bottleneck
### Describe the workflow you want to enable
For: sklearn/decomposition/_fastica.py
Hello,
Firstly thank you for the amazing library :D
I see in the FastICA there was a bottleneck that was messing a lot with my run time, so i optimized it and compared my implementation with th... | 32,914 | [
-0.011527368798851967,
0.030680900439620018,
0.03712945803999901,
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0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32914 | [
"New Feature",
"Needs Triage"
] | Addressed: FastICA logcosh bottleneck
### Describe the workflow you want to enable
For: sklearn/decomposition/_fastica.py
Hello,
Firstly thank you for the amazing library :D
I see in the FastICA there was a bottleneck that was messing a lot with my run time, so i optimized it and compared my implementation with th... | 32,914 | [
-0.011527368798851967,
0.030680900439620018,
0.03712945803999901,
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0.02834862656891346,
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0.0030740874353796244,
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-0.06483162194490433,
-0.0135176507756114,
-0.02118898183107376,
-0.02008195035159588,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32914 | [
"New Feature",
"Needs Triage"
] | Addressed: FastICA logcosh bottleneck
### Describe the workflow you want to enable
For: sklearn/decomposition/_fastica.py
Hello,
Firstly thank you for the amazing library :D
I see in the FastICA there was a bottleneck that was messing a lot with my run time, so i optimized it and compared my implementation with th... | 32,914 | [
-0.011527368798851967,
0.030680900439620018,
0.03712945803999901,
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0.02834862656891346,
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0.0030740874353796244,
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-0.06483162194490433,
-0.0135176507756114,
-0.02118898183107376,
-0.02008195035159588,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32914 | [
"New Feature",
"Needs Triage"
] | Addressed: FastICA logcosh bottleneck
### Describe the workflow you want to enable
For: sklearn/decomposition/_fastica.py
Hello,
Firstly thank you for the amazing library :D
I see in the FastICA there was a bottleneck that was messing a lot with my run time, so i optimized it and compared my implementation with th... | 32,914 | [
-0.011527368798851967,
0.030680900439620018,
0.03712945803999901,
-0.03375076875090599,
0.02834862656891346,
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0.0030740874353796244,
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0.0... |
https://github.com/scikit-learn/scikit-learn/issues/32910 | [
"Bug",
"Needs Triage"
] | bug: Nested Pipeline is not fitted (sklearn 1.8)
EDIT: The specific issue described here is actually caused by skrub, and solved in https://github.com/skrub-data/skrub/pull/1813.
However, this poses a more general question on how easy it is to abide by sklearn's conventions: skip directly to [this comment](https://git... | 32,910 | [
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0.014912722632288933,
0.03525058... |
https://github.com/scikit-learn/scikit-learn/issues/32910 | [
"Bug",
"Needs Triage"
] | bug: Nested Pipeline is not fitted (sklearn 1.8)
EDIT: The specific issue described here is actually caused by skrub, and solved in https://github.com/skrub-data/skrub/pull/1813.
However, this poses a more general question on how easy it is to abide by sklearn's conventions: skip directly to [this comment](https://git... | 32,910 | [
-0.02928832173347473,
0.10328248143196106,
0.008403494022786617,
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0.06098496913909912,
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0.042155671864748,
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0.007643809076398611,
0.04948941245675087,
0.06540796905755997,
0.014912722632288933,
0.03525058... |
https://github.com/scikit-learn/scikit-learn/issues/32910 | [
"Bug",
"Needs Triage"
] | bug: Nested Pipeline is not fitted (sklearn 1.8)
EDIT: The specific issue described here is actually caused by skrub, and solved in https://github.com/skrub-data/skrub/pull/1813.
However, this poses a more general question on how easy it is to abide by sklearn's conventions: skip directly to [this comment](https://git... | 32,910 | [
-0.02928832173347473,
0.10328248143196106,
0.008403494022786617,
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0.06098496913909912,
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0.06922031193971634,
0.042155671864748,
0.03298599645495415,
0.007643809076398611,
0.04948941245675087,
0.06540796905755997,
0.014912722632288933,
0.03525058... |
https://github.com/scikit-learn/scikit-learn/issues/32910 | [
"Bug",
"Needs Triage"
] | bug: Nested Pipeline is not fitted (sklearn 1.8)
EDIT: The specific issue described here is actually caused by skrub, and solved in https://github.com/skrub-data/skrub/pull/1813.
However, this poses a more general question on how easy it is to abide by sklearn's conventions: skip directly to [this comment](https://git... | 32,910 | [
-0.02928832173347473,
0.10328248143196106,
0.008403494022786617,
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0.06098496913909912,
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0.06922031193971634,
0.042155671864748,
0.03298599645495415,
0.007643809076398611,
0.04948941245675087,
0.06540796905755997,
0.014912722632288933,
0.03525058... |
https://github.com/scikit-learn/scikit-learn/issues/32910 | [
"Bug",
"Needs Triage"
] | bug: Nested Pipeline is not fitted (sklearn 1.8)
EDIT: The specific issue described here is actually caused by skrub, and solved in https://github.com/skrub-data/skrub/pull/1813.
However, this poses a more general question on how easy it is to abide by sklearn's conventions: skip directly to [this comment](https://git... | 32,910 | [
-0.02928832173347473,
0.10328248143196106,
0.008403494022786617,
-0.026602445170283318,
0.06098496913909912,
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0.06922031193971634,
0.042155671864748,
0.03298599645495415,
0.007643809076398611,
0.04948941245675087,
0.06540796905755997,
0.014912722632288933,
0.03525058... |
https://github.com/scikit-learn/scikit-learn/issues/32910 | [
"Bug",
"Needs Triage"
] | bug: Nested Pipeline is not fitted (sklearn 1.8)
EDIT: The specific issue described here is actually caused by skrub, and solved in https://github.com/skrub-data/skrub/pull/1813.
However, this poses a more general question on how easy it is to abide by sklearn's conventions: skip directly to [this comment](https://git... | 32,910 | [
-0.02928832173347473,
0.10328248143196106,
0.008403494022786617,
-0.026602445170283318,
0.06098496913909912,
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0.06922031193971634,
0.042155671864748,
0.03298599645495415,
0.007643809076398611,
0.04948941245675087,
0.06540796905755997,
0.014912722632288933,
0.03525058... |
https://github.com/scikit-learn/scikit-learn/issues/32910 | [
"Bug",
"Needs Triage"
] | bug: Nested Pipeline is not fitted (sklearn 1.8)
EDIT: The specific issue described here is actually caused by skrub, and solved in https://github.com/skrub-data/skrub/pull/1813.
However, this poses a more general question on how easy it is to abide by sklearn's conventions: skip directly to [this comment](https://git... | 32,910 | [
-0.02928832173347473,
0.10328248143196106,
0.008403494022786617,
-0.026602445170283318,
0.06098496913909912,
-0.0034954871516674757,
0.06922031193971634,
0.042155671864748,
0.03298599645495415,
0.007643809076398611,
0.04948941245675087,
0.06540796905755997,
0.014912722632288933,
0.03525058... |
https://github.com/scikit-learn/scikit-learn/issues/32910 | [
"Bug",
"Needs Triage"
] | bug: Nested Pipeline is not fitted (sklearn 1.8)
EDIT: The specific issue described here is actually caused by skrub, and solved in https://github.com/skrub-data/skrub/pull/1813.
However, this poses a more general question on how easy it is to abide by sklearn's conventions: skip directly to [this comment](https://git... | 32,910 | [
-0.02928832173347473,
0.10328248143196106,
0.008403494022786617,
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0.06098496913909912,
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0.06922031193971634,
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0.007643809076398611,
0.04948941245675087,
0.06540796905755997,
0.014912722632288933,
0.03525058... |
https://github.com/scikit-learn/scikit-learn/issues/32910 | [
"Bug",
"Needs Triage"
] | bug: Nested Pipeline is not fitted (sklearn 1.8)
EDIT: The specific issue described here is actually caused by skrub, and solved in https://github.com/skrub-data/skrub/pull/1813.
However, this poses a more general question on how easy it is to abide by sklearn's conventions: skip directly to [this comment](https://git... | 32,910 | [
-0.02928832173347473,
0.10328248143196106,
0.008403494022786617,
-0.026602445170283318,
0.06098496913909912,
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0.06922031193971634,
0.042155671864748,
0.03298599645495415,
0.007643809076398611,
0.04948941245675087,
0.06540796905755997,
0.014912722632288933,
0.03525058... |
https://github.com/scikit-learn/scikit-learn/issues/32910 | [
"Bug",
"Needs Triage"
] | bug: Nested Pipeline is not fitted (sklearn 1.8)
EDIT: The specific issue described here is actually caused by skrub, and solved in https://github.com/skrub-data/skrub/pull/1813.
However, this poses a more general question on how easy it is to abide by sklearn's conventions: skip directly to [this comment](https://git... | 32,910 | [
-0.02928832173347473,
0.10328248143196106,
0.008403494022786617,
-0.026602445170283318,
0.06098496913909912,
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0.06922031193971634,
0.042155671864748,
0.03298599645495415,
0.007643809076398611,
0.04948941245675087,
0.06540796905755997,
0.014912722632288933,
0.03525058... |
https://github.com/scikit-learn/scikit-learn/issues/32910 | [
"Bug",
"Needs Triage"
] | bug: Nested Pipeline is not fitted (sklearn 1.8)
EDIT: The specific issue described here is actually caused by skrub, and solved in https://github.com/skrub-data/skrub/pull/1813.
However, this poses a more general question on how easy it is to abide by sklearn's conventions: skip directly to [this comment](https://git... | 32,910 | [
-0.02928832173347473,
0.10328248143196106,
0.008403494022786617,
-0.026602445170283318,
0.06098496913909912,
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0.007643809076398611,
0.04948941245675087,
0.06540796905755997,
0.014912722632288933,
0.03525058... |
https://github.com/scikit-learn/scikit-learn/issues/32908 | [
"Bug",
"Needs Reproducible Code",
"Needs Triage"
] | Call to estimator.score() in RANSAC even if the produced input data set is too small - fix proposed
### Describe the bug
By sampling radomly from a distribution of x,y values, the RANSAC algorithm tries to find the line which describes best most of the data (while ignoring outliers). For deciding, how well a certain ... | 32,908 | [
-0.01052760984748602,
0.004222351126372814,
0.0313519686460495,
0.003257312346249819,
0.09391093999147415,
0.018175611272454262,
0.0011085157748311758,
0.043925851583480835,
0.05089614912867546,
0.035465024411678314,
0.05669824779033661,
0.022565532475709915,
0.01199099887162447,
0.0171996... |
https://github.com/scikit-learn/scikit-learn/issues/32908 | [
"Bug",
"Needs Reproducible Code",
"Needs Triage"
] | Call to estimator.score() in RANSAC even if the produced input data set is too small - fix proposed
### Describe the bug
By sampling radomly from a distribution of x,y values, the RANSAC algorithm tries to find the line which describes best most of the data (while ignoring outliers). For deciding, how well a certain ... | 32,908 | [
-0.01052760984748602,
0.004222351126372814,
0.0313519686460495,
0.003257312346249819,
0.09391093999147415,
0.018175611272454262,
0.0011085157748311758,
0.043925851583480835,
0.05089614912867546,
0.035465024411678314,
0.05669824779033661,
0.022565532475709915,
0.01199099887162447,
0.0171996... |
https://github.com/scikit-learn/scikit-learn/issues/32908 | [
"Bug",
"Needs Reproducible Code",
"Needs Triage"
] | Call to estimator.score() in RANSAC even if the produced input data set is too small - fix proposed
### Describe the bug
By sampling radomly from a distribution of x,y values, the RANSAC algorithm tries to find the line which describes best most of the data (while ignoring outliers). For deciding, how well a certain ... | 32,908 | [
-0.01052760984748602,
0.004222351126372814,
0.0313519686460495,
0.003257312346249819,
0.09391093999147415,
0.018175611272454262,
0.0011085157748311758,
0.043925851583480835,
0.05089614912867546,
0.035465024411678314,
0.05669824779033661,
0.022565532475709915,
0.01199099887162447,
0.0171996... |
https://github.com/scikit-learn/scikit-learn/issues/32908 | [
"Bug",
"Needs Reproducible Code",
"Needs Triage"
] | Call to estimator.score() in RANSAC even if the produced input data set is too small - fix proposed
### Describe the bug
By sampling radomly from a distribution of x,y values, the RANSAC algorithm tries to find the line which describes best most of the data (while ignoring outliers). For deciding, how well a certain ... | 32,908 | [
-0.01052760984748602,
0.004222351126372814,
0.0313519686460495,
0.003257312346249819,
0.09391093999147415,
0.018175611272454262,
0.0011085157748311758,
0.043925851583480835,
0.05089614912867546,
0.035465024411678314,
0.05669824779033661,
0.022565532475709915,
0.01199099887162447,
0.0171996... |
https://github.com/scikit-learn/scikit-learn/issues/32908 | [
"Bug",
"Needs Reproducible Code",
"Needs Triage"
] | Call to estimator.score() in RANSAC even if the produced input data set is too small - fix proposed
### Describe the bug
By sampling radomly from a distribution of x,y values, the RANSAC algorithm tries to find the line which describes best most of the data (while ignoring outliers). For deciding, how well a certain ... | 32,908 | [
-0.01052760984748602,
0.004222351126372814,
0.0313519686460495,
0.003257312346249819,
0.09391093999147415,
0.018175611272454262,
0.0011085157748311758,
0.043925851583480835,
0.05089614912867546,
0.035465024411678314,
0.05669824779033661,
0.022565532475709915,
0.01199099887162447,
0.0171996... |
https://github.com/scikit-learn/scikit-learn/issues/32908 | [
"Bug",
"Needs Reproducible Code",
"Needs Triage"
] | Call to estimator.score() in RANSAC even if the produced input data set is too small - fix proposed
### Describe the bug
By sampling radomly from a distribution of x,y values, the RANSAC algorithm tries to find the line which describes best most of the data (while ignoring outliers). For deciding, how well a certain ... | 32,908 | [
-0.01052760984748602,
0.004222351126372814,
0.0313519686460495,
0.003257312346249819,
0.09391093999147415,
0.018175611272454262,
0.0011085157748311758,
0.043925851583480835,
0.05089614912867546,
0.035465024411678314,
0.05669824779033661,
0.022565532475709915,
0.01199099887162447,
0.0171996... |
https://github.com/scikit-learn/scikit-learn/issues/32908 | [
"Bug",
"Needs Reproducible Code",
"Needs Triage"
] | Call to estimator.score() in RANSAC even if the produced input data set is too small - fix proposed
### Describe the bug
By sampling radomly from a distribution of x,y values, the RANSAC algorithm tries to find the line which describes best most of the data (while ignoring outliers). For deciding, how well a certain ... | 32,908 | [
-0.01052760984748602,
0.004222351126372814,
0.0313519686460495,
0.003257312346249819,
0.09391093999147415,
0.018175611272454262,
0.0011085157748311758,
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0.035465024411678314,
0.05669824779033661,
0.022565532475709915,
0.01199099887162447,
0.0171996... |
https://github.com/scikit-learn/scikit-learn/issues/32898 | [
"Bug",
"Needs Triage"
] | inconsistent warnings for ElasticNetCV and LassoCV
### Describe the bug
ElasticNetCV and LassoCV generate warnings when y is a (n,1) vector but doesn't when y is a (n,) vector. This behavior is not in LinearRegression or RidgeCV. Can they be made consistent to avoid confusion in applications?
### Steps/Code to Repro... | 32,898 | [
0.03320303186774254,
-0.013031907379627228,
0.022930460050702095,
0.03777141496539116,
0.11968795955181122,
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0.037154920399188995,
0.011709059588611126,
0.029609927907586098,
0.03139481693506241,
0.06985554844141006,
0.027822524309158325,
0.019873639568686485,
-0.0327... |
https://github.com/scikit-learn/scikit-learn/issues/32898 | [
"Bug",
"Needs Triage"
] | inconsistent warnings for ElasticNetCV and LassoCV
### Describe the bug
ElasticNetCV and LassoCV generate warnings when y is a (n,1) vector but doesn't when y is a (n,) vector. This behavior is not in LinearRegression or RidgeCV. Can they be made consistent to avoid confusion in applications?
### Steps/Code to Repro... | 32,898 | [
0.03320303186774254,
-0.013031907379627228,
0.022930460050702095,
0.03777141496539116,
0.11968795955181122,
-0.007895038463175297,
0.037154920399188995,
0.011709059588611126,
0.029609927907586098,
0.03139481693506241,
0.06985554844141006,
0.027822524309158325,
0.019873639568686485,
-0.0327... |
https://github.com/scikit-learn/scikit-learn/issues/32898 | [
"Bug",
"Needs Triage"
] | inconsistent warnings for ElasticNetCV and LassoCV
### Describe the bug
ElasticNetCV and LassoCV generate warnings when y is a (n,1) vector but doesn't when y is a (n,) vector. This behavior is not in LinearRegression or RidgeCV. Can they be made consistent to avoid confusion in applications?
### Steps/Code to Repro... | 32,898 | [
0.03320303186774254,
-0.013031907379627228,
0.022930460050702095,
0.03777141496539116,
0.11968795955181122,
-0.007895038463175297,
0.037154920399188995,
0.011709059588611126,
0.029609927907586098,
0.03139481693506241,
0.06985554844141006,
0.027822524309158325,
0.019873639568686485,
-0.0327... |
https://github.com/scikit-learn/scikit-learn/issues/32898 | [
"Bug",
"Needs Triage"
] | inconsistent warnings for ElasticNetCV and LassoCV
### Describe the bug
ElasticNetCV and LassoCV generate warnings when y is a (n,1) vector but doesn't when y is a (n,) vector. This behavior is not in LinearRegression or RidgeCV. Can they be made consistent to avoid confusion in applications?
### Steps/Code to Repro... | 32,898 | [
0.03320303186774254,
-0.013031907379627228,
0.022930460050702095,
0.03777141496539116,
0.11968795955181122,
-0.007895038463175297,
0.037154920399188995,
0.011709059588611126,
0.029609927907586098,
0.03139481693506241,
0.06985554844141006,
0.027822524309158325,
0.019873639568686485,
-0.0327... |
https://github.com/scikit-learn/scikit-learn/issues/32891 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_Nightly.pylatest_pip_scipy_dev (last failure: Dec 14, 2025) ⚠️
**CI is still failing on [Linux_Nightly.pylatest_pip_scipy_dev](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=83442&view=logs&j=dfe99b15-50db-5d7b-b1e9-4105c42527cf)** (Dec 14, 2025)
- test_pandas_copy_on_writ... | 32,891 | [
0.025161024183034897,
0.04809069260954857,
-0.018618222326040268,
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0.029606271535158157,
0.011106111109256744,
0.03966907784342766,
0.05835177004337311,
0.002365854335948825,
-0.004574318882077932,
0.05001821368932724,
0.025729089975357056,
-0.006016325671225786,
0.07... |
https://github.com/scikit-learn/scikit-learn/issues/32891 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_Nightly.pylatest_pip_scipy_dev (last failure: Dec 14, 2025) ⚠️
**CI is still failing on [Linux_Nightly.pylatest_pip_scipy_dev](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=83442&view=logs&j=dfe99b15-50db-5d7b-b1e9-4105c42527cf)** (Dec 14, 2025)
- test_pandas_copy_on_writ... | 32,891 | [
0.022743798792362213,
0.03208643198013306,
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0.02160147950053215,
0.029291152954101562,
0.06032849848270416,
0.009078209288418293,
0.004527402576059103,
0.03991273045539856,
0.01733723282814026,
-0.001888227998279035,
0.069461591... |
https://github.com/scikit-learn/scikit-learn/issues/32886 | [
"RFC",
"Array API"
] | RFC Add gallery example with Array API support
Mentioned somewhere in the release activity the closest I could find was https://github.com/scikit-learn/scikit-learn/pull/32809#discussion_r2587809537. It would probably be doable to add pytorch-cpu in the doc lock-file and add an example with a somewhat non trivial pipe... | 32,886 | [
-0.0006389739573933184,
0.028814485296607018,
-0.02248498797416687,
-0.005359344650059938,
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0.014936504885554314,
0.11793409287929535,
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0.04913431406021118,
-0.03904204070568085,
0.015822140499949455,
0.03602083399891853,
-0.012553855776786804,
-... |
https://github.com/scikit-learn/scikit-learn/issues/32872 | [
"Bug",
"module:inspection"
] | `DecisionBoundaryDisplay` with `response_method="predict"` has inconsistent handling for the colormap in the multiclass case
### Describe the bug
This issue was discovered while reviewing #32867, but since it's not directly related, let's open a dedicated issue to avoid derailing the original discussion.
As can be ... | 32,872 | [
0.03664347529411316,
0.030627798289060593,
0.01615993306040764,
0.03398316726088524,
0.040818262845277786,
-0.06314370781183243,
0.00939030759036541,
0.03751359134912491,
-0.008010688237845898,
-0.02486354671418667,
-0.00530165433883667,
0.044624850153923035,
0.019910505041480064,
-0.00727... |
https://github.com/scikit-learn/scikit-learn/issues/32872 | [
"Bug",
"module:inspection"
] | `DecisionBoundaryDisplay` with `response_method="predict"` has inconsistent handling for the colormap in the multiclass case
### Describe the bug
This issue was discovered while reviewing #32867, but since it's not directly related, let's open a dedicated issue to avoid derailing the original discussion.
As can be ... | 32,872 | [
0.03664347529411316,
0.030627798289060593,
0.01615993306040764,
0.03398316726088524,
0.040818262845277786,
-0.06314370781183243,
0.00939030759036541,
0.03751359134912491,
-0.008010688237845898,
-0.02486354671418667,
-0.00530165433883667,
0.044624850153923035,
0.019910505041480064,
-0.00727... |
https://github.com/scikit-learn/scikit-learn/issues/32872 | [
"Bug",
"module:inspection"
] | `DecisionBoundaryDisplay` with `response_method="predict"` has inconsistent handling for the colormap in the multiclass case
### Describe the bug
This issue was discovered while reviewing #32867, but since it's not directly related, let's open a dedicated issue to avoid derailing the original discussion.
As can be ... | 32,872 | [
0.03664347529411316,
0.030627798289060593,
0.01615993306040764,
0.03398316726088524,
0.040818262845277786,
-0.06314370781183243,
0.00939030759036541,
0.03751359134912491,
-0.008010688237845898,
-0.02486354671418667,
-0.00530165433883667,
0.044624850153923035,
0.019910505041480064,
-0.00727... |
https://github.com/scikit-learn/scikit-learn/issues/32872 | [
"Bug",
"module:inspection"
] | `DecisionBoundaryDisplay` with `response_method="predict"` has inconsistent handling for the colormap in the multiclass case
### Describe the bug
This issue was discovered while reviewing #32867, but since it's not directly related, let's open a dedicated issue to avoid derailing the original discussion.
As can be ... | 32,872 | [
0.03664347529411316,
0.030627798289060593,
0.01615993306040764,
0.03398316726088524,
0.040818262845277786,
-0.06314370781183243,
0.00939030759036541,
0.03751359134912491,
-0.008010688237845898,
-0.02486354671418667,
-0.00530165433883667,
0.044624850153923035,
0.019910505041480064,
-0.00727... |
https://github.com/scikit-learn/scikit-learn/issues/32872 | [
"Bug",
"module:inspection"
] | `DecisionBoundaryDisplay` with `response_method="predict"` has inconsistent handling for the colormap in the multiclass case
### Describe the bug
This issue was discovered while reviewing #32867, but since it's not directly related, let's open a dedicated issue to avoid derailing the original discussion.
As can be ... | 32,872 | [
0.03664347529411316,
0.030627798289060593,
0.01615993306040764,
0.03398316726088524,
0.040818262845277786,
-0.06314370781183243,
0.00939030759036541,
0.03751359134912491,
-0.008010688237845898,
-0.02486354671418667,
-0.00530165433883667,
0.044624850153923035,
0.019910505041480064,
-0.00727... |
https://github.com/scikit-learn/scikit-learn/issues/32872 | [
"Bug",
"module:inspection"
] | `DecisionBoundaryDisplay` with `response_method="predict"` has inconsistent handling for the colormap in the multiclass case
### Describe the bug
This issue was discovered while reviewing #32867, but since it's not directly related, let's open a dedicated issue to avoid derailing the original discussion.
As can be ... | 32,872 | [
0.03664347529411316,
0.030627798289060593,
0.01615993306040764,
0.03398316726088524,
0.040818262845277786,
-0.06314370781183243,
0.00939030759036541,
0.03751359134912491,
-0.008010688237845898,
-0.02486354671418667,
-0.00530165433883667,
0.044624850153923035,
0.019910505041480064,
-0.00727... |
https://github.com/scikit-learn/scikit-learn/issues/32872 | [
"Bug",
"module:inspection"
] | `DecisionBoundaryDisplay` with `response_method="predict"` has inconsistent handling for the colormap in the multiclass case
### Describe the bug
This issue was discovered while reviewing #32867, but since it's not directly related, let's open a dedicated issue to avoid derailing the original discussion.
As can be ... | 32,872 | [
0.03664347529411316,
0.030627798289060593,
0.01615993306040764,
0.03398316726088524,
0.040818262845277786,
-0.06314370781183243,
0.00939030759036541,
0.03751359134912491,
-0.008010688237845898,
-0.02486354671418667,
-0.00530165433883667,
0.044624850153923035,
0.019910505041480064,
-0.00727... |
https://github.com/scikit-learn/scikit-learn/issues/32872 | [
"Bug",
"module:inspection"
] | `DecisionBoundaryDisplay` with `response_method="predict"` has inconsistent handling for the colormap in the multiclass case
### Describe the bug
This issue was discovered while reviewing #32867, but since it's not directly related, let's open a dedicated issue to avoid derailing the original discussion.
As can be ... | 32,872 | [
0.03664347529411316,
0.030627798289060593,
0.01615993306040764,
0.03398316726088524,
0.040818262845277786,
-0.06314370781183243,
0.00939030759036541,
0.03751359134912491,
-0.008010688237845898,
-0.02486354671418667,
-0.00530165433883667,
0.044624850153923035,
0.019910505041480064,
-0.00727... |
https://github.com/scikit-learn/scikit-learn/issues/32872 | [
"Bug",
"module:inspection"
] | `DecisionBoundaryDisplay` with `response_method="predict"` has inconsistent handling for the colormap in the multiclass case
### Describe the bug
This issue was discovered while reviewing #32867, but since it's not directly related, let's open a dedicated issue to avoid derailing the original discussion.
As can be ... | 32,872 | [
0.03664347529411316,
0.030627798289060593,
0.01615993306040764,
0.03398316726088524,
0.040818262845277786,
-0.06314370781183243,
0.00939030759036541,
0.03751359134912491,
-0.008010688237845898,
-0.02486354671418667,
-0.00530165433883667,
0.044624850153923035,
0.019910505041480064,
-0.00727... |
https://github.com/scikit-learn/scikit-learn/issues/32872 | [
"Bug",
"module:inspection"
] | `DecisionBoundaryDisplay` with `response_method="predict"` has inconsistent handling for the colormap in the multiclass case
### Describe the bug
This issue was discovered while reviewing #32867, but since it's not directly related, let's open a dedicated issue to avoid derailing the original discussion.
As can be ... | 32,872 | [
0.03664347529411316,
0.030627798289060593,
0.01615993306040764,
0.03398316726088524,
0.040818262845277786,
-0.06314370781183243,
0.00939030759036541,
0.03751359134912491,
-0.008010688237845898,
-0.02486354671418667,
-0.00530165433883667,
0.044624850153923035,
0.019910505041480064,
-0.00727... |
https://github.com/scikit-learn/scikit-learn/issues/32872 | [
"Bug",
"module:inspection"
] | `DecisionBoundaryDisplay` with `response_method="predict"` has inconsistent handling for the colormap in the multiclass case
### Describe the bug
This issue was discovered while reviewing #32867, but since it's not directly related, let's open a dedicated issue to avoid derailing the original discussion.
As can be ... | 32,872 | [
0.03664347529411316,
0.030627798289060593,
0.01615993306040764,
0.03398316726088524,
0.040818262845277786,
-0.06314370781183243,
0.00939030759036541,
0.03751359134912491,
-0.008010688237845898,
-0.02486354671418667,
-0.00530165433883667,
0.044624850153923035,
0.019910505041480064,
-0.00727... |
https://github.com/scikit-learn/scikit-learn/issues/32872 | [
"Bug",
"module:inspection"
] | `DecisionBoundaryDisplay` with `response_method="predict"` has inconsistent handling for the colormap in the multiclass case
### Describe the bug
This issue was discovered while reviewing #32867, but since it's not directly related, let's open a dedicated issue to avoid derailing the original discussion.
As can be ... | 32,872 | [
0.03664347529411316,
0.030627798289060593,
0.01615993306040764,
0.03398316726088524,
0.040818262845277786,
-0.06314370781183243,
0.00939030759036541,
0.03751359134912491,
-0.008010688237845898,
-0.02486354671418667,
-0.00530165433883667,
0.044624850153923035,
0.019910505041480064,
-0.00727... |
https://github.com/scikit-learn/scikit-learn/issues/32872 | [
"Bug",
"module:inspection"
] | `DecisionBoundaryDisplay` with `response_method="predict"` has inconsistent handling for the colormap in the multiclass case
### Describe the bug
This issue was discovered while reviewing #32867, but since it's not directly related, let's open a dedicated issue to avoid derailing the original discussion.
As can be ... | 32,872 | [
0.03664347529411316,
0.030627798289060593,
0.01615993306040764,
0.03398316726088524,
0.040818262845277786,
-0.06314370781183243,
0.00939030759036541,
0.03751359134912491,
-0.008010688237845898,
-0.02486354671418667,
-0.00530165433883667,
0.044624850153923035,
0.019910505041480064,
-0.00727... |
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