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/26598 | [
"Documentation",
"Needs Triage"
] | DOC Link in warning about doc build with Sphinx versions outdated
### Describe the issue linked to the documentation
The link in the warning about sphinx versions at the end of ['Building the documentation'](https://scikit-learn.org/dev/developers/contributing.html#building-the-documentation) is to a Github search ... | 26,598 | [
0.055645622313022614,
-0.008725660853087902,
-0.038239892572164536,
-0.03882757946848869,
-0.0042658657766878605,
0.02720640040934086,
0.008741399273276329,
0.008102240040898323,
-0.011893517337739468,
-0.02428511530160904,
0.04957049712538719,
0.043773431330919266,
0.017270801588892937,
-... |
https://github.com/scikit-learn/scikit-learn/issues/26598 | [
"Documentation",
"Needs Triage"
] | DOC Link in warning about doc build with Sphinx versions outdated
### Describe the issue linked to the documentation
The link in the warning about sphinx versions at the end of ['Building the documentation'](https://scikit-learn.org/dev/developers/contributing.html#building-the-documentation) is to a Github search ... | 26,598 | [
0.06109637767076492,
-0.020181553438305855,
-0.020244406536221504,
-0.030357982963323593,
-0.007680491544306278,
0.04043062403798103,
0.005715417675673962,
0.02042476460337639,
-0.015844881534576416,
-0.03333647921681404,
0.031787995249032974,
0.047930993139743805,
0.02336035668849945,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/26598 | [
"Documentation",
"Needs Triage"
] | DOC Link in warning about doc build with Sphinx versions outdated
### Describe the issue linked to the documentation
The link in the warning about sphinx versions at the end of ['Building the documentation'](https://scikit-learn.org/dev/developers/contributing.html#building-the-documentation) is to a Github search ... | 26,598 | [
0.050180304795503616,
-0.01348420325666666,
-0.0200080294162035,
-0.029303360730409622,
-0.012218104675412178,
0.037585049867630005,
0.00669475132599473,
0.015458899550139904,
-0.020806366577744484,
-0.03218481317162514,
0.041091591119766235,
0.045201100409030914,
0.0242258682847023,
-0.02... |
https://github.com/scikit-learn/scikit-learn/issues/26598 | [
"Documentation",
"Needs Triage"
] | DOC Link in warning about doc build with Sphinx versions outdated
### Describe the issue linked to the documentation
The link in the warning about sphinx versions at the end of ['Building the documentation'](https://scikit-learn.org/dev/developers/contributing.html#building-the-documentation) is to a Github search ... | 26,598 | [
0.059741027653217316,
-0.019434770569205284,
-0.020149949938058853,
-0.030771072953939438,
-0.00906571839004755,
0.03918702155351639,
0.008374201133847237,
0.01926281303167343,
-0.015287832356989384,
-0.03453053906559944,
0.033002495765686035,
0.04828646034002304,
0.025222234427928925,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/26598 | [
"Documentation",
"Needs Triage"
] | DOC Link in warning about doc build with Sphinx versions outdated
### Describe the issue linked to the documentation
The link in the warning about sphinx versions at the end of ['Building the documentation'](https://scikit-learn.org/dev/developers/contributing.html#building-the-documentation) is to a Github search ... | 26,598 | [
0.05898911505937576,
-0.02023386023938656,
-0.022366348654031754,
-0.031179359182715416,
-0.006611234974116087,
0.039135850965976715,
0.006551880389451981,
0.01990544982254505,
-0.016188915818929672,
-0.03254209831357002,
0.03342800959944725,
0.049091994762420654,
0.021837221458554268,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/26598 | [
"Documentation",
"Needs Triage"
] | DOC Link in warning about doc build with Sphinx versions outdated
### Describe the issue linked to the documentation
The link in the warning about sphinx versions at the end of ['Building the documentation'](https://scikit-learn.org/dev/developers/contributing.html#building-the-documentation) is to a Github search ... | 26,598 | [
0.06584569066762924,
-0.011695951223373413,
-0.029374875128269196,
-0.03683781251311302,
-0.004411682020872831,
0.030755825340747833,
0.0041831377893686295,
0.021143952384591103,
-0.016368012875318527,
-0.029114486649632454,
0.030942726880311966,
0.05140681937336922,
0.019069118425250053,
... |
https://github.com/scikit-learn/scikit-learn/issues/26596 | [
"Bug",
"Needs Triage"
] | calibrated classifier cv estimator is not fitted
### Describe the bug
fitted estimator behaves as if it is unfitted if under CalibatedClassifier CV
### Steps/Code to Reproduce
```
from sklearn.calibration import CalibratedClassifierCV
from sklearn.ensemble import GradientBoostingClassifier
from sklearn.dataset... | 26,596 | [
-0.019542554393410683,
-0.05655994266271591,
0.01593621075153351,
-0.009318365715444088,
0.09112386405467987,
-0.021321890875697136,
0.002349481452256441,
0.009719851426780224,
0.038356754928827286,
0.015321873128414154,
0.035645075142383575,
0.05765514448285103,
0.030430685728788376,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/26596 | [
"Bug",
"Needs Triage"
] | calibrated classifier cv estimator is not fitted
### Describe the bug
fitted estimator behaves as if it is unfitted if under CalibatedClassifier CV
### Steps/Code to Reproduce
```
from sklearn.calibration import CalibratedClassifierCV
from sklearn.ensemble import GradientBoostingClassifier
from sklearn.dataset... | 26,596 | [
-0.019542554393410683,
-0.05655994266271591,
0.01593621075153351,
-0.009318365715444088,
0.09112386405467987,
-0.021321890875697136,
0.002349481452256441,
0.009719851426780224,
0.038356754928827286,
0.015321873128414154,
0.035645075142383575,
0.05765514448285103,
0.030430685728788376,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/26596 | [
"Bug",
"Needs Triage"
] | calibrated classifier cv estimator is not fitted
### Describe the bug
fitted estimator behaves as if it is unfitted if under CalibatedClassifier CV
### Steps/Code to Reproduce
```
from sklearn.calibration import CalibratedClassifierCV
from sklearn.ensemble import GradientBoostingClassifier
from sklearn.dataset... | 26,596 | [
-0.019542554393410683,
-0.05655994266271591,
0.01593621075153351,
-0.009318365715444088,
0.09112386405467987,
-0.021321890875697136,
0.002349481452256441,
0.009719851426780224,
0.038356754928827286,
0.015321873128414154,
0.035645075142383575,
0.05765514448285103,
0.030430685728788376,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/26595 | [
"New Feature",
"RFC"
] | UX: Enhance the HTML displays
### Describe the workflow you want to enable
When I interact when non-advanced users a recurrent difficulty for them is finding information and understanding what is going on.
### Describe your proposed solution
I think that we can guide users with better html displays. In general, ... | 26,595 | [
0.005267217289656401,
0.04104406759142876,
0.006759097333997488,
0.012190579436719418,
0.040151581168174744,
-0.015905505046248436,
0.0363149531185627,
0.020192192867398262,
0.06427054107189178,
0.022000636905431747,
-0.023440537974238396,
0.10032474249601364,
-0.0019877152517437935,
0.080... |
https://github.com/scikit-learn/scikit-learn/issues/26595 | [
"New Feature",
"RFC"
] | UX: Enhance the HTML displays
### Describe the workflow you want to enable
When I interact when non-advanced users a recurrent difficulty for them is finding information and understanding what is going on.
### Describe your proposed solution
I think that we can guide users with better html displays. In general, ... | 26,595 | [
0.005267217289656401,
0.04104406759142876,
0.006759097333997488,
0.012190579436719418,
0.040151581168174744,
-0.015905505046248436,
0.0363149531185627,
0.020192192867398262,
0.06427054107189178,
0.022000636905431747,
-0.023440537974238396,
0.10032474249601364,
-0.0019877152517437935,
0.080... |
https://github.com/scikit-learn/scikit-learn/issues/26595 | [
"New Feature",
"RFC"
] | UX: Enhance the HTML displays
### Describe the workflow you want to enable
When I interact when non-advanced users a recurrent difficulty for them is finding information and understanding what is going on.
### Describe your proposed solution
I think that we can guide users with better html displays. In general, ... | 26,595 | [
0.005267217289656401,
0.04104406759142876,
0.006759097333997488,
0.012190579436719418,
0.040151581168174744,
-0.015905505046248436,
0.0363149531185627,
0.020192192867398262,
0.06427054107189178,
0.022000636905431747,
-0.023440537974238396,
0.10032474249601364,
-0.0019877152517437935,
0.080... |
https://github.com/scikit-learn/scikit-learn/issues/26595 | [
"New Feature",
"RFC"
] | UX: Enhance the HTML displays
### Describe the workflow you want to enable
When I interact when non-advanced users a recurrent difficulty for them is finding information and understanding what is going on.
### Describe your proposed solution
I think that we can guide users with better html displays. In general, ... | 26,595 | [
0.005267217289656401,
0.04104406759142876,
0.006759097333997488,
0.012190579436719418,
0.040151581168174744,
-0.015905505046248436,
0.0363149531185627,
0.020192192867398262,
0.06427054107189178,
0.022000636905431747,
-0.023440537974238396,
0.10032474249601364,
-0.0019877152517437935,
0.080... |
https://github.com/scikit-learn/scikit-learn/issues/26590 | [
"Bug"
] | KNNImputer add_indicator fails to persist where missing data had been present in training
### Describe the bug
Hello, I've encountered an issue where the KNNImputer fails to record the fields where there were missing data at the time when `.fit` is called, but not recognised if `.transform` is called on a dense mat... | 26,590 | [
0.028099168092012405,
0.0157766155898571,
0.030122607946395874,
-0.014204203151166439,
0.039214637130498886,
-0.004440700635313988,
0.05698681250214577,
0.031683433800935745,
-0.015065162442624569,
-0.0022574681788682938,
0.04884953051805496,
0.07041201740503311,
0.015498767606914043,
0.01... |
https://github.com/scikit-learn/scikit-learn/issues/26590 | [
"Bug"
] | KNNImputer add_indicator fails to persist where missing data had been present in training
### Describe the bug
Hello, I've encountered an issue where the KNNImputer fails to record the fields where there were missing data at the time when `.fit` is called, but not recognised if `.transform` is called on a dense mat... | 26,590 | [
0.028099168092012405,
0.0157766155898571,
0.030122607946395874,
-0.014204203151166439,
0.039214637130498886,
-0.004440700635313988,
0.05698681250214577,
0.031683433800935745,
-0.015065162442624569,
-0.0022574681788682938,
0.04884953051805496,
0.07041201740503311,
0.015498767606914043,
0.01... |
https://github.com/scikit-learn/scikit-learn/issues/26590 | [
"Bug"
] | KNNImputer add_indicator fails to persist where missing data had been present in training
### Describe the bug
Hello, I've encountered an issue where the KNNImputer fails to record the fields where there were missing data at the time when `.fit` is called, but not recognised if `.transform` is called on a dense mat... | 26,590 | [
0.028099168092012405,
0.0157766155898571,
0.030122607946395874,
-0.014204203151166439,
0.039214637130498886,
-0.004440700635313988,
0.05698681250214577,
0.031683433800935745,
-0.015065162442624569,
-0.0022574681788682938,
0.04884953051805496,
0.07041201740503311,
0.015498767606914043,
0.01... |
https://github.com/scikit-learn/scikit-learn/issues/26590 | [
"Bug"
] | KNNImputer add_indicator fails to persist where missing data had been present in training
### Describe the bug
Hello, I've encountered an issue where the KNNImputer fails to record the fields where there were missing data at the time when `.fit` is called, but not recognised if `.transform` is called on a dense mat... | 26,590 | [
0.028099168092012405,
0.0157766155898571,
0.030122607946395874,
-0.014204203151166439,
0.039214637130498886,
-0.004440700635313988,
0.05698681250214577,
0.031683433800935745,
-0.015065162442624569,
-0.0022574681788682938,
0.04884953051805496,
0.07041201740503311,
0.015498767606914043,
0.01... |
https://github.com/scikit-learn/scikit-learn/issues/26590 | [
"Bug"
] | KNNImputer add_indicator fails to persist where missing data had been present in training
### Describe the bug
Hello, I've encountered an issue where the KNNImputer fails to record the fields where there were missing data at the time when `.fit` is called, but not recognised if `.transform` is called on a dense mat... | 26,590 | [
0.028099168092012405,
0.0157766155898571,
0.030122607946395874,
-0.014204203151166439,
0.039214637130498886,
-0.004440700635313988,
0.05698681250214577,
0.031683433800935745,
-0.015065162442624569,
-0.0022574681788682938,
0.04884953051805496,
0.07041201740503311,
0.015498767606914043,
0.01... |
https://github.com/scikit-learn/scikit-learn/issues/26590 | [
"Bug"
] | KNNImputer add_indicator fails to persist where missing data had been present in training
### Describe the bug
Hello, I've encountered an issue where the KNNImputer fails to record the fields where there were missing data at the time when `.fit` is called, but not recognised if `.transform` is called on a dense mat... | 26,590 | [
0.028099168092012405,
0.0157766155898571,
0.030122607946395874,
-0.014204203151166439,
0.039214637130498886,
-0.004440700635313988,
0.05698681250214577,
0.031683433800935745,
-0.015065162442624569,
-0.0022574681788682938,
0.04884953051805496,
0.07041201740503311,
0.015498767606914043,
0.01... |
https://github.com/scikit-learn/scikit-learn/issues/26586 | [
"New Feature",
"Array API"
] | Array API support for k-nearest neighbors models with the brute force method
This issue is a sibling of a similar issue for k-means: #26585 with similar purpose but likely different constraints.
In particular an efficient implementation of k-NN on the GPU would require:
- `torch.cdist`
- `torch.topk` being disc... | 26,586 | [
0.007362378295511007,
0.056097544729709625,
-0.018267158418893814,
0.02699856646358967,
-0.04502861946821213,
-0.023614730685949326,
0.05461559444665909,
0.03730860352516174,
0.02398112416267395,
-0.02594532072544098,
-0.03323996439576149,
0.03740531578660011,
-0.04331434145569801,
-0.0360... |
https://github.com/scikit-learn/scikit-learn/issues/26586 | [
"New Feature",
"Array API"
] | Array API support for k-nearest neighbors models with the brute force method
This issue is a sibling of a similar issue for k-means: #26585 with similar purpose but likely different constraints.
In particular an efficient implementation of k-NN on the GPU would require:
- `torch.cdist`
- `torch.topk` being disc... | 26,586 | [
0.01282674539834261,
0.024453630670905113,
-0.02941671386361122,
0.02006848342716694,
-0.06364038586616516,
-0.014186442829668522,
0.082316093146801,
0.021692704409360886,
0.03155839815735817,
-0.029523571953177452,
-0.03415321558713913,
0.06086359918117523,
-0.030093533918261528,
-0.06954... |
https://github.com/scikit-learn/scikit-learn/issues/26586 | [
"New Feature",
"Array API"
] | Array API support for k-nearest neighbors models with the brute force method
This issue is a sibling of a similar issue for k-means: #26585 with similar purpose but likely different constraints.
In particular an efficient implementation of k-NN on the GPU would require:
- `torch.cdist`
- `torch.topk` being disc... | 26,586 | [
0.025825584307312965,
0.03506524860858917,
-0.02947443537414074,
0.030090728774666786,
-0.023490404710173607,
-0.00876841600984335,
0.037655945867300034,
0.034287624061107635,
0.03978722542524338,
-0.014419695362448692,
-0.028799941763281822,
0.06083637848496437,
-0.0211515910923481,
-0.06... |
https://github.com/scikit-learn/scikit-learn/issues/26586 | [
"New Feature",
"Array API"
] | Array API support for k-nearest neighbors models with the brute force method
This issue is a sibling of a similar issue for k-means: #26585 with similar purpose but likely different constraints.
In particular an efficient implementation of k-NN on the GPU would require:
- `torch.cdist`
- `torch.topk` being disc... | 26,586 | [
0.018530482426285744,
0.022410018369555473,
-0.03859872743487358,
0.03195199370384216,
-0.024875357747077942,
-0.019329983741044998,
0.08266230672597885,
0.037386540323495865,
0.03430655226111412,
0.00019629117741715163,
-0.027141179889440536,
0.05261584743857384,
-0.014425242319703102,
-0... |
https://github.com/scikit-learn/scikit-learn/issues/26585 | [
"New Feature",
"Array API"
] | Array API support for k-means
This is an early issue to publicly discuss the possibility (or not) to use the Array API (see #22352) for k-means and make it run on GPUs using PyTorch in particular.
@fcharras has already started to run some promising experiments using the raw PyTorch API. Maybe you could link to a gi... | 26,585 | [
-0.033728618174791336,
0.03922823816537857,
-0.017014728859066963,
0.012740629725158215,
0.0018280810909345746,
-0.016369957476854324,
0.08760666847229004,
-0.008627377450466156,
-0.00048121617874130607,
-0.023021133616566658,
-0.009545386768877506,
0.07716953009366989,
-0.017262950539588928... |
https://github.com/scikit-learn/scikit-learn/issues/26585 | [
"New Feature",
"Array API"
] | Array API support for k-means
This is an early issue to publicly discuss the possibility (or not) to use the Array API (see #22352) for k-means and make it run on GPUs using PyTorch in particular.
@fcharras has already started to run some promising experiments using the raw PyTorch API. Maybe you could link to a gi... | 26,585 | [
-0.02668432705104351,
0.026697203516960144,
-0.01928918994963169,
0.0081798629835248,
0.0021153755951672792,
-0.008312898688018322,
0.10202281922101974,
0.01450099516659975,
0.01595441810786724,
-0.029677120968699455,
-0.009741507470607758,
0.07317987084388733,
-0.01516986545175314,
-0.021... |
https://github.com/scikit-learn/scikit-learn/issues/26585 | [
"New Feature",
"Array API"
] | Array API support for k-means
This is an early issue to publicly discuss the possibility (or not) to use the Array API (see #22352) for k-means and make it run on GPUs using PyTorch in particular.
@fcharras has already started to run some promising experiments using the raw PyTorch API. Maybe you could link to a gi... | 26,585 | [
-0.032266389578580856,
0.038222022354602814,
-0.021501166746020317,
0.0077419704757630825,
0.0021693434100598097,
-0.012241671793162823,
0.10372915118932724,
0.0020821758080273867,
0.01319365669041872,
-0.026145633310079575,
-0.011345034465193748,
0.06792444735765457,
-0.016491346061229706,
... |
https://github.com/scikit-learn/scikit-learn/issues/26585 | [
"New Feature",
"Array API"
] | Array API support for k-means
This is an early issue to publicly discuss the possibility (or not) to use the Array API (see #22352) for k-means and make it run on GPUs using PyTorch in particular.
@fcharras has already started to run some promising experiments using the raw PyTorch API. Maybe you could link to a gi... | 26,585 | [
-0.019961180165410042,
0.01842508837580681,
-0.02362629771232605,
0.010524715296924114,
0.0063611469231545925,
-0.0011008279398083687,
0.087520532310009,
0.00005901573968003504,
0.0032862049993127584,
-0.03296930715441704,
-0.016258394345641136,
0.08185499906539917,
-0.014561028219759464,
... |
https://github.com/scikit-learn/scikit-learn/issues/26583 | [
"Bug"
] | ⚠️ CI failed on Wheel builder ⚠️
**CI failed on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/5274563578)** (Jun 15, 2023)
COMMENT:
Looks like `test_learning_curve_display_deprecate_log_scale `is missing a marker to say "skip if matplotlib is not installed". Weird that it was not seen befo... | 26,583 | [
-0.011760751716792583,
0.03261783346533775,
-0.018645403906702995,
-0.05118769779801369,
0.018879259005188942,
0.047736719250679016,
0.05238750949501991,
0.05439724028110504,
0.00846213847398758,
0.016983354464173317,
0.069292813539505,
0.06642073392868042,
-0.037550702691078186,
0.0795577... |
https://github.com/scikit-learn/scikit-learn/issues/26583 | [
"Bug"
] | ⚠️ CI failed on Wheel builder ⚠️
**CI failed on [Wheel builder](https://github.com/scikit-learn/scikit-learn/actions/runs/5274563578)** (Jun 15, 2023)
COMMENT:
Looking through `build_tools/update_environments_and_lock_files.py`, it looks like all our CI jobs that run on PRs have matplotlib installed, so we did not ca... | 26,583 | [
-0.024633876979351044,
0.02784150093793869,
-0.02245202474296093,
-0.03593626990914345,
0.02446594275534153,
0.024363350123167038,
0.01434161514043808,
0.03444761782884598,
-0.04435774311423302,
0.03205471858382225,
0.07208301872015,
0.04712792858481407,
-0.034386903047561646,
0.0616779550... |
https://github.com/scikit-learn/scikit-learn/issues/26573 | [
"Documentation",
"module:tree"
] | Improving the descriptions in decision tree structure example
### Describe the issue linked to the documentation
I am suggesting two improvements to the documentation of decision trees. This is motivated by constantly having to come back to the source code to try to understand what `DecisionTreeClassifier.tree_.val... | 26,573 | [
-0.0075998855754733086,
-0.05380038917064667,
-0.022954311221837997,
0.016114478930830956,
-0.015246899798512459,
-0.007623896934092045,
-0.05549713969230652,
-0.03925636038184166,
-0.08081251382827759,
-0.042700305581092834,
0.009386568330228329,
0.0424451045691967,
0.0243869386613369,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/26573 | [
"Documentation",
"module:tree"
] | Improving the descriptions in decision tree structure example
### Describe the issue linked to the documentation
I am suggesting two improvements to the documentation of decision trees. This is motivated by constantly having to come back to the source code to try to understand what `DecisionTreeClassifier.tree_.val... | 26,573 | [
-0.0075998855754733086,
-0.05380038917064667,
-0.022954311221837997,
0.016114478930830956,
-0.015246899798512459,
-0.007623896934092045,
-0.05549713969230652,
-0.03925636038184166,
-0.08081251382827759,
-0.042700305581092834,
0.009386568330228329,
0.0424451045691967,
0.0243869386613369,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/26565 | [
"New Feature",
"Needs Triage"
] | Dropout implementation
### Describe the workflow you want to enable
I am coming from Tensorflow models, and there is a neural network important feature that is not implemented yet: the dropout rate.
### Describe your proposed solution
When reading across internet, you can find a useful link explaining the drop out ... | 26,565 | [
-0.023055382072925568,
-0.0176389180123806,
0.010201197117567062,
0.017460452392697334,
0.02091088704764843,
-0.006257787812501192,
0.022961754351854324,
-0.028028693050146103,
0.005567923188209534,
-0.03599870204925537,
0.021337857469916344,
0.06489560008049011,
-0.04058799147605896,
0.09... |
https://github.com/scikit-learn/scikit-learn/issues/26560 | [
"Bug",
"Needs Triage"
] | Failed testcase with numpy binary compiled with clang compiler on AWS Graviton
### Describe the bug
Below testcase is failing when we are building scikit-learn using numpy binary compiled with clang compiler on AWS Graviton:
```py
@wraps(func)
def inner(*args, **kwds):
with self._recreate_cm()... | 26,560 | [
0.007616148330271244,
-0.028508400544524193,
-0.004953972063958645,
-0.006944688037037849,
0.05338510498404503,
0.03069777972996235,
-0.004131751600652933,
0.013029218651354313,
0.015223703347146511,
-0.010555671527981758,
0.005166162736713886,
0.048495180904865265,
-0.008133885450661182,
... |
https://github.com/scikit-learn/scikit-learn/issues/26552 | [
"Enhancement"
] | False positive warning in `FunctionTransformer`
While looking at #26543, I find out that we raise a `FutureWarning` that looked like a false positive to me:
```python
from sklearn.preprocessing import FunctionTransformer, OneHotEncoder
from sklearn.pipeline import make_pipeline
import pandas as pd
import numpy ... | 26,552 | [
0.0011289619142189622,
0.04060347005724907,
0.016163773834705353,
-0.007794537581503391,
0.07856416702270508,
0.009732448495924473,
0.07178911566734314,
0.029819287359714508,
-0.0018716728081926703,
0.015291408635675907,
0.05359266325831413,
0.012868777848780155,
0.03449862077832222,
0.041... |
https://github.com/scikit-learn/scikit-learn/issues/26552 | [
"Enhancement"
] | False positive warning in `FunctionTransformer`
While looking at #26543, I find out that we raise a `FutureWarning` that looked like a false positive to me:
```python
from sklearn.preprocessing import FunctionTransformer, OneHotEncoder
from sklearn.pipeline import make_pipeline
import pandas as pd
import numpy ... | 26,552 | [
0.0011289619142189622,
0.04060347005724907,
0.016163773834705353,
-0.007794537581503391,
0.07856416702270508,
0.009732448495924473,
0.07178911566734314,
0.029819287359714508,
-0.0018716728081926703,
0.015291408635675907,
0.05359266325831413,
0.012868777848780155,
0.03449862077832222,
0.041... |
https://github.com/scikit-learn/scikit-learn/issues/26552 | [
"Enhancement"
] | False positive warning in `FunctionTransformer`
While looking at #26543, I find out that we raise a `FutureWarning` that looked like a false positive to me:
```python
from sklearn.preprocessing import FunctionTransformer, OneHotEncoder
from sklearn.pipeline import make_pipeline
import pandas as pd
import numpy ... | 26,552 | [
0.0011289619142189622,
0.04060347005724907,
0.016163773834705353,
-0.007794537581503391,
0.07856416702270508,
0.009732448495924473,
0.07178911566734314,
0.029819287359714508,
-0.0018716728081926703,
0.015291408635675907,
0.05359266325831413,
0.012868777848780155,
0.03449862077832222,
0.041... |
https://github.com/scikit-learn/scikit-learn/issues/26552 | [
"Enhancement"
] | False positive warning in `FunctionTransformer`
While looking at #26543, I find out that we raise a `FutureWarning` that looked like a false positive to me:
```python
from sklearn.preprocessing import FunctionTransformer, OneHotEncoder
from sklearn.pipeline import make_pipeline
import pandas as pd
import numpy ... | 26,552 | [
0.0011289619142189622,
0.04060347005724907,
0.016163773834705353,
-0.007794537581503391,
0.07856416702270508,
0.009732448495924473,
0.07178911566734314,
0.029819287359714508,
-0.0018716728081926703,
0.015291408635675907,
0.05359266325831413,
0.012868777848780155,
0.03449862077832222,
0.041... |
https://github.com/scikit-learn/scikit-learn/issues/26552 | [
"Enhancement"
] | False positive warning in `FunctionTransformer`
While looking at #26543, I find out that we raise a `FutureWarning` that looked like a false positive to me:
```python
from sklearn.preprocessing import FunctionTransformer, OneHotEncoder
from sklearn.pipeline import make_pipeline
import pandas as pd
import numpy ... | 26,552 | [
0.0011289619142189622,
0.04060347005724907,
0.016163773834705353,
-0.007794537581503391,
0.07856416702270508,
0.009732448495924473,
0.07178911566734314,
0.029819287359714508,
-0.0018716728081926703,
0.015291408635675907,
0.05359266325831413,
0.012868777848780155,
0.03449862077832222,
0.041... |
https://github.com/scikit-learn/scikit-learn/issues/26552 | [
"Enhancement"
] | False positive warning in `FunctionTransformer`
While looking at #26543, I find out that we raise a `FutureWarning` that looked like a false positive to me:
```python
from sklearn.preprocessing import FunctionTransformer, OneHotEncoder
from sklearn.pipeline import make_pipeline
import pandas as pd
import numpy ... | 26,552 | [
0.0011289619142189622,
0.04060347005724907,
0.016163773834705353,
-0.007794537581503391,
0.07856416702270508,
0.009732448495924473,
0.07178911566734314,
0.029819287359714508,
-0.0018716728081926703,
0.015291408635675907,
0.05359266325831413,
0.012868777848780155,
0.03449862077832222,
0.041... |
https://github.com/scikit-learn/scikit-learn/issues/26550 | [
"Bug",
"Needs Triage"
] | AttributeError: module 'sklearn.metrics._dist_metrics' has no attribute 'DistanceMetric32'
### Describe the bug
I am using the pyldavis library which depends on scikit learn, I have been working for months without any problem. Today at night a new error appeared when I tried the library
`import pyLDAvis`
Attrib... | 26,550 | [
-0.0029079054947942495,
0.002904177876189351,
-0.0025010637473315,
-0.010223111137747765,
0.06126474589109421,
0.02842356450855732,
0.03961631655693054,
0.09637420624494553,
0.03406831994652748,
-0.010804018005728722,
0.0065348451025784016,
0.04974489286541939,
-0.012043440714478493,
-0.02... |
https://github.com/scikit-learn/scikit-learn/issues/26550 | [
"Bug",
"Needs Triage"
] | AttributeError: module 'sklearn.metrics._dist_metrics' has no attribute 'DistanceMetric32'
### Describe the bug
I am using the pyldavis library which depends on scikit learn, I have been working for months without any problem. Today at night a new error appeared when I tried the library
`import pyLDAvis`
Attrib... | 26,550 | [
-0.0029079054947942495,
0.002904177876189351,
-0.0025010637473315,
-0.010223111137747765,
0.06126474589109421,
0.02842356450855732,
0.03961631655693054,
0.09637420624494553,
0.03406831994652748,
-0.010804018005728722,
0.0065348451025784016,
0.04974489286541939,
-0.012043440714478493,
-0.02... |
https://github.com/scikit-learn/scikit-learn/issues/26548 | [
"Bug"
] | Using `NearestNeighbors` with `p < 1` and floats raises an error
### Describe the bug
Using `NearestNeighbors` with `p < 1` raises an error if the array `X` contains floats. It does not seem to raise errors if `X` consists of integers.
This was originally discussed in https://github.com/scikit-learn/scikit-learn... | 26,548 | [
-0.043090060353279114,
-0.006354923360049725,
0.015324294567108154,
-0.01357774157077074,
0.05447714403271675,
-0.0043554347939789295,
0.05413166433572769,
0.03879235312342644,
0.011647844687104225,
-0.024471690878272057,
-0.0178802739828825,
0.01219676248729229,
-0.005710398778319359,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/26548 | [
"Bug"
] | Using `NearestNeighbors` with `p < 1` and floats raises an error
### Describe the bug
Using `NearestNeighbors` with `p < 1` raises an error if the array `X` contains floats. It does not seem to raise errors if `X` consists of integers.
This was originally discussed in https://github.com/scikit-learn/scikit-learn... | 26,548 | [
-0.043090060353279114,
-0.006354923360049725,
0.015324294567108154,
-0.01357774157077074,
0.05447714403271675,
-0.0043554347939789295,
0.05413166433572769,
0.03879235312342644,
0.011647844687104225,
-0.024471690878272057,
-0.0178802739828825,
0.01219676248729229,
-0.005710398778319359,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/26548 | [
"Bug"
] | Using `NearestNeighbors` with `p < 1` and floats raises an error
### Describe the bug
Using `NearestNeighbors` with `p < 1` raises an error if the array `X` contains floats. It does not seem to raise errors if `X` consists of integers.
This was originally discussed in https://github.com/scikit-learn/scikit-learn... | 26,548 | [
-0.043090060353279114,
-0.006354923360049725,
0.015324294567108154,
-0.01357774157077074,
0.05447714403271675,
-0.0043554347939789295,
0.05413166433572769,
0.03879235312342644,
0.011647844687104225,
-0.024471690878272057,
-0.0178802739828825,
0.01219676248729229,
-0.005710398778319359,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/26548 | [
"Bug"
] | Using `NearestNeighbors` with `p < 1` and floats raises an error
### Describe the bug
Using `NearestNeighbors` with `p < 1` raises an error if the array `X` contains floats. It does not seem to raise errors if `X` consists of integers.
This was originally discussed in https://github.com/scikit-learn/scikit-learn... | 26,548 | [
-0.043090060353279114,
-0.006354923360049725,
0.015324294567108154,
-0.01357774157077074,
0.05447714403271675,
-0.0043554347939789295,
0.05413166433572769,
0.03879235312342644,
0.011647844687104225,
-0.024471690878272057,
-0.0178802739828825,
0.01219676248729229,
-0.005710398778319359,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/26548 | [
"Bug"
] | Using `NearestNeighbors` with `p < 1` and floats raises an error
### Describe the bug
Using `NearestNeighbors` with `p < 1` raises an error if the array `X` contains floats. It does not seem to raise errors if `X` consists of integers.
This was originally discussed in https://github.com/scikit-learn/scikit-learn... | 26,548 | [
-0.043090060353279114,
-0.006354923360049725,
0.015324294567108154,
-0.01357774157077074,
0.05447714403271675,
-0.0043554347939789295,
0.05413166433572769,
0.03879235312342644,
0.011647844687104225,
-0.024471690878272057,
-0.0178802739828825,
0.01219676248729229,
-0.005710398778319359,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/26548 | [
"Bug"
] | Using `NearestNeighbors` with `p < 1` and floats raises an error
### Describe the bug
Using `NearestNeighbors` with `p < 1` raises an error if the array `X` contains floats. It does not seem to raise errors if `X` consists of integers.
This was originally discussed in https://github.com/scikit-learn/scikit-learn... | 26,548 | [
-0.043090060353279114,
-0.006354923360049725,
0.015324294567108154,
-0.01357774157077074,
0.05447714403271675,
-0.0043554347939789295,
0.05413166433572769,
0.03879235312342644,
0.011647844687104225,
-0.024471690878272057,
-0.0178802739828825,
0.01219676248729229,
-0.005710398778319359,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/26548 | [
"Bug"
] | Using `NearestNeighbors` with `p < 1` and floats raises an error
### Describe the bug
Using `NearestNeighbors` with `p < 1` raises an error if the array `X` contains floats. It does not seem to raise errors if `X` consists of integers.
This was originally discussed in https://github.com/scikit-learn/scikit-learn... | 26,548 | [
-0.043090060353279114,
-0.006354923360049725,
0.015324294567108154,
-0.01357774157077074,
0.05447714403271675,
-0.0043554347939789295,
0.05413166433572769,
0.03879235312342644,
0.011647844687104225,
-0.024471690878272057,
-0.0178802739828825,
0.01219676248729229,
-0.005710398778319359,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/26548 | [
"Bug"
] | Using `NearestNeighbors` with `p < 1` and floats raises an error
### Describe the bug
Using `NearestNeighbors` with `p < 1` raises an error if the array `X` contains floats. It does not seem to raise errors if `X` consists of integers.
This was originally discussed in https://github.com/scikit-learn/scikit-learn... | 26,548 | [
-0.043090060353279114,
-0.006354923360049725,
0.015324294567108154,
-0.01357774157077074,
0.05447714403271675,
-0.0043554347939789295,
0.05413166433572769,
0.03879235312342644,
0.011647844687104225,
-0.024471690878272057,
-0.0178802739828825,
0.01219676248729229,
-0.005710398778319359,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/26543 | [
"Enhancement"
] | What happend to the idea of adding a 'handle_missing' parameter to the OneHotEncoder?
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/26531
<div type='discussions-op-text'>
<sup>Originally posted by **woodly0** June 7, 2023</sup>
Hello,
I'm having trouble understanding what finally h... | 26,543 | [
0.008428244851529598,
0.0693809911608696,
0.037125423550605774,
-0.01030366774648428,
0.025877835229039192,
0.02532918006181717,
0.10105551034212112,
0.029714014381170273,
-0.03562074899673462,
-0.0016591924941167235,
0.10537809133529663,
0.02045581117272377,
0.005351979751139879,
0.039793... |
https://github.com/scikit-learn/scikit-learn/issues/26543 | [
"Enhancement"
] | What happend to the idea of adding a 'handle_missing' parameter to the OneHotEncoder?
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/26531
<div type='discussions-op-text'>
<sup>Originally posted by **woodly0** June 7, 2023</sup>
Hello,
I'm having trouble understanding what finally h... | 26,543 | [
0.008428244851529598,
0.0693809911608696,
0.037125423550605774,
-0.01030366774648428,
0.025877835229039192,
0.02532918006181717,
0.10105551034212112,
0.029714014381170273,
-0.03562074899673462,
-0.0016591924941167235,
0.10537809133529663,
0.02045581117272377,
0.005351979751139879,
0.039793... |
https://github.com/scikit-learn/scikit-learn/issues/26543 | [
"Enhancement"
] | What happend to the idea of adding a 'handle_missing' parameter to the OneHotEncoder?
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/26531
<div type='discussions-op-text'>
<sup>Originally posted by **woodly0** June 7, 2023</sup>
Hello,
I'm having trouble understanding what finally h... | 26,543 | [
0.008428244851529598,
0.0693809911608696,
0.037125423550605774,
-0.01030366774648428,
0.025877835229039192,
0.02532918006181717,
0.10105551034212112,
0.029714014381170273,
-0.03562074899673462,
-0.0016591924941167235,
0.10537809133529663,
0.02045581117272377,
0.005351979751139879,
0.039793... |
https://github.com/scikit-learn/scikit-learn/issues/26543 | [
"Enhancement"
] | What happend to the idea of adding a 'handle_missing' parameter to the OneHotEncoder?
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/26531
<div type='discussions-op-text'>
<sup>Originally posted by **woodly0** June 7, 2023</sup>
Hello,
I'm having trouble understanding what finally h... | 26,543 | [
0.008428244851529598,
0.0693809911608696,
0.037125423550605774,
-0.01030366774648428,
0.025877835229039192,
0.02532918006181717,
0.10105551034212112,
0.029714014381170273,
-0.03562074899673462,
-0.0016591924941167235,
0.10537809133529663,
0.02045581117272377,
0.005351979751139879,
0.039793... |
https://github.com/scikit-learn/scikit-learn/issues/26543 | [
"Enhancement"
] | What happend to the idea of adding a 'handle_missing' parameter to the OneHotEncoder?
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/26531
<div type='discussions-op-text'>
<sup>Originally posted by **woodly0** June 7, 2023</sup>
Hello,
I'm having trouble understanding what finally h... | 26,543 | [
0.008428244851529598,
0.0693809911608696,
0.037125423550605774,
-0.01030366774648428,
0.025877835229039192,
0.02532918006181717,
0.10105551034212112,
0.029714014381170273,
-0.03562074899673462,
-0.0016591924941167235,
0.10537809133529663,
0.02045581117272377,
0.005351979751139879,
0.039793... |
https://github.com/scikit-learn/scikit-learn/issues/26543 | [
"Enhancement"
] | What happend to the idea of adding a 'handle_missing' parameter to the OneHotEncoder?
### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/26531
<div type='discussions-op-text'>
<sup>Originally posted by **woodly0** June 7, 2023</sup>
Hello,
I'm having trouble understanding what finally h... | 26,543 | [
0.008428244851529598,
0.0693809911608696,
0.037125423550605774,
-0.01030366774648428,
0.025877835229039192,
0.02532918006181717,
0.10105551034212112,
0.029714014381170273,
-0.03562074899673462,
-0.0016591924941167235,
0.10537809133529663,
0.02045581117272377,
0.005351979751139879,
0.039793... |
https://github.com/scikit-learn/scikit-learn/issues/26541 | [
"pypy"
] | HDBSCAN tests are failing on pypy
As seen in the nigthly build, a lot of hdbscan tests are failing in the pypy job.
Here's a link with the full failure report for some of them https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=55668&view=logs&jobId=0b16f832-29d6-5b92-1c23-eb006f606a66&j=0b16f832-2... | 26,541 | [
-0.008555883541703224,
-0.007827877067029476,
0.017918383702635765,
-0.05195579677820206,
0.01722240261733532,
0.023259954527020454,
0.03140982985496521,
0.06491029262542725,
0.0022267671301960945,
0.007571327034384012,
0.03343954682350159,
0.009962704963982105,
-0.02136196754872799,
0.047... |
https://github.com/scikit-learn/scikit-learn/issues/26537 | [
"Bug",
"Needs Info"
] | ValueError: The covariance matrix of the support data is equal to 0 - Elliptic Envelope
### Describe the bug
I have been using Elliptic Envelope on a simple time series dataset with default parameters and only setting `contamination` value to `0.5`. However it throws me error like below:
`ValueError: The covaria... | 26,537 | [
0.010539663955569267,
-0.05453098192811012,
0.052719857543706894,
0.04195037856698036,
0.07019630074501038,
-0.008350674994289875,
-0.025223663076758385,
0.0009684902615845203,
-0.018641047179698944,
0.017229214310646057,
0.06699466705322266,
0.010425918735563755,
-0.02499433048069477,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/26537 | [
"Bug",
"Needs Info"
] | ValueError: The covariance matrix of the support data is equal to 0 - Elliptic Envelope
### Describe the bug
I have been using Elliptic Envelope on a simple time series dataset with default parameters and only setting `contamination` value to `0.5`. However it throws me error like below:
`ValueError: The covaria... | 26,537 | [
0.010539663955569267,
-0.05453098192811012,
0.052719857543706894,
0.04195037856698036,
0.07019630074501038,
-0.008350674994289875,
-0.025223663076758385,
0.0009684902615845203,
-0.018641047179698944,
0.017229214310646057,
0.06699466705322266,
0.010425918735563755,
-0.02499433048069477,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/26537 | [
"Bug",
"Needs Info"
] | ValueError: The covariance matrix of the support data is equal to 0 - Elliptic Envelope
### Describe the bug
I have been using Elliptic Envelope on a simple time series dataset with default parameters and only setting `contamination` value to `0.5`. However it throws me error like below:
`ValueError: The covaria... | 26,537 | [
0.010539663955569267,
-0.05453098192811012,
0.052719857543706894,
0.04195037856698036,
0.07019630074501038,
-0.008350674994289875,
-0.025223663076758385,
0.0009684902615845203,
-0.018641047179698944,
0.017229214310646057,
0.06699466705322266,
0.010425918735563755,
-0.02499433048069477,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/26537 | [
"Bug",
"Needs Info"
] | ValueError: The covariance matrix of the support data is equal to 0 - Elliptic Envelope
### Describe the bug
I have been using Elliptic Envelope on a simple time series dataset with default parameters and only setting `contamination` value to `0.5`. However it throws me error like below:
`ValueError: The covaria... | 26,537 | [
0.010539663955569267,
-0.05453098192811012,
0.052719857543706894,
0.04195037856698036,
0.07019630074501038,
-0.008350674994289875,
-0.025223663076758385,
0.0009684902615845203,
-0.018641047179698944,
0.017229214310646057,
0.06699466705322266,
0.010425918735563755,
-0.02499433048069477,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/26532 | [
"New Feature",
"Needs Triage"
] | Add tqdm integration for progress tracking in GridSearchCV
### Describe the workflow you want to enable
I believe it would be beneficial to integrate tqdm into GridSearchCV for more detailed and user-friendly progress tracking. While the verbose parameter provides some information, a progress bar could give users a b... | 26,532 | [
-0.007927702739834785,
0.07964152097702026,
0.0027187445666640997,
-0.04465073347091675,
0.03605226054787636,
-0.030719242990016937,
-0.012938683852553368,
0.009159351699054241,
-0.01639408804476261,
0.012440159916877747,
-0.011226750910282135,
0.042599156498909,
-0.058010637760162354,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/26532 | [
"New Feature",
"Needs Triage"
] | Add tqdm integration for progress tracking in GridSearchCV
### Describe the workflow you want to enable
I believe it would be beneficial to integrate tqdm into GridSearchCV for more detailed and user-friendly progress tracking. While the verbose parameter provides some information, a progress bar could give users a b... | 26,532 | [
-0.018149925395846367,
0.08657994121313095,
-0.002544487826526165,
-0.04437461867928505,
0.029101379215717316,
-0.03240232542157173,
-0.017840992659330368,
0.007747318129986525,
-0.024599362164735794,
0.016500482335686684,
-0.019342472776770592,
0.03300099819898605,
-0.06778627634048462,
0... |
https://github.com/scikit-learn/scikit-learn/issues/26532 | [
"New Feature",
"Needs Triage"
] | Add tqdm integration for progress tracking in GridSearchCV
### Describe the workflow you want to enable
I believe it would be beneficial to integrate tqdm into GridSearchCV for more detailed and user-friendly progress tracking. While the verbose parameter provides some information, a progress bar could give users a b... | 26,532 | [
-0.014319201000034809,
0.08073493838310242,
-0.004316339269280434,
-0.043558426201343536,
0.0295349583029747,
-0.031394489109516144,
-0.024661194533109665,
0.008817440830171108,
-0.02452251873910427,
0.017947256565093994,
-0.016133306547999382,
0.031147971749305725,
-0.066375732421875,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/26530 | [
"Bug",
"good first issue"
] | TransformedTargetRegressor forces 1d y shape to regressor
### Describe the bug
I experience the following error when using TransformedTargetRegressor with my skorch model:
ValueError: The target data shouldn't be 1-dimensional but instead have 2 dimensions, with the second dimension having the same size as the num... | 26,530 | [
-0.00023014181351754814,
0.008045204915106297,
0.03907763212919235,
-0.014943045563995838,
0.05080793425440788,
-0.0347558967769146,
0.07032428681850433,
-0.0023593148216605186,
-0.03521960973739624,
0.04198155179619789,
0.05861818045377731,
-0.012158812955021858,
0.02662483975291252,
0.06... |
https://github.com/scikit-learn/scikit-learn/issues/26530 | [
"Bug",
"good first issue"
] | TransformedTargetRegressor forces 1d y shape to regressor
### Describe the bug
I experience the following error when using TransformedTargetRegressor with my skorch model:
ValueError: The target data shouldn't be 1-dimensional but instead have 2 dimensions, with the second dimension having the same size as the num... | 26,530 | [
-0.00023014181351754814,
0.008045204915106297,
0.03907763212919235,
-0.014943045563995838,
0.05080793425440788,
-0.0347558967769146,
0.07032428681850433,
-0.0023593148216605186,
-0.03521960973739624,
0.04198155179619789,
0.05861818045377731,
-0.012158812955021858,
0.02662483975291252,
0.06... |
https://github.com/scikit-learn/scikit-learn/issues/26530 | [
"Bug",
"good first issue"
] | TransformedTargetRegressor forces 1d y shape to regressor
### Describe the bug
I experience the following error when using TransformedTargetRegressor with my skorch model:
ValueError: The target data shouldn't be 1-dimensional but instead have 2 dimensions, with the second dimension having the same size as the num... | 26,530 | [
-0.00023014181351754814,
0.008045204915106297,
0.03907763212919235,
-0.014943045563995838,
0.05080793425440788,
-0.0347558967769146,
0.07032428681850433,
-0.0023593148216605186,
-0.03521960973739624,
0.04198155179619789,
0.05861818045377731,
-0.012158812955021858,
0.02662483975291252,
0.06... |
https://github.com/scikit-learn/scikit-learn/issues/26530 | [
"Bug",
"good first issue"
] | TransformedTargetRegressor forces 1d y shape to regressor
### Describe the bug
I experience the following error when using TransformedTargetRegressor with my skorch model:
ValueError: The target data shouldn't be 1-dimensional but instead have 2 dimensions, with the second dimension having the same size as the num... | 26,530 | [
-0.00023014181351754814,
0.008045204915106297,
0.03907763212919235,
-0.014943045563995838,
0.05080793425440788,
-0.0347558967769146,
0.07032428681850433,
-0.0023593148216605186,
-0.03521960973739624,
0.04198155179619789,
0.05861818045377731,
-0.012158812955021858,
0.02662483975291252,
0.06... |
https://github.com/scikit-learn/scikit-learn/issues/26530 | [
"Bug",
"good first issue"
] | TransformedTargetRegressor forces 1d y shape to regressor
### Describe the bug
I experience the following error when using TransformedTargetRegressor with my skorch model:
ValueError: The target data shouldn't be 1-dimensional but instead have 2 dimensions, with the second dimension having the same size as the num... | 26,530 | [
-0.00023014181351754814,
0.008045204915106297,
0.03907763212919235,
-0.014943045563995838,
0.05080793425440788,
-0.0347558967769146,
0.07032428681850433,
-0.0023593148216605186,
-0.03521960973739624,
0.04198155179619789,
0.05861818045377731,
-0.012158812955021858,
0.02662483975291252,
0.06... |
https://github.com/scikit-learn/scikit-learn/issues/26530 | [
"Bug",
"good first issue"
] | TransformedTargetRegressor forces 1d y shape to regressor
### Describe the bug
I experience the following error when using TransformedTargetRegressor with my skorch model:
ValueError: The target data shouldn't be 1-dimensional but instead have 2 dimensions, with the second dimension having the same size as the num... | 26,530 | [
-0.00023014181351754814,
0.008045204915106297,
0.03907763212919235,
-0.014943045563995838,
0.05080793425440788,
-0.0347558967769146,
0.07032428681850433,
-0.0023593148216605186,
-0.03521960973739624,
0.04198155179619789,
0.05861818045377731,
-0.012158812955021858,
0.02662483975291252,
0.06... |
https://github.com/scikit-learn/scikit-learn/issues/26530 | [
"Bug",
"good first issue"
] | TransformedTargetRegressor forces 1d y shape to regressor
### Describe the bug
I experience the following error when using TransformedTargetRegressor with my skorch model:
ValueError: The target data shouldn't be 1-dimensional but instead have 2 dimensions, with the second dimension having the same size as the num... | 26,530 | [
-0.00023014181351754814,
0.008045204915106297,
0.03907763212919235,
-0.014943045563995838,
0.05080793425440788,
-0.0347558967769146,
0.07032428681850433,
-0.0023593148216605186,
-0.03521960973739624,
0.04198155179619789,
0.05861818045377731,
-0.012158812955021858,
0.02662483975291252,
0.06... |
https://github.com/scikit-learn/scikit-learn/issues/26530 | [
"Bug",
"good first issue"
] | TransformedTargetRegressor forces 1d y shape to regressor
### Describe the bug
I experience the following error when using TransformedTargetRegressor with my skorch model:
ValueError: The target data shouldn't be 1-dimensional but instead have 2 dimensions, with the second dimension having the same size as the num... | 26,530 | [
-0.00023014181351754814,
0.008045204915106297,
0.03907763212919235,
-0.014943045563995838,
0.05080793425440788,
-0.0347558967769146,
0.07032428681850433,
-0.0023593148216605186,
-0.03521960973739624,
0.04198155179619789,
0.05861818045377731,
-0.012158812955021858,
0.02662483975291252,
0.06... |
https://github.com/scikit-learn/scikit-learn/issues/26530 | [
"Bug",
"good first issue"
] | TransformedTargetRegressor forces 1d y shape to regressor
### Describe the bug
I experience the following error when using TransformedTargetRegressor with my skorch model:
ValueError: The target data shouldn't be 1-dimensional but instead have 2 dimensions, with the second dimension having the same size as the num... | 26,530 | [
-0.00023014181351754814,
0.008045204915106297,
0.03907763212919235,
-0.014943045563995838,
0.05080793425440788,
-0.0347558967769146,
0.07032428681850433,
-0.0023593148216605186,
-0.03521960973739624,
0.04198155179619789,
0.05861818045377731,
-0.012158812955021858,
0.02662483975291252,
0.06... |
https://github.com/scikit-learn/scikit-learn/issues/26530 | [
"Bug",
"good first issue"
] | TransformedTargetRegressor forces 1d y shape to regressor
### Describe the bug
I experience the following error when using TransformedTargetRegressor with my skorch model:
ValueError: The target data shouldn't be 1-dimensional but instead have 2 dimensions, with the second dimension having the same size as the num... | 26,530 | [
-0.00023014181351754814,
0.008045204915106297,
0.03907763212919235,
-0.014943045563995838,
0.05080793425440788,
-0.0347558967769146,
0.07032428681850433,
-0.0023593148216605186,
-0.03521960973739624,
0.04198155179619789,
0.05861818045377731,
-0.012158812955021858,
0.02662483975291252,
0.06... |
https://github.com/scikit-learn/scikit-learn/issues/26530 | [
"Bug",
"good first issue"
] | TransformedTargetRegressor forces 1d y shape to regressor
### Describe the bug
I experience the following error when using TransformedTargetRegressor with my skorch model:
ValueError: The target data shouldn't be 1-dimensional but instead have 2 dimensions, with the second dimension having the same size as the num... | 26,530 | [
-0.00023014181351754814,
0.008045204915106297,
0.03907763212919235,
-0.014943045563995838,
0.05080793425440788,
-0.0347558967769146,
0.07032428681850433,
-0.0023593148216605186,
-0.03521960973739624,
0.04198155179619789,
0.05861818045377731,
-0.012158812955021858,
0.02662483975291252,
0.06... |
https://github.com/scikit-learn/scikit-learn/issues/26524 | [
"New Feature",
"Needs Triage"
] | GridSearchCV for neural networks that allows evaluation of the validation set after every epoch
### Describe the workflow you want to enable
I would like to be able to perform a grid search of hyperparemeters for a neural network using crossvalidation such as with GridSearchCV. I was able to set everything up in Scik... | 26,524 | [
-0.05671679228544235,
0.07581344246864319,
0.02361449971795082,
-0.03921123594045639,
0.07058614492416382,
-0.024591123685240746,
-0.006660216487944126,
0.009702622890472412,
-0.008396482095122337,
0.012540995143353939,
0.03303230181336403,
0.010404320433735847,
-0.030956119298934937,
0.05... |
https://github.com/scikit-learn/scikit-learn/issues/26524 | [
"New Feature",
"Needs Triage"
] | GridSearchCV for neural networks that allows evaluation of the validation set after every epoch
### Describe the workflow you want to enable
I would like to be able to perform a grid search of hyperparemeters for a neural network using crossvalidation such as with GridSearchCV. I was able to set everything up in Scik... | 26,524 | [
-0.05671679228544235,
0.07581344246864319,
0.02361449971795082,
-0.03921123594045639,
0.07058614492416382,
-0.024591123685240746,
-0.006660216487944126,
0.009702622890472412,
-0.008396482095122337,
0.012540995143353939,
0.03303230181336403,
0.010404320433735847,
-0.030956119298934937,
0.05... |
https://github.com/scikit-learn/scikit-learn/issues/26524 | [
"New Feature",
"Needs Triage"
] | GridSearchCV for neural networks that allows evaluation of the validation set after every epoch
### Describe the workflow you want to enable
I would like to be able to perform a grid search of hyperparemeters for a neural network using crossvalidation such as with GridSearchCV. I was able to set everything up in Scik... | 26,524 | [
-0.05671679228544235,
0.07581344246864319,
0.02361449971795082,
-0.03921123594045639,
0.07058614492416382,
-0.024591123685240746,
-0.006660216487944126,
0.009702622890472412,
-0.008396482095122337,
0.012540995143353939,
0.03303230181336403,
0.010404320433735847,
-0.030956119298934937,
0.05... |
https://github.com/scikit-learn/scikit-learn/issues/26523 | [
"Needs Triage"
] | ⚠️ CI failed on Ubuntu_Jammy_Jellyfish.py38_conda_forge_openblas_ubuntu_2204 ⚠️
**CI is still failing on [Ubuntu_Jammy_Jellyfish.py38_conda_forge_openblas_ubuntu_2204](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=55614&view=logs&j=7d13af21-9cb9-5d40-483b-ea0f074409c6)** (Jun 07, 2023)
- test_... | 26,523 | [
0.016103269532322884,
0.01707587018609047,
-0.028878387063741684,
-0.04928590729832649,
0.038022201508283615,
0.008980830200016499,
0.013879481703042984,
0.036473046988248825,
-0.030708834528923035,
0.021075529977679253,
0.014957881532609463,
0.0269149299710989,
0.014870816841721535,
0.099... |
https://github.com/scikit-learn/scikit-learn/issues/26518 | [
"Documentation"
] | DOC add __sklearn_is_fitted__ and others to Developer guide
### Describe the issue linked to the documentation
It would be nice to add the internal developer "APIs" like `__sklearn_is_fitted__` to the user guide section [Developing scikit-learn estimators](https://scikit-learn.org/dev/developers/develop.html#developi... | 26,518 | [
0.0007761863525956869,
0.007121598348021507,
0.021447885781526566,
-0.02069220505654812,
0.047801800072193146,
-0.018311653286218643,
0.0444280207157135,
0.017396431416273117,
0.08168123662471771,
0.008421394973993301,
0.057525984942913055,
0.05286112800240517,
0.005626401863992214,
0.0162... |
https://github.com/scikit-learn/scikit-learn/issues/26518 | [
"Documentation"
] | DOC add __sklearn_is_fitted__ and others to Developer guide
### Describe the issue linked to the documentation
It would be nice to add the internal developer "APIs" like `__sklearn_is_fitted__` to the user guide section [Developing scikit-learn estimators](https://scikit-learn.org/dev/developers/develop.html#developi... | 26,518 | [
-0.008665173314511776,
-0.008728958666324615,
0.00225850404240191,
0.008240282535552979,
0.04699736833572388,
-0.009812419302761555,
0.0409528948366642,
-0.0007190552423708141,
0.07804431766271591,
-0.003374901134520769,
0.06547601521015167,
0.08697275817394257,
0.00972768384963274,
0.0289... |
https://github.com/scikit-learn/scikit-learn/issues/26518 | [
"Documentation"
] | DOC add __sklearn_is_fitted__ and others to Developer guide
### Describe the issue linked to the documentation
It would be nice to add the internal developer "APIs" like `__sklearn_is_fitted__` to the user guide section [Developing scikit-learn estimators](https://scikit-learn.org/dev/developers/develop.html#developi... | 26,518 | [
-0.011533781886100769,
-0.014309779740869999,
0.009040110744535923,
0.007925480604171753,
0.03821035474538803,
-0.01720406860113144,
0.03434396907687187,
0.012450543232262135,
0.09380710870027542,
-0.007659037131816149,
0.05378181114792824,
0.08130151033401489,
0.023327017202973366,
0.0129... |
https://github.com/scikit-learn/scikit-learn/issues/26518 | [
"Documentation"
] | DOC add __sklearn_is_fitted__ and others to Developer guide
### Describe the issue linked to the documentation
It would be nice to add the internal developer "APIs" like `__sklearn_is_fitted__` to the user guide section [Developing scikit-learn estimators](https://scikit-learn.org/dev/developers/develop.html#developi... | 26,518 | [
-0.009573147632181644,
-0.0003509349189698696,
0.004000574350357056,
0.005445840768516064,
0.04022424295544624,
-0.017406858503818512,
0.04529917240142822,
0.010797444730997086,
0.07961443066596985,
-0.004762405063956976,
0.05600181594491005,
0.07887867838144302,
0.022463003173470497,
0.01... |
https://github.com/scikit-learn/scikit-learn/issues/26518 | [
"Documentation"
] | DOC add __sklearn_is_fitted__ and others to Developer guide
### Describe the issue linked to the documentation
It would be nice to add the internal developer "APIs" like `__sklearn_is_fitted__` to the user guide section [Developing scikit-learn estimators](https://scikit-learn.org/dev/developers/develop.html#developi... | 26,518 | [
0.007133963517844677,
-0.01990411803126335,
0.0010149604640901089,
0.010252265259623528,
0.027454597875475883,
-0.006289553828537464,
0.057466059923172,
0.004330754280090332,
0.05392053350806236,
-0.0201518964022398,
0.06707939505577087,
0.0615965761244297,
0.009125703945755959,
0.00733481... |
https://github.com/scikit-learn/scikit-learn/issues/26518 | [
"Documentation"
] | DOC add __sklearn_is_fitted__ and others to Developer guide
### Describe the issue linked to the documentation
It would be nice to add the internal developer "APIs" like `__sklearn_is_fitted__` to the user guide section [Developing scikit-learn estimators](https://scikit-learn.org/dev/developers/develop.html#developi... | 26,518 | [
-0.005236690863966942,
-0.023788273334503174,
0.011486778035759926,
0.016919611021876335,
0.04357393458485603,
-0.015204479917883873,
0.04313524812459946,
0.011231679469347,
0.07551278173923492,
-0.01140112616121769,
0.06211800500750542,
0.06426436454057693,
0.029181091114878654,
0.0174684... |
https://github.com/scikit-learn/scikit-learn/issues/26518 | [
"Documentation"
] | DOC add __sklearn_is_fitted__ and others to Developer guide
### Describe the issue linked to the documentation
It would be nice to add the internal developer "APIs" like `__sklearn_is_fitted__` to the user guide section [Developing scikit-learn estimators](https://scikit-learn.org/dev/developers/develop.html#developi... | 26,518 | [
-0.004570036195218563,
0.002368070650845766,
-0.0005557028925977647,
0.002448946936056018,
0.03897351771593094,
-0.014485875144600868,
0.05335036292672157,
0.0030056959949433804,
0.0747114047408104,
-0.0024671736173331738,
0.055766042321920395,
0.08387788385152817,
0.008010449819266796,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/26515 | [
"New Feature"
] | Improve error message with pandas output and sparse data
Currently, we raise an error:
```
ValueError: Pandas output does not support sparse data.
```
when a transformer does output sparse data and we try to wrap it inside a dataframe due to `set_output(transform="pandas")`. I assume that at this point, we cou... | 26,515 | [
-0.015780463814735413,
0.08748671412467957,
0.037697721272706985,
-0.011867784895002842,
0.09771668910980225,
0.0058397650718688965,
0.024609897285699844,
0.07751654833555222,
-0.06095058470964432,
-0.013514846563339233,
0.03214370831847191,
0.011153479106724262,
-0.016631195321679115,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/26515 | [
"New Feature"
] | Improve error message with pandas output and sparse data
Currently, we raise an error:
```
ValueError: Pandas output does not support sparse data.
```
when a transformer does output sparse data and we try to wrap it inside a dataframe due to `set_output(transform="pandas")`. I assume that at this point, we cou... | 26,515 | [
-0.015145421028137207,
0.10576167702674866,
0.03956272080540657,
-0.00387420691549778,
0.09069564193487167,
-0.0007164822891354561,
0.026231780648231506,
0.07713440805673599,
-0.05095023289322853,
-0.013759736903011799,
0.02325117588043213,
0.022256925702095032,
-0.007938888855278492,
0.05... |
https://github.com/scikit-learn/scikit-learn/issues/26515 | [
"New Feature"
] | Improve error message with pandas output and sparse data
Currently, we raise an error:
```
ValueError: Pandas output does not support sparse data.
```
when a transformer does output sparse data and we try to wrap it inside a dataframe due to `set_output(transform="pandas")`. I assume that at this point, we cou... | 26,515 | [
-0.002467196434736252,
0.106535404920578,
0.033684439957141876,
-0.015487904660403728,
0.10288973897695541,
0.0035259933210909367,
0.04399137198925018,
0.08062969148159027,
-0.04021289199590683,
-0.011477830819785595,
0.037950240075588226,
0.02472488209605217,
-0.009968538768589497,
0.0639... |
https://github.com/scikit-learn/scikit-learn/issues/26514 | [
"Needs Triage"
] | ⚠️ CI failed on linux_arm64_wheel ⚠️
**CI failed on [linux_arm64_wheel](https://cirrus-ci.com/build/4705054238703616)** (Jun 05, 2023)
COMMENT:
## CI is no longer failing! ✅
[Successful run](https://cirrus-ci.com/build/5999585902985216) on Jun 06, 2023 | 26,514 | [
-0.021356401965022087,
-0.01584792323410511,
-0.03635216876864433,
-0.02891818806529045,
0.01567285880446434,
0.03430863469839096,
0.009591098874807358,
0.04406064748764038,
-0.05513109266757965,
0.020167455077171326,
0.04727966710925102,
0.009166247211396694,
0.011319554410874844,
0.02875... |
https://github.com/scikit-learn/scikit-learn/issues/26513 | [
"Needs Triage"
] | ⚠️ CI failed on linux_arm64_wheel ⚠️
**CI failed on [linux_arm64_wheel](https://cirrus-ci.com/build/4705054238703616)** (Jun 05, 2023)
COMMENT:
## CI is no longer failing! ✅
[Successful run](https://cirrus-ci.com/build/4705054238703616) on Jun 05, 2023 | 26,513 | [
-0.022680452093482018,
-0.019131461158394814,
-0.036645401269197464,
-0.03367378190159798,
0.019073981791734695,
0.03633115440607071,
0.008875994943082333,
0.04496503248810768,
-0.04983880743384361,
0.022218676283955574,
0.046526700258255005,
0.008885668590664864,
0.010861695744097233,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/26507 | [
"Needs Triage"
] | ⚠️ CI failed on linux_arm64_wheel ⚠️
**CI failed on [linux_arm64_wheel](https://cirrus-ci.com/build/5851815137247232)** (Jun 04, 2023)
COMMENT:
## CI is no longer failing! ✅
[Successful run](https://cirrus-ci.com/build/5851815137247232) on Jun 04, 2023 | 26,507 | [
-0.018341336399316788,
-0.015954390168190002,
-0.03618701174855232,
-0.03521397337317467,
0.017949577420949936,
0.033750019967556,
0.008545922115445137,
0.046082764863967896,
-0.05027758330106735,
0.02246950939297676,
0.0464363731443882,
0.013236014172434807,
0.01599319837987423,
0.0267452... |
https://github.com/scikit-learn/scikit-learn/issues/26501 | [
"Bug",
"Needs Triage"
] | ModuleNotFoundError: No module named 'sklearn.ensemble._bagging'
### Describe the bug
ModuleNotFoundError: No module named 'sklearn.ensemble._bagging'
Above error i am gettting while using python3.7 . Please provide me with the right version of scikit-learn .Here i am using scikit-learn =0.21.3
### Steps/Code to ... | 26,501 | [
0.03190097212791443,
-0.029065536335110664,
0.010901166126132011,
-0.051432691514492035,
0.03063778020441532,
0.043899185955524445,
0.0665537491440773,
0.0210296418517828,
0.08797922730445862,
0.007519860751926899,
0.0036360465455800295,
0.07435626536607742,
-0.02702367678284645,
0.0353017... |
https://github.com/scikit-learn/scikit-learn/issues/26500 | [
"Needs Triage"
] | ⚠️ CI failed on macOS.pylatest_conda_forge_mkl ⚠️
**CI is still failing on [macOS.pylatest_conda_forge_mkl](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=55585&view=logs&j=97641769-79fb-5590-9088-a30ce9b850b9)** (Jun 05, 2023)
- test_fastica_simple[9-float32-True]
- test_fastica_simple[9-float... | 26,500 | [
-0.018342584371566772,
0.015084263868629932,
-0.04304663836956024,
-0.05141666904091835,
0.05279981717467308,
0.006797465495765209,
0.028363415971398354,
0.02820795215666294,
-0.039911773055791855,
0.007948142476379871,
0.024830704554915428,
0.03494739904999733,
-0.008649253286421299,
0.10... |
https://github.com/scikit-learn/scikit-learn/issues/26499 | [
"Needs Triage"
] | ⚠️ CI failed on Linux_Runs.pylatest_conda_forge_mkl ⚠️
**CI is still failing on [Linux_Runs.pylatest_conda_forge_mkl](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=55657&view=logs&j=dde5042c-7464-5d47-9507-31bdd2ee0a3a)** (Jun 08, 2023)
- test_fastica_simple[41-float32-False]
COMMENT:
## CI i... | 26,499 | [
-0.016698792576789856,
0.011024300940334797,
-0.029662972316145897,
-0.028009064495563507,
0.05120840296149254,
0.009421521797776222,
0.029483307152986526,
0.03300948441028595,
-0.025231098756194115,
0.020908594131469727,
0.028360474854707718,
0.03509737178683281,
0.0006826329627074301,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/26498 | [
"Needs Triage"
] | ⚠️ CI failed on linux_arm64_wheel ⚠️
**CI failed on [linux_arm64_wheel](https://cirrus-ci.com/build/4727305860284416)** (Jun 03, 2023)
COMMENT:
## CI is no longer failing! ✅
[Successful run](https://cirrus-ci.com/build/5851815137247232) on Jun 04, 2023 | 26,498 | [
-0.019999753683805466,
-0.01671716757118702,
-0.036314841359853745,
-0.029564855620265007,
0.014752587303519249,
0.03324976563453674,
0.009501783177256584,
0.04523838311433792,
-0.05520188808441162,
0.020599311217665672,
0.04752510413527489,
0.010376375168561935,
0.012388091534376144,
0.02... |
https://github.com/scikit-learn/scikit-learn/issues/26496 | [
"Needs Triage"
] | ⚠️ CI failed on linux_arm64_wheel ⚠️
**CI failed on [linux_arm64_wheel](https://cirrus-ci.com/build/4727305860284416)** (Jun 03, 2023)
COMMENT:
## CI is no longer failing! ✅
[Successful run](https://cirrus-ci.com/build/4727305860284416) on Jun 03, 2023 | 26,496 | [
-0.02165672741830349,
-0.020750664174556732,
-0.03867122530937195,
-0.03370580077171326,
0.017840534448623657,
0.03777013346552849,
0.007845178246498108,
0.04779648035764694,
-0.04969029873609543,
0.022445302456617355,
0.04716995358467102,
0.009871028363704681,
0.01089763268828392,
0.02549... |
https://github.com/scikit-learn/scikit-learn/issues/26494 | [
"New Feature",
"module:linear_model"
] | Return training loss from LogisticRegression
### Describe the workflow you want to enable
Currently there seems to be no way to retrieve the loss (or change in loss) when training a logistic regression model (`sklearn.linear_model.LogisticRegression`). If one changes the verbosity then this can be seen from the ter... | 26,494 | [
-0.037052761763334274,
0.05040183663368225,
0.03253184258937836,
0.041264671832323074,
0.05990108475089073,
0.0013743552844971418,
-0.001933172345161438,
0.028451791033148766,
0.002606332069262862,
0.008470357395708561,
0.03173832222819328,
0.045614149421453476,
-0.05344657599925995,
0.035... |
https://github.com/scikit-learn/scikit-learn/issues/26494 | [
"New Feature",
"module:linear_model"
] | Return training loss from LogisticRegression
### Describe the workflow you want to enable
Currently there seems to be no way to retrieve the loss (or change in loss) when training a logistic regression model (`sklearn.linear_model.LogisticRegression`). If one changes the verbosity then this can be seen from the ter... | 26,494 | [
-0.042469803243875504,
0.06601236760616302,
0.030889904126524925,
0.04545135051012039,
0.053908806294202805,
0.0027870123740285635,
-0.0032391115091741085,
0.021213825792074203,
-0.010314783081412315,
0.010658297687768936,
0.047760218381881714,
0.03757147118449211,
-0.05043742433190346,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/26494 | [
"New Feature",
"module:linear_model"
] | Return training loss from LogisticRegression
### Describe the workflow you want to enable
Currently there seems to be no way to retrieve the loss (or change in loss) when training a logistic regression model (`sklearn.linear_model.LogisticRegression`). If one changes the verbosity then this can be seen from the ter... | 26,494 | [
-0.03576518967747688,
0.06616435945034027,
0.030884962528944016,
0.0401579774916172,
0.050525370985269547,
-0.003640957875177264,
-0.0011246397625654936,
0.031936511397361755,
0.003068121848627925,
0.01437403541058302,
0.03773359954357147,
0.04302395507693291,
-0.05119480565190315,
0.04138... |
https://github.com/scikit-learn/scikit-learn/issues/26493 | [
"Bug"
] | Inconsitency between C-contiguous and F-contiguous arrays
### No consistency between C-contiguous and F-contiguous arrays for LinearRegression()
At least for LinearRegression() : In some edge case (when X is almost singular), there is huge difference between C-contiguous and F-contiguous arrays predictions.
- Th... | 26,493 | [
0.009875279851257801,
0.09620746225118637,
0.006904460955411196,
0.0011464350391179323,
0.054937999695539474,
-0.0009026548359543085,
0.05766007676720619,
-0.010657188482582569,
0.02108437567949295,
-0.0027747221756726503,
0.03390808403491974,
-0.005249921232461929,
0.04713102802634239,
0.... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.