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/27653 | [
"Bug",
"Needs Triage"
] | scikit-learn-1.3.2.tar.gz archive contains version 1.4.dev0
### Describe the bug
The package downloaded from [https://github.com/scikit-learn/scikit-learn/archive/1.3.2/scikit-learn-1.3.2.tar.gz](https://github.com/scikit-learn/scikit-learn/archive/1.3.2/scikit-learn-1.3.2.tar.gz)
contains version 1.4.dev0:
The... | 27,653 | [
0.0261519942432642,
-0.03655630350112915,
-0.011622763238847256,
-0.010973338969051838,
0.002871571108698845,
0.0231429785490036,
-0.013082643039524555,
0.04725732281804085,
0.05064987391233444,
-0.008027764968574047,
0.07702288776636124,
0.06997964531183243,
0.010054385289549828,
0.040477... |
https://github.com/scikit-learn/scikit-learn/issues/27652 | [
"New Feature",
"Needs Decision"
] | Add individual penalization to precision matrix in graphical_lasso.py
### Describe the workflow you want to enable
Friedman et al. (2008) describe the coordinate descent procedure used for the graphical lasso.
In the paper, there is a REMARK 2.1, which states that the objective function to be optimized can be modifi... | 27,652 | [
0.012105674482882023,
0.05597870051860809,
0.015368669293820858,
0.02498537115752697,
0.06059817224740982,
0.008663062937557697,
0.023552648723125458,
0.013242739252746105,
0.003813625080510974,
-0.00974491611123085,
-0.014361904934048653,
0.0730152502655983,
-0.05085994675755501,
-0.03651... |
https://github.com/scikit-learn/scikit-learn/issues/27652 | [
"New Feature",
"Needs Decision"
] | Add individual penalization to precision matrix in graphical_lasso.py
### Describe the workflow you want to enable
Friedman et al. (2008) describe the coordinate descent procedure used for the graphical lasso.
In the paper, there is a REMARK 2.1, which states that the objective function to be optimized can be modifi... | 27,652 | [
0.015513161197304726,
0.05399288237094879,
0.012078060768544674,
0.019662680104374886,
0.06071784347295761,
0.010975021868944168,
0.029651185497641563,
0.012432003393769264,
0.008990591391921043,
-0.008964912965893745,
-0.0200116615742445,
0.081659696996212,
-0.04396747425198555,
-0.031369... |
https://github.com/scikit-learn/scikit-learn/issues/27652 | [
"New Feature",
"Needs Decision"
] | Add individual penalization to precision matrix in graphical_lasso.py
### Describe the workflow you want to enable
Friedman et al. (2008) describe the coordinate descent procedure used for the graphical lasso.
In the paper, there is a REMARK 2.1, which states that the objective function to be optimized can be modifi... | 27,652 | [
0.025475243106484413,
0.06989872455596924,
0.019293993711471558,
0.025595450773835182,
0.05068275332450867,
0.008084060624241829,
0.029104305431246758,
0.018603160977363586,
0.01793932542204857,
-0.00015245295071508735,
-0.0013030049158260226,
0.06806953251361847,
-0.04440923407673836,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/27652 | [
"New Feature",
"Needs Decision"
] | Add individual penalization to precision matrix in graphical_lasso.py
### Describe the workflow you want to enable
Friedman et al. (2008) describe the coordinate descent procedure used for the graphical lasso.
In the paper, there is a REMARK 2.1, which states that the objective function to be optimized can be modifi... | 27,652 | [
0.01462460309267044,
0.04956125468015671,
0.017813879996538162,
0.026141872629523277,
0.05734260752797127,
0.008427513763308525,
0.026039913296699524,
0.015345193445682526,
0.011225483380258083,
-0.007914476096630096,
-0.012289470061659813,
0.06864865869283676,
-0.044639576226472855,
-0.03... |
https://github.com/scikit-learn/scikit-learn/issues/27644 | [
"Bug",
"Needs Triage"
] | installing scikit-learn in alpine
### Describe the bug
i am trying to install scikit-learn in an alpine image, python:3.9-alpine, but it is failing
This is my dockerfile
```
FROM python:3.9-alpine
RUN apk --update add gcc build-base freetype-dev libpng-dev openblas-dev py3-scikit-learn
RUN pip install scikit... | 27,644 | [
-0.007266470696777105,
-0.04929341375827789,
-0.03424202650785446,
-0.031675901263952255,
0.052822694182395935,
0.010230626910924911,
0.0014330726116895676,
0.026745017617940903,
0.018626583740115166,
-0.011720956303179264,
0.024709906429052353,
0.07704407721757889,
-0.009682873263955116,
... |
https://github.com/scikit-learn/scikit-learn/issues/27643 | [
"Documentation"
] | Sphinx version information in "Building the documentation" section needs reevaluation
### Describe the issue linked to the documentation
At the bottom of the ["Building the documentation" section](https://github.com/scikit-learn/scikit-learn/blob/main/doc/developers/contributing.rst#building-the-documentation) there ... | 27,643 | [
0.05512457713484764,
-0.018952712416648865,
-0.01817764900624752,
-0.03332870081067085,
-0.010275785811245441,
0.031371187418699265,
-0.0014480805257335305,
0.02750970609486103,
0.015111908316612244,
-0.025672724470496178,
0.04282756149768829,
0.05540911480784416,
0.039348822087049484,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/27643 | [
"Documentation"
] | Sphinx version information in "Building the documentation" section needs reevaluation
### Describe the issue linked to the documentation
At the bottom of the ["Building the documentation" section](https://github.com/scikit-learn/scikit-learn/blob/main/doc/developers/contributing.rst#building-the-documentation) there ... | 27,643 | [
0.050100021064281464,
-0.024065567180514336,
-0.012537223286926746,
-0.03204714506864548,
-0.007297490257769823,
0.02900109812617302,
0.011573332361876965,
0.02954493835568428,
0.024477312341332436,
-0.0346195288002491,
0.03367199748754501,
0.0523509681224823,
0.031104251742362976,
-0.0566... |
https://github.com/scikit-learn/scikit-learn/issues/27643 | [
"Documentation"
] | Sphinx version information in "Building the documentation" section needs reevaluation
### Describe the issue linked to the documentation
At the bottom of the ["Building the documentation" section](https://github.com/scikit-learn/scikit-learn/blob/main/doc/developers/contributing.rst#building-the-documentation) there ... | 27,643 | [
0.04969879239797592,
-0.02245534025132656,
-0.017205718904733658,
-0.03108149766921997,
-0.010800876654684544,
0.02958308532834053,
0.0032807127572596073,
0.038746993988752365,
0.011246319860219955,
-0.036067571491003036,
0.041213326156139374,
0.05194515734910965,
0.031550053507089615,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/27643 | [
"Documentation"
] | Sphinx version information in "Building the documentation" section needs reevaluation
### Describe the issue linked to the documentation
At the bottom of the ["Building the documentation" section](https://github.com/scikit-learn/scikit-learn/blob/main/doc/developers/contributing.rst#building-the-documentation) there ... | 27,643 | [
0.04644704610109329,
-0.01580028608441353,
-0.016611248254776,
-0.03184288367629051,
-0.006662706378847361,
0.03629366680979729,
0.004086550325155258,
0.03557296097278595,
0.0138957304880023,
-0.033040449023246765,
0.04387729987502098,
0.06087052449584007,
0.02494879812002182,
-0.060652781... |
https://github.com/scikit-learn/scikit-learn/issues/27643 | [
"Documentation"
] | Sphinx version information in "Building the documentation" section needs reevaluation
### Describe the issue linked to the documentation
At the bottom of the ["Building the documentation" section](https://github.com/scikit-learn/scikit-learn/blob/main/doc/developers/contributing.rst#building-the-documentation) there ... | 27,643 | [
0.04918079823255539,
-0.02088283561170101,
-0.01746816188097,
-0.028380047529935837,
-0.008828671649098396,
0.03161522001028061,
0.002078964142128825,
0.03170624002814293,
0.007002434693276882,
-0.03045083023607731,
0.042782772332429886,
0.0529332160949707,
0.03068222850561142,
-0.05715101... |
https://github.com/scikit-learn/scikit-learn/issues/27643 | [
"Documentation"
] | Sphinx version information in "Building the documentation" section needs reevaluation
### Describe the issue linked to the documentation
At the bottom of the ["Building the documentation" section](https://github.com/scikit-learn/scikit-learn/blob/main/doc/developers/contributing.rst#building-the-documentation) there ... | 27,643 | [
0.04820756986737251,
-0.02995447628200054,
-0.012634024024009705,
-0.03280533477663994,
-0.008165359497070312,
0.028059497475624084,
0.00989756640046835,
0.031057259067893028,
0.022210463881492615,
-0.03198057785630226,
0.034562744200229645,
0.055313125252723694,
0.03401971980929375,
-0.05... |
https://github.com/scikit-learn/scikit-learn/issues/27643 | [
"Documentation"
] | Sphinx version information in "Building the documentation" section needs reevaluation
### Describe the issue linked to the documentation
At the bottom of the ["Building the documentation" section](https://github.com/scikit-learn/scikit-learn/blob/main/doc/developers/contributing.rst#building-the-documentation) there ... | 27,643 | [
0.052198491990566254,
-0.017098212614655495,
-0.01672610454261303,
-0.02854149043560028,
-0.01065651886165142,
0.027042658999562263,
-0.0008831423474475741,
0.03439614921808243,
0.007438104599714279,
-0.033822182565927505,
0.04178659990429878,
0.05078478530049324,
0.034548569470644,
-0.060... |
https://github.com/scikit-learn/scikit-learn/issues/27643 | [
"Documentation"
] | Sphinx version information in "Building the documentation" section needs reevaluation
### Describe the issue linked to the documentation
At the bottom of the ["Building the documentation" section](https://github.com/scikit-learn/scikit-learn/blob/main/doc/developers/contributing.rst#building-the-documentation) there ... | 27,643 | [
0.04197869822382927,
-0.013608970679342747,
-0.014519106596708298,
-0.03061208687722683,
-0.010865000076591969,
0.029532654210925102,
-0.003011864610016346,
0.023288266733288765,
-0.005122276954352856,
-0.03795954957604408,
0.03927985951304436,
0.04129145294427872,
0.039333246648311615,
-0... |
https://github.com/scikit-learn/scikit-learn/issues/27643 | [
"Documentation"
] | Sphinx version information in "Building the documentation" section needs reevaluation
### Describe the issue linked to the documentation
At the bottom of the ["Building the documentation" section](https://github.com/scikit-learn/scikit-learn/blob/main/doc/developers/contributing.rst#building-the-documentation) there ... | 27,643 | [
0.04470750689506531,
-0.009832080453634262,
-0.013692742213606834,
-0.033005330711603165,
-0.010457353666424751,
0.028549835085868835,
-0.002853809855878353,
0.025123585015535355,
-0.007957905530929565,
-0.037422556430101395,
0.043028563261032104,
0.043410371989011765,
0.039346374571323395,
... |
https://github.com/scikit-learn/scikit-learn/issues/27643 | [
"Documentation"
] | Sphinx version information in "Building the documentation" section needs reevaluation
### Describe the issue linked to the documentation
At the bottom of the ["Building the documentation" section](https://github.com/scikit-learn/scikit-learn/blob/main/doc/developers/contributing.rst#building-the-documentation) there ... | 27,643 | [
0.04902590811252594,
-0.025083744898438454,
-0.020039621740579605,
-0.032613400369882584,
-0.008601169101893902,
0.03641675040125847,
0.006214567460119724,
0.03462526202201843,
0.010057538747787476,
-0.03692134842276573,
0.041734728962183,
0.052098240703344345,
0.03262520954012871,
-0.0607... |
https://github.com/scikit-learn/scikit-learn/issues/27629 | [
"New Feature",
"help wanted",
"Hard"
] | Please provide option to set unknown_values during test time to same as encoded min_frequency in OrdinalEncoder(Infrequent categories)
### Describe the workflow you want to enable
It seems that OneHotEncoder has a parameter for setting` handle_unknown='infrequent_if_exist'` but the same is missing in OrdinalEncode... | 27,629 | [
-0.042284756898880005,
0.11906927824020386,
-0.012284948490560055,
-0.023618575185537338,
0.035100772976875305,
0.008131559938192368,
-0.002953385701403022,
0.07073294371366501,
-0.09824035316705704,
0.0545855313539505,
0.08666278421878815,
0.005357528105378151,
-0.057615168392658234,
0.04... |
https://github.com/scikit-learn/scikit-learn/issues/27629 | [
"New Feature",
"help wanted",
"Hard"
] | Please provide option to set unknown_values during test time to same as encoded min_frequency in OrdinalEncoder(Infrequent categories)
### Describe the workflow you want to enable
It seems that OneHotEncoder has a parameter for setting` handle_unknown='infrequent_if_exist'` but the same is missing in OrdinalEncode... | 27,629 | [
-0.0340970978140831,
0.1337735503911972,
-0.011816052719950676,
-0.02028052881360054,
0.037579551339149475,
0.01249056588858366,
-0.009523662738502026,
0.07577712833881378,
-0.09208831936120987,
0.04964581876993179,
0.09327222406864166,
0.022612573578953743,
-0.0492134727537632,
0.04749726... |
https://github.com/scikit-learn/scikit-learn/issues/27629 | [
"New Feature",
"help wanted",
"Hard"
] | Please provide option to set unknown_values during test time to same as encoded min_frequency in OrdinalEncoder(Infrequent categories)
### Describe the workflow you want to enable
It seems that OneHotEncoder has a parameter for setting` handle_unknown='infrequent_if_exist'` but the same is missing in OrdinalEncode... | 27,629 | [
-0.03786807134747505,
0.12620443105697632,
0.0005168808274902403,
-0.0303578432649374,
0.030096547678112984,
0.0070700878277421,
0.012293338775634766,
0.064077228307724,
-0.09374168515205383,
0.04866901412606239,
0.09107976406812668,
0.010006492957472801,
-0.044978465884923935,
0.048410080... |
https://github.com/scikit-learn/scikit-learn/issues/27626 | [
"Bug"
] | Isolation Forest Bug with Sparse Matrix and Contamination as Float
### Describe the bug
### Environment:
```
Python 3.11 and 3.8
Scikit-learn library 1.3.1
Isolation Forest algorithm
Sparse matrix input (tested csr and csc)
Contamination parameter set as a float
```
### Bug Summary:
When using the Is... | 27,626 | [
0.026396317407488823,
-0.0031782016158103943,
0.04466690495610237,
0.0049442872405052185,
0.07909516990184784,
-0.02397998794913292,
0.0168137289583683,
0.006582763511687517,
-0.0050095804035663605,
0.01579722948372364,
0.027072306722402573,
0.0031962161883711815,
0.009377808310091496,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27626 | [
"Bug"
] | Isolation Forest Bug with Sparse Matrix and Contamination as Float
### Describe the bug
### Environment:
```
Python 3.11 and 3.8
Scikit-learn library 1.3.1
Isolation Forest algorithm
Sparse matrix input (tested csr and csc)
Contamination parameter set as a float
```
### Bug Summary:
When using the Is... | 27,626 | [
0.026396317407488823,
-0.0031782016158103943,
0.04466690495610237,
0.0049442872405052185,
0.07909516990184784,
-0.02397998794913292,
0.0168137289583683,
0.006582763511687517,
-0.0050095804035663605,
0.01579722948372364,
0.027072306722402573,
0.0031962161883711815,
0.009377808310091496,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27623 | [
"Documentation"
] | DOC link benchmark results site
### Describe the issue linked to the documentation
Mention https://scikit-learn.org/scikit-learn-benchmarks somewhere in our docs. I could only find it in the Readme.
### Suggest a potential alternative/fix
_No response_
COMMENT:
I'm on it! | 27,623 | [
0.0025614267215132713,
-0.03515530750155449,
0.016751110553741455,
0.02762654423713684,
-0.0015687965787947178,
-0.006744774524122477,
0.0476076640188694,
0.05654138699173927,
0.008595477789640427,
-0.04411504790186882,
0.041718728840351105,
0.04542398825287819,
0.04733993113040924,
-0.008... |
https://github.com/scikit-learn/scikit-learn/issues/27623 | [
"Documentation"
] | DOC link benchmark results site
### Describe the issue linked to the documentation
Mention https://scikit-learn.org/scikit-learn-benchmarks somewhere in our docs. I could only find it in the Readme.
### Suggest a potential alternative/fix
_No response_
COMMENT:
It is already mentioned in https://scikit-learn.org/d... | 27,623 | [
-0.010337131097912788,
-0.04878649115562439,
0.010578314773738384,
0.00847818423062563,
-0.009764307178556919,
-0.005207785405218601,
0.053887031972408295,
0.043581731617450714,
0.019513066858053207,
-0.049159035086631775,
0.030646035447716713,
0.052552249282598495,
0.05024474486708641,
-0... |
https://github.com/scikit-learn/scikit-learn/issues/27623 | [
"Documentation"
] | DOC link benchmark results site
### Describe the issue linked to the documentation
Mention https://scikit-learn.org/scikit-learn-benchmarks somewhere in our docs. I could only find it in the Readme.
### Suggest a potential alternative/fix
_No response_
COMMENT:
I was not able to find that link. It appears as one o... | 27,623 | [
0.008825484663248062,
-0.03513169288635254,
0.0071576302871108055,
0.02293681912124157,
-0.007943418808281422,
-0.004328249953687191,
0.05756606534123421,
0.042281560599803925,
0.007594316266477108,
-0.03919259086251259,
0.020141232758760452,
0.04131368547677994,
0.037592366337776184,
-0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27623 | [
"Documentation"
] | DOC link benchmark results site
### Describe the issue linked to the documentation
Mention https://scikit-learn.org/scikit-learn-benchmarks somewhere in our docs. I could only find it in the Readme.
### Suggest a potential alternative/fix
_No response_
COMMENT:
I think it makes sense to have it in the contributing... | 27,623 | [
0.01612039841711521,
0.013041752390563488,
-0.0011756164021790028,
0.007847555913031101,
0.018888356164097786,
-0.007878378964960575,
0.014582715928554535,
0.06017392873764038,
-0.021702736616134644,
-0.06705319881439209,
-0.020189322531223297,
0.06545562297105789,
0.03998208045959473,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27623 | [
"Documentation"
] | DOC link benchmark results site
### Describe the issue linked to the documentation
Mention https://scikit-learn.org/scikit-learn-benchmarks somewhere in our docs. I could only find it in the Readme.
### Suggest a potential alternative/fix
_No response_
COMMENT:
I close as we seem happy with the place of the link, ... | 27,623 | [
0.028225192800164223,
-0.018621137365698814,
0.00618608808144927,
0.01715776138007641,
0.01298097986727953,
-0.0008335667080245912,
0.07205616682767868,
0.03497316315770149,
0.01764354482293129,
-0.04619181528687477,
0.0036865409929305315,
0.05379772558808327,
0.03773783892393112,
-0.03899... |
https://github.com/scikit-learn/scikit-learn/issues/27621 | [
"Bug"
] | euclidean_distances with float64 x,y and float32 xx and yy
### Describe the bug
When running `euclidean_distances` I think it is possible to get to [this](https://github.com/scikit-learn/scikit-learn/blob/d99b728b3a7952b2111cf5e0cb5d14f92c6f3a80/sklearn/metrics/pairwise.py#L380) line of code with `XX` being `None`. T... | 27,621 | [
-0.0030945762991905212,
-0.02630740962922573,
0.016978101804852486,
0.017123516649007797,
0.06199396401643753,
0.04301944375038147,
0.06368796527385712,
0.06173490732908249,
0.021424708887934685,
-0.042945560067892075,
-0.00354430777952075,
-0.02713693492114544,
0.03255348652601242,
-0.043... |
https://github.com/scikit-learn/scikit-learn/issues/27621 | [
"Bug"
] | euclidean_distances with float64 x,y and float32 xx and yy
### Describe the bug
When running `euclidean_distances` I think it is possible to get to [this](https://github.com/scikit-learn/scikit-learn/blob/d99b728b3a7952b2111cf5e0cb5d14f92c6f3a80/sklearn/metrics/pairwise.py#L380) line of code with `XX` being `None`. T... | 27,621 | [
-0.0030945762991905212,
-0.02630740962922573,
0.016978101804852486,
0.017123516649007797,
0.06199396401643753,
0.04301944375038147,
0.06368796527385712,
0.06173490732908249,
0.021424708887934685,
-0.042945560067892075,
-0.00354430777952075,
-0.02713693492114544,
0.03255348652601242,
-0.043... |
https://github.com/scikit-learn/scikit-learn/issues/27621 | [
"Bug"
] | euclidean_distances with float64 x,y and float32 xx and yy
### Describe the bug
When running `euclidean_distances` I think it is possible to get to [this](https://github.com/scikit-learn/scikit-learn/blob/d99b728b3a7952b2111cf5e0cb5d14f92c6f3a80/sklearn/metrics/pairwise.py#L380) line of code with `XX` being `None`. T... | 27,621 | [
-0.0030945762991905212,
-0.02630740962922573,
0.016978101804852486,
0.017123516649007797,
0.06199396401643753,
0.04301944375038147,
0.06368796527385712,
0.06173490732908249,
0.021424708887934685,
-0.042945560067892075,
-0.00354430777952075,
-0.02713693492114544,
0.03255348652601242,
-0.043... |
https://github.com/scikit-learn/scikit-learn/issues/27620 | [
"Bug"
] | sklearn PCA rotates a single vector
### Describe the bug
The issue we recently discovered is that sklearn PCA rotates the input when only a single variable is fed into the model.
I am aware there are infinite rotations when there is a single vector fed into the model, however, the output from PCA should intuit... | 27,620 | [
-0.026665471494197845,
0.0005112471408210695,
0.002707923064008355,
0.0058309463784098625,
0.07041729986667633,
-0.0045676021836698055,
0.007962208241224289,
-0.013250729069113731,
-0.027478091418743134,
-0.00670721847563982,
0.035950519144535065,
0.08459474891424179,
0.04363005608320236,
... |
https://github.com/scikit-learn/scikit-learn/issues/27620 | [
"Bug"
] | sklearn PCA rotates a single vector
### Describe the bug
The issue we recently discovered is that sklearn PCA rotates the input when only a single variable is fed into the model.
I am aware there are infinite rotations when there is a single vector fed into the model, however, the output from PCA should intuit... | 27,620 | [
-0.026665471494197845,
0.0005112471408210695,
0.002707923064008355,
0.0058309463784098625,
0.07041729986667633,
-0.0045676021836698055,
0.007962208241224289,
-0.013250729069113731,
-0.027478091418743134,
-0.00670721847563982,
0.035950519144535065,
0.08459474891424179,
0.04363005608320236,
... |
https://github.com/scikit-learn/scikit-learn/issues/27620 | [
"Bug"
] | sklearn PCA rotates a single vector
### Describe the bug
The issue we recently discovered is that sklearn PCA rotates the input when only a single variable is fed into the model.
I am aware there are infinite rotations when there is a single vector fed into the model, however, the output from PCA should intuit... | 27,620 | [
-0.026665471494197845,
0.0005112471408210695,
0.002707923064008355,
0.0058309463784098625,
0.07041729986667633,
-0.0045676021836698055,
0.007962208241224289,
-0.013250729069113731,
-0.027478091418743134,
-0.00670721847563982,
0.035950519144535065,
0.08459474891424179,
0.04363005608320236,
... |
https://github.com/scikit-learn/scikit-learn/issues/27620 | [
"Bug"
] | sklearn PCA rotates a single vector
### Describe the bug
The issue we recently discovered is that sklearn PCA rotates the input when only a single variable is fed into the model.
I am aware there are infinite rotations when there is a single vector fed into the model, however, the output from PCA should intuit... | 27,620 | [
-0.026665471494197845,
0.0005112471408210695,
0.002707923064008355,
0.0058309463784098625,
0.07041729986667633,
-0.0045676021836698055,
0.007962208241224289,
-0.013250729069113731,
-0.027478091418743134,
-0.00670721847563982,
0.035950519144535065,
0.08459474891424179,
0.04363005608320236,
... |
https://github.com/scikit-learn/scikit-learn/issues/27620 | [
"Bug"
] | sklearn PCA rotates a single vector
### Describe the bug
The issue we recently discovered is that sklearn PCA rotates the input when only a single variable is fed into the model.
I am aware there are infinite rotations when there is a single vector fed into the model, however, the output from PCA should intuit... | 27,620 | [
-0.026665471494197845,
0.0005112471408210695,
0.002707923064008355,
0.0058309463784098625,
0.07041729986667633,
-0.0045676021836698055,
0.007962208241224289,
-0.013250729069113731,
-0.027478091418743134,
-0.00670721847563982,
0.035950519144535065,
0.08459474891424179,
0.04363005608320236,
... |
https://github.com/scikit-learn/scikit-learn/issues/27620 | [
"Bug"
] | sklearn PCA rotates a single vector
### Describe the bug
The issue we recently discovered is that sklearn PCA rotates the input when only a single variable is fed into the model.
I am aware there are infinite rotations when there is a single vector fed into the model, however, the output from PCA should intuit... | 27,620 | [
-0.026665471494197845,
0.0005112471408210695,
0.002707923064008355,
0.0058309463784098625,
0.07041729986667633,
-0.0045676021836698055,
0.007962208241224289,
-0.013250729069113731,
-0.027478091418743134,
-0.00670721847563982,
0.035950519144535065,
0.08459474891424179,
0.04363005608320236,
... |
https://github.com/scikit-learn/scikit-learn/issues/27620 | [
"Bug"
] | sklearn PCA rotates a single vector
### Describe the bug
The issue we recently discovered is that sklearn PCA rotates the input when only a single variable is fed into the model.
I am aware there are infinite rotations when there is a single vector fed into the model, however, the output from PCA should intuit... | 27,620 | [
-0.026665471494197845,
0.0005112471408210695,
0.002707923064008355,
0.0058309463784098625,
0.07041729986667633,
-0.0045676021836698055,
0.007962208241224289,
-0.013250729069113731,
-0.027478091418743134,
-0.00670721847563982,
0.035950519144535065,
0.08459474891424179,
0.04363005608320236,
... |
https://github.com/scikit-learn/scikit-learn/issues/27620 | [
"Bug"
] | sklearn PCA rotates a single vector
### Describe the bug
The issue we recently discovered is that sklearn PCA rotates the input when only a single variable is fed into the model.
I am aware there are infinite rotations when there is a single vector fed into the model, however, the output from PCA should intuit... | 27,620 | [
-0.026665471494197845,
0.0005112471408210695,
0.002707923064008355,
0.0058309463784098625,
0.07041729986667633,
-0.0045676021836698055,
0.007962208241224289,
-0.013250729069113731,
-0.027478091418743134,
-0.00670721847563982,
0.035950519144535065,
0.08459474891424179,
0.04363005608320236,
... |
https://github.com/scikit-learn/scikit-learn/issues/27620 | [
"Bug"
] | sklearn PCA rotates a single vector
### Describe the bug
The issue we recently discovered is that sklearn PCA rotates the input when only a single variable is fed into the model.
I am aware there are infinite rotations when there is a single vector fed into the model, however, the output from PCA should intuit... | 27,620 | [
-0.026665471494197845,
0.0005112471408210695,
0.002707923064008355,
0.0058309463784098625,
0.07041729986667633,
-0.0045676021836698055,
0.007962208241224289,
-0.013250729069113731,
-0.027478091418743134,
-0.00670721847563982,
0.035950519144535065,
0.08459474891424179,
0.04363005608320236,
... |
https://github.com/scikit-learn/scikit-learn/issues/27617 | [
"frontend",
"module:base"
] | Diagrams displayed using dark mode in light mode editor/notebook
I saw a couple of time that the dark mode to display the diagram is activated in my light mode editor or notebook:
I did not follow the pul... | 27,617 | [
0.02249952033162117,
0.025697294622659683,
0.006483799312263727,
-0.038759518414735794,
-0.013196351937949657,
-0.0037921022158116102,
0.09336298704147339,
0.07760938256978989,
-0.02842777408659458,
-0.05584641173481941,
-0.028511548414826393,
0.005326779093593359,
0.0091154919937253,
0.00... |
https://github.com/scikit-learn/scikit-learn/issues/27617 | [
"frontend",
"module:base"
] | Diagrams displayed using dark mode in light mode editor/notebook
I saw a couple of time that the dark mode to display the diagram is activated in my light mode editor or notebook:
I did not follow the pul... | 27,617 | [
0.006560459733009338,
-0.00835002213716507,
-0.003485537599772215,
0.002183895790949464,
-0.030184045433998108,
-0.014946423470973969,
0.06863000988960266,
0.05811567232012749,
-0.01896945759654045,
-0.04320186376571655,
-0.0010330112418159842,
0.005135559011250734,
0.0012378558749333024,
... |
https://github.com/scikit-learn/scikit-learn/issues/27617 | [
"frontend",
"module:base"
] | Diagrams displayed using dark mode in light mode editor/notebook
I saw a couple of time that the dark mode to display the diagram is activated in my light mode editor or notebook:
I did not follow the pul... | 27,617 | [
0.00679963082075119,
-0.01670314185321331,
-0.01966719888150692,
-0.011026942171156406,
-0.040161751210689545,
-0.02338169328868389,
0.07653700560331345,
0.04915871098637581,
-0.041004929691553116,
-0.022502658888697624,
-0.017718613147735596,
0.004694742616266012,
0.008619519881904125,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/27617 | [
"frontend",
"module:base"
] | Diagrams displayed using dark mode in light mode editor/notebook
I saw a couple of time that the dark mode to display the diagram is activated in my light mode editor or notebook:
I did not follow the pul... | 27,617 | [
0.006507416721433401,
-0.00975745264440775,
-0.01845523528754711,
-0.008821356110274792,
-0.0270413588732481,
-0.0017122201388701797,
0.07535351067781448,
0.06403893977403641,
-0.03438665345311165,
-0.04103410243988037,
-0.004638294223695993,
0.020629841834306717,
0.006657759193331003,
-0.... |
https://github.com/scikit-learn/scikit-learn/issues/27617 | [
"frontend",
"module:base"
] | Diagrams displayed using dark mode in light mode editor/notebook
I saw a couple of time that the dark mode to display the diagram is activated in my light mode editor or notebook:
I did not follow the pul... | 27,617 | [
-0.0028643568512052298,
-0.028653547167778015,
-0.024452922865748405,
-0.0028983107767999172,
-0.03328855335712433,
0.001323523698374629,
0.07714881747961044,
0.06457093358039856,
-0.027342746034264565,
-0.025842688977718353,
0.006012478843331337,
0.017598174512386322,
0.0015793712809681892,... |
https://github.com/scikit-learn/scikit-learn/issues/27615 | [
"Performance",
"cython"
] | Cython: Use boundscheck(False) for faster access
When building scikit-learn on the Windows CI (with cython 0.29.36), I see many lines such as:
```
warning: sklearn\cluster\_k_means_lloyd.pyx:403:52: Use boundscheck(False) for faster access
```
See for instance: https://dev.azure.com/scikit-learn/scikit-learn/_... | 27,615 | [
-0.046572960913181305,
-0.02095228247344494,
-0.03315629065036774,
0.010385246947407722,
0.015506830997765064,
0.03191565349698067,
0.0525863952934742,
-0.016442066058516502,
0.048191215842962265,
0.0018659562338143587,
0.024219568818807602,
0.022337986156344414,
-0.006189393345266581,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27615 | [
"Performance",
"cython"
] | Cython: Use boundscheck(False) for faster access
When building scikit-learn on the Windows CI (with cython 0.29.36), I see many lines such as:
```
warning: sklearn\cluster\_k_means_lloyd.pyx:403:52: Use boundscheck(False) for faster access
```
See for instance: https://dev.azure.com/scikit-learn/scikit-learn/_... | 27,615 | [
-0.04441074654459953,
-0.01998654380440712,
-0.03853936493396759,
-0.0016035172156989574,
0.020521631464362144,
0.018769055604934692,
0.04538513720035553,
-0.01569058932363987,
0.041662972420454025,
0.004330137278884649,
0.021730512380599976,
0.0258337389677763,
-0.005384267773479223,
0.01... |
https://github.com/scikit-learn/scikit-learn/issues/27615 | [
"Performance",
"cython"
] | Cython: Use boundscheck(False) for faster access
When building scikit-learn on the Windows CI (with cython 0.29.36), I see many lines such as:
```
warning: sklearn\cluster\_k_means_lloyd.pyx:403:52: Use boundscheck(False) for faster access
```
See for instance: https://dev.azure.com/scikit-learn/scikit-learn/_... | 27,615 | [
-0.04440870136022568,
-0.009834319353103638,
-0.03620172664523125,
0.007828851230442524,
0.024437488988041878,
0.015894263982772827,
0.046549174934625626,
-0.0040843612514436245,
0.04154571518301964,
0.0038026536349207163,
0.021787386387586594,
0.02971637435257435,
-0.0121841449290514,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27615 | [
"Performance",
"cython"
] | Cython: Use boundscheck(False) for faster access
When building scikit-learn on the Windows CI (with cython 0.29.36), I see many lines such as:
```
warning: sklearn\cluster\_k_means_lloyd.pyx:403:52: Use boundscheck(False) for faster access
```
See for instance: https://dev.azure.com/scikit-learn/scikit-learn/_... | 27,615 | [
-0.03714461997151375,
-0.03226412832736969,
-0.033274196088314056,
0.009906240738928318,
0.02907107211649418,
0.0178321935236454,
0.047665778547525406,
-0.01011070515960455,
0.039956413209438324,
0.007259283680468798,
0.01928357407450676,
0.026516268029808998,
-0.008093748241662979,
0.0051... |
https://github.com/scikit-learn/scikit-learn/issues/27609 | [
"New Feature"
] | Add a version of `GenericUnivariateSelect`/`SelectPercentile`/`SelectKBest` that allows input of X with missing values and `y=None`.
### Describe the workflow you want to enable
- Select features by the percentage of missing values of X
- Select features only by statistical properties of X before y is available
###... | 27,609 | [
0.02344251610338688,
0.08403047919273376,
0.048364896327257156,
-0.04517870023846626,
0.04582761600613594,
0.026385800912976265,
-0.0060984003357589245,
0.01659928821027279,
0.03341089189052582,
-0.01417620200663805,
0.04325571283698082,
0.02264348976314068,
-0.02116876095533371,
0.0394306... |
https://github.com/scikit-learn/scikit-learn/issues/27609 | [
"New Feature"
] | Add a version of `GenericUnivariateSelect`/`SelectPercentile`/`SelectKBest` that allows input of X with missing values and `y=None`.
### Describe the workflow you want to enable
- Select features by the percentage of missing values of X
- Select features only by statistical properties of X before y is available
###... | 27,609 | [
0.006526786834001541,
0.10600209981203079,
0.03493232652544975,
-0.04664135351777077,
0.04392474889755249,
0.022665411233901978,
-0.0052906665951013565,
0.01687159389257431,
0.018549958243966103,
-0.008572828955948353,
0.03461802750825882,
0.007563459221273661,
-0.024106789380311966,
0.040... |
https://github.com/scikit-learn/scikit-learn/issues/27609 | [
"New Feature"
] | Add a version of `GenericUnivariateSelect`/`SelectPercentile`/`SelectKBest` that allows input of X with missing values and `y=None`.
### Describe the workflow you want to enable
- Select features by the percentage of missing values of X
- Select features only by statistical properties of X before y is available
###... | 27,609 | [
0.011946415528655052,
0.10007856041193008,
0.03846238926053047,
-0.042032014578580856,
0.044368941336870193,
0.026673709973692894,
-0.012207315303385258,
0.021038517355918884,
0.021707195788621902,
-0.009981414303183556,
0.03594345226883888,
0.02696295455098152,
-0.02555115520954132,
0.036... |
https://github.com/scikit-learn/scikit-learn/issues/27609 | [
"New Feature"
] | Add a version of `GenericUnivariateSelect`/`SelectPercentile`/`SelectKBest` that allows input of X with missing values and `y=None`.
### Describe the workflow you want to enable
- Select features by the percentage of missing values of X
- Select features only by statistical properties of X before y is available
###... | 27,609 | [
0.015898020938038826,
0.09954372048377991,
0.039681416004896164,
-0.04486193135380745,
0.04664873331785202,
0.0216643288731575,
-0.005773134063929319,
0.014743565581738949,
0.02111172489821911,
-0.012725399807095528,
0.039115749299526215,
0.023159483447670937,
-0.0218772292137146,
0.036921... |
https://github.com/scikit-learn/scikit-learn/issues/27609 | [
"New Feature"
] | Add a version of `GenericUnivariateSelect`/`SelectPercentile`/`SelectKBest` that allows input of X with missing values and `y=None`.
### Describe the workflow you want to enable
- Select features by the percentage of missing values of X
- Select features only by statistical properties of X before y is available
###... | 27,609 | [
0.020043784752488136,
0.10701362788677216,
0.040213461965322495,
-0.04681776091456413,
0.04425796866416931,
0.022064657881855965,
-0.0024399554822593927,
0.011173471808433533,
0.020829975605010986,
-0.008550800383090973,
0.04633735120296478,
0.024864843115210533,
-0.01600201614201069,
0.03... |
https://github.com/scikit-learn/scikit-learn/issues/27609 | [
"New Feature"
] | Add a version of `GenericUnivariateSelect`/`SelectPercentile`/`SelectKBest` that allows input of X with missing values and `y=None`.
### Describe the workflow you want to enable
- Select features by the percentage of missing values of X
- Select features only by statistical properties of X before y is available
###... | 27,609 | [
0.016091683879494667,
0.10750802606344223,
0.035220447927713394,
-0.04142208769917488,
0.04535854235291481,
0.030053328722715378,
-0.014251895248889923,
0.02094823308289051,
0.01902349293231964,
-0.009443040005862713,
0.035193342715501785,
0.024560727179050446,
-0.022633034735918045,
0.032... |
https://github.com/scikit-learn/scikit-learn/issues/27609 | [
"New Feature"
] | Add a version of `GenericUnivariateSelect`/`SelectPercentile`/`SelectKBest` that allows input of X with missing values and `y=None`.
### Describe the workflow you want to enable
- Select features by the percentage of missing values of X
- Select features only by statistical properties of X before y is available
###... | 27,609 | [
0.01774211786687374,
0.09961897134780884,
0.03892386704683304,
-0.04133932292461395,
0.048062533140182495,
0.020222559571266174,
-0.0065257353708148,
0.016934171319007874,
0.01567586325109005,
-0.016680873930454254,
0.03944719582796097,
0.02536954917013645,
-0.02186180092394352,
0.03556057... |
https://github.com/scikit-learn/scikit-learn/issues/27609 | [
"New Feature"
] | Add a version of `GenericUnivariateSelect`/`SelectPercentile`/`SelectKBest` that allows input of X with missing values and `y=None`.
### Describe the workflow you want to enable
- Select features by the percentage of missing values of X
- Select features only by statistical properties of X before y is available
###... | 27,609 | [
0.014170120470225811,
0.09997599571943283,
0.03597604110836983,
-0.042960185557603836,
0.0472811721265316,
0.0258193202316761,
-0.012326933443546295,
0.014679527841508389,
0.020306410267949104,
-0.014428517781198025,
0.03687293827533722,
0.023947978392243385,
-0.019093960523605347,
0.03045... |
https://github.com/scikit-learn/scikit-learn/issues/27609 | [
"New Feature"
] | Add a version of `GenericUnivariateSelect`/`SelectPercentile`/`SelectKBest` that allows input of X with missing values and `y=None`.
### Describe the workflow you want to enable
- Select features by the percentage of missing values of X
- Select features only by statistical properties of X before y is available
###... | 27,609 | [
0.010862776078283787,
0.09661830216646194,
0.04272700846195221,
-0.042948875576257706,
0.043890174478292465,
0.02916305512189865,
0.006183203309774399,
0.018351249396800995,
0.029288213700056076,
-0.010305175557732582,
0.05029413104057312,
0.03883131965994835,
-0.017756247892975807,
0.0552... |
https://github.com/scikit-learn/scikit-learn/issues/27609 | [
"New Feature"
] | Add a version of `GenericUnivariateSelect`/`SelectPercentile`/`SelectKBest` that allows input of X with missing values and `y=None`.
### Describe the workflow you want to enable
- Select features by the percentage of missing values of X
- Select features only by statistical properties of X before y is available
###... | 27,609 | [
0.017732612788677216,
0.08851299434900284,
0.044458240270614624,
-0.04116975516080856,
0.04686858505010605,
0.024821871891617775,
-0.007191845215857029,
0.01547938957810402,
0.03707485646009445,
-0.013991464860737324,
0.03843514621257782,
0.02819133922457695,
-0.023278284817934036,
0.03810... |
https://github.com/scikit-learn/scikit-learn/issues/27609 | [
"New Feature"
] | Add a version of `GenericUnivariateSelect`/`SelectPercentile`/`SelectKBest` that allows input of X with missing values and `y=None`.
### Describe the workflow you want to enable
- Select features by the percentage of missing values of X
- Select features only by statistical properties of X before y is available
###... | 27,609 | [
0.017492035403847694,
0.09195747971534729,
0.0446673147380352,
-0.04192290082573891,
0.04616289213299751,
0.024107763543725014,
-0.007325227838009596,
0.015527415089309216,
0.03455575928092003,
-0.014391194097697735,
0.039448853582143784,
0.02700488269329071,
-0.02349220961332321,
0.036778... |
https://github.com/scikit-learn/scikit-learn/issues/27600 | [
"Bug"
] | Missing assert in test_kernel_approximation.py
### Describe the bug
[scikit-learn/sklearn/tests/test\_kernel\_approximation.py at main · scikit-learn/scikit-learn](https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/tests/test_kernel_approximation.py#L144)
```python
@pytest.mark.parametrize("method",... | 27,600 | [
-0.028463734313845634,
0.007492233067750931,
0.011488422751426697,
-0.01922006532549858,
0.051609158515930176,
-0.019940579310059547,
0.027368925511837006,
0.0627056285738945,
0.0012630167184397578,
0.02007819339632988,
0.07886052131652832,
0.06271447986364365,
0.020741060376167297,
-0.022... |
https://github.com/scikit-learn/scikit-learn/issues/27600 | [
"Bug"
] | Missing assert in test_kernel_approximation.py
### Describe the bug
[scikit-learn/sklearn/tests/test\_kernel\_approximation.py at main · scikit-learn/scikit-learn](https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/tests/test_kernel_approximation.py#L144)
```python
@pytest.mark.parametrize("method",... | 27,600 | [
-0.028463734313845634,
0.007492233067750931,
0.011488422751426697,
-0.01922006532549858,
0.051609158515930176,
-0.019940579310059547,
0.027368925511837006,
0.0627056285738945,
0.0012630167184397578,
0.02007819339632988,
0.07886052131652832,
0.06271447986364365,
0.020741060376167297,
-0.022... |
https://github.com/scikit-learn/scikit-learn/issues/27600 | [
"Bug"
] | Missing assert in test_kernel_approximation.py
### Describe the bug
[scikit-learn/sklearn/tests/test\_kernel\_approximation.py at main · scikit-learn/scikit-learn](https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/tests/test_kernel_approximation.py#L144)
```python
@pytest.mark.parametrize("method",... | 27,600 | [
-0.028463734313845634,
0.007492233067750931,
0.011488422751426697,
-0.01922006532549858,
0.051609158515930176,
-0.019940579310059547,
0.027368925511837006,
0.0627056285738945,
0.0012630167184397578,
0.02007819339632988,
0.07886052131652832,
0.06271447986364365,
0.020741060376167297,
-0.022... |
https://github.com/scikit-learn/scikit-learn/issues/27595 | [
"Needs Reproducible Code"
] | partial dependence display generates empty plot with all grid values being nan
### Describe the bug
I trained a binary classifier using XGBoost, and I was trying to generate partial dependence plot for each feature in my dataset. The partial_dependence() and PartialDependenceDisplay.from_estimator() function worked... | 27,595 | [
0.017499856650829315,
-0.007060348987579346,
0.043330345302820206,
0.020014196634292603,
0.05472605675458908,
-0.02474054880440235,
0.01296949665993452,
0.03413216024637222,
0.045719925314188004,
-0.006831708364188671,
-0.022729313001036644,
0.001827774802222848,
0.008991195820271969,
0.03... |
https://github.com/scikit-learn/scikit-learn/issues/27595 | [
"Needs Reproducible Code"
] | partial dependence display generates empty plot with all grid values being nan
### Describe the bug
I trained a binary classifier using XGBoost, and I was trying to generate partial dependence plot for each feature in my dataset. The partial_dependence() and PartialDependenceDisplay.from_estimator() function worked... | 27,595 | [
0.017499856650829315,
-0.007060348987579346,
0.043330345302820206,
0.020014196634292603,
0.05472605675458908,
-0.02474054880440235,
0.01296949665993452,
0.03413216024637222,
0.045719925314188004,
-0.006831708364188671,
-0.022729313001036644,
0.001827774802222848,
0.008991195820271969,
0.03... |
https://github.com/scikit-learn/scikit-learn/issues/27593 | [
"API",
"Breaking Change",
"cython"
] | Deprecate murmurhash3_32
`sklearn.utils.murmurhash3_32` is part of our API, but we don't use it anywhere internally.
I propose to deprecate and finally remove it. The standard Python [`hash`](https://docs.python.org/3/library/functions.html#hash) function using SipHash per [PEP0456](https://peps.python.org/pep-0456/)... | 27,593 | [
-0.013896329328417778,
0.033734891563653946,
0.020089179277420044,
-0.001389424898661673,
-0.01760825142264366,
0.028715364634990692,
0.05096062645316124,
0.013557096011936665,
-0.02122371457517147,
-0.003651402425020933,
0.07433462888002396,
0.03722105175256729,
-0.023054905235767365,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27593 | [
"API",
"Breaking Change",
"cython"
] | Deprecate murmurhash3_32
`sklearn.utils.murmurhash3_32` is part of our API, but we don't use it anywhere internally.
I propose to deprecate and finally remove it. The standard Python [`hash`](https://docs.python.org/3/library/functions.html#hash) function using SipHash per [PEP0456](https://peps.python.org/pep-0456/)... | 27,593 | [
-0.002245247131213546,
0.03168695792555809,
0.03345801308751106,
0.00801429245620966,
-0.0022282921709120274,
0.026227561756968498,
0.01758543960750103,
0.014586969278752804,
-0.020383277907967567,
-0.015193987637758255,
0.06037298962473869,
0.022112898528575897,
-0.050925806164741516,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27593 | [
"API",
"Breaking Change",
"cython"
] | Deprecate murmurhash3_32
`sklearn.utils.murmurhash3_32` is part of our API, but we don't use it anywhere internally.
I propose to deprecate and finally remove it. The standard Python [`hash`](https://docs.python.org/3/library/functions.html#hash) function using SipHash per [PEP0456](https://peps.python.org/pep-0456/)... | 27,593 | [
-0.017949089407920837,
-0.008078939281404018,
0.01743556745350361,
0.01680046133697033,
0.0012191355926916003,
0.022540144622325897,
0.021469976752996445,
0.025143800303339958,
-0.03131683170795441,
-0.010844792239367962,
0.0442814975976944,
0.04566304758191109,
-0.01762370951473713,
0.045... |
https://github.com/scikit-learn/scikit-learn/issues/27593 | [
"API",
"Breaking Change",
"cython"
] | Deprecate murmurhash3_32
`sklearn.utils.murmurhash3_32` is part of our API, but we don't use it anywhere internally.
I propose to deprecate and finally remove it. The standard Python [`hash`](https://docs.python.org/3/library/functions.html#hash) function using SipHash per [PEP0456](https://peps.python.org/pep-0456/)... | 27,593 | [
-0.0017997701652348042,
-0.0026922740507870913,
0.025371791794896126,
0.011606931686401367,
-0.0067702000960707664,
0.022549964487552643,
0.03028179332613945,
0.0167051050812006,
-0.02726549468934536,
-0.01886342465877533,
0.04727601632475853,
0.03879378363490105,
-0.020530808717012405,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/27593 | [
"API",
"Breaking Change",
"cython"
] | Deprecate murmurhash3_32
`sklearn.utils.murmurhash3_32` is part of our API, but we don't use it anywhere internally.
I propose to deprecate and finally remove it. The standard Python [`hash`](https://docs.python.org/3/library/functions.html#hash) function using SipHash per [PEP0456](https://peps.python.org/pep-0456/)... | 27,593 | [
-0.018116727471351624,
0.008214656263589859,
0.01425456628203392,
-0.006529032252728939,
-0.03184332698583603,
0.015809014439582825,
0.027958974242210388,
0.0014301409246399999,
-0.02516467496752739,
-0.010374434292316437,
0.08000753074884415,
0.03338947519659996,
-0.023259121924638748,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/27593 | [
"API",
"Breaking Change",
"cython"
] | Deprecate murmurhash3_32
`sklearn.utils.murmurhash3_32` is part of our API, but we don't use it anywhere internally.
I propose to deprecate and finally remove it. The standard Python [`hash`](https://docs.python.org/3/library/functions.html#hash) function using SipHash per [PEP0456](https://peps.python.org/pep-0456/)... | 27,593 | [
-0.020038481801748276,
0.004623595625162125,
0.01889490894973278,
0.001929582329466939,
-0.023671472445130348,
0.01920454204082489,
0.01659080758690834,
0.021222328767180443,
-0.0466722771525383,
-0.015519414097070694,
0.05845566466450691,
0.027174493297934532,
-0.019213160499930382,
0.062... |
https://github.com/scikit-learn/scikit-learn/issues/27593 | [
"API",
"Breaking Change",
"cython"
] | Deprecate murmurhash3_32
`sklearn.utils.murmurhash3_32` is part of our API, but we don't use it anywhere internally.
I propose to deprecate and finally remove it. The standard Python [`hash`](https://docs.python.org/3/library/functions.html#hash) function using SipHash per [PEP0456](https://peps.python.org/pep-0456/)... | 27,593 | [
0.0040633464232087135,
0.0007258270052261651,
0.02870669588446617,
-0.006117035634815693,
0.010277973487973213,
0.03716280683875084,
0.01618945226073265,
0.02097133919596672,
-0.013061036355793476,
-0.015375811606645584,
0.069066621363163,
0.03599533438682556,
-0.041990283876657486,
0.0618... |
https://github.com/scikit-learn/scikit-learn/issues/27593 | [
"API",
"Breaking Change",
"cython"
] | Deprecate murmurhash3_32
`sklearn.utils.murmurhash3_32` is part of our API, but we don't use it anywhere internally.
I propose to deprecate and finally remove it. The standard Python [`hash`](https://docs.python.org/3/library/functions.html#hash) function using SipHash per [PEP0456](https://peps.python.org/pep-0456/)... | 27,593 | [
-0.012777349911630154,
0.008371812291443348,
0.018025880679488182,
0.009480036795139313,
-0.0025751101784408092,
0.045806702226400375,
0.027664339169859886,
0.0005260633770376444,
-0.027017656713724136,
-0.01716557890176773,
0.07899981737136841,
0.027351167052984238,
-0.03430233895778656,
... |
https://github.com/scikit-learn/scikit-learn/issues/27593 | [
"API",
"Breaking Change",
"cython"
] | Deprecate murmurhash3_32
`sklearn.utils.murmurhash3_32` is part of our API, but we don't use it anywhere internally.
I propose to deprecate and finally remove it. The standard Python [`hash`](https://docs.python.org/3/library/functions.html#hash) function using SipHash per [PEP0456](https://peps.python.org/pep-0456/)... | 27,593 | [
-0.015638401731848717,
0.01691274344921112,
0.02170656993985176,
0.002641683677211404,
-0.01208226103335619,
0.01904352754354477,
0.00939447246491909,
0.004735507071018219,
-0.03328482434153557,
-0.009666255675256252,
0.05993680655956268,
0.05430809035897255,
-0.029228271916508675,
0.06163... |
https://github.com/scikit-learn/scikit-learn/issues/27593 | [
"API",
"Breaking Change",
"cython"
] | Deprecate murmurhash3_32
`sklearn.utils.murmurhash3_32` is part of our API, but we don't use it anywhere internally.
I propose to deprecate and finally remove it. The standard Python [`hash`](https://docs.python.org/3/library/functions.html#hash) function using SipHash per [PEP0456](https://peps.python.org/pep-0456/)... | 27,593 | [
-0.001081869238987565,
0.03228609263896942,
0.020259208977222443,
-0.0068361107259988785,
-0.03175729513168335,
0.016037827357649803,
0.014527292922139168,
0.004876726306974888,
-0.016868403181433678,
-0.007286709267646074,
0.06402846425771713,
0.06584858149290085,
-0.02702055685222149,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/27593 | [
"API",
"Breaking Change",
"cython"
] | Deprecate murmurhash3_32
`sklearn.utils.murmurhash3_32` is part of our API, but we don't use it anywhere internally.
I propose to deprecate and finally remove it. The standard Python [`hash`](https://docs.python.org/3/library/functions.html#hash) function using SipHash per [PEP0456](https://peps.python.org/pep-0456/)... | 27,593 | [
-0.02045546844601631,
0.02613014355301857,
0.013106441125273705,
0.016058916226029396,
-0.023139091208577156,
0.019546112045645714,
0.012749494053423405,
0.002746694954112172,
-0.04193349555134773,
-0.015236526727676392,
0.07899066805839539,
0.029744576662778854,
-0.036791928112506866,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27592 | [
"New Feature"
] | Using tqdm or progress bars while downloading datasets using `urlretreve`
### Describe the workflow you want to enable
https://github.com/scikit-learn/scikit-learn/blob/4ca01961969a0c9e1c7c48410e0976bb04a92703/sklearn/datasets/_base.py#L1368-L1399
When we fetch remote data using the function `_fetch_remote`, we ... | 27,592 | [
-0.017010249197483063,
0.06397183984518051,
-0.0005692997365258634,
-0.041991766542196274,
0.017206959426403046,
0.006644764915108681,
0.0057383435778319836,
0.01828458532691002,
0.0018665967509150505,
0.04489326477050781,
-0.022194325923919678,
0.015084360726177692,
-0.02756311371922493,
... |
https://github.com/scikit-learn/scikit-learn/issues/27592 | [
"New Feature"
] | Using tqdm or progress bars while downloading datasets using `urlretreve`
### Describe the workflow you want to enable
https://github.com/scikit-learn/scikit-learn/blob/4ca01961969a0c9e1c7c48410e0976bb04a92703/sklearn/datasets/_base.py#L1368-L1399
When we fetch remote data using the function `_fetch_remote`, we ... | 27,592 | [
-0.01933756284415722,
0.07789250463247299,
-0.004296297673135996,
-0.028636746108531952,
0.017211677506566048,
0.0007359019364230335,
-0.0007349787629209459,
0.015431240200996399,
0.005740417633205652,
0.037108130753040314,
-0.01293079275637865,
0.010073664598166943,
-0.029420629143714905,
... |
https://github.com/scikit-learn/scikit-learn/issues/27592 | [
"New Feature"
] | Using tqdm or progress bars while downloading datasets using `urlretreve`
### Describe the workflow you want to enable
https://github.com/scikit-learn/scikit-learn/blob/4ca01961969a0c9e1c7c48410e0976bb04a92703/sklearn/datasets/_base.py#L1368-L1399
When we fetch remote data using the function `_fetch_remote`, we ... | 27,592 | [
-0.017230430617928505,
0.06829817593097687,
0.007459287531673908,
-0.03240862116217613,
0.016635173931717873,
-0.000272199249593541,
0.008012882433831692,
0.015849128365516663,
0.004895559512078762,
0.047087058424949646,
-0.03121579810976982,
0.012763196602463722,
-0.02498229220509529,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27592 | [
"New Feature"
] | Using tqdm or progress bars while downloading datasets using `urlretreve`
### Describe the workflow you want to enable
https://github.com/scikit-learn/scikit-learn/blob/4ca01961969a0c9e1c7c48410e0976bb04a92703/sklearn/datasets/_base.py#L1368-L1399
When we fetch remote data using the function `_fetch_remote`, we ... | 27,592 | [
-0.019911140203475952,
0.06600893288850784,
0.003924594260752201,
-0.036480654031038284,
0.017689397558569908,
0.00214567338116467,
0.001145696733146906,
0.01957077905535698,
0.007090544328093529,
0.05048787593841553,
-0.01813744567334652,
0.013620639219880104,
-0.029632294550538063,
0.044... |
https://github.com/scikit-learn/scikit-learn/issues/27592 | [
"New Feature"
] | Using tqdm or progress bars while downloading datasets using `urlretreve`
### Describe the workflow you want to enable
https://github.com/scikit-learn/scikit-learn/blob/4ca01961969a0c9e1c7c48410e0976bb04a92703/sklearn/datasets/_base.py#L1368-L1399
When we fetch remote data using the function `_fetch_remote`, we ... | 27,592 | [
-0.02429221011698246,
0.05664967745542526,
0.006083745509386063,
-0.026195213198661804,
0.02633819542825222,
0.007367431651800871,
0.0013339570723474026,
0.024556193500757217,
0.01217156182974577,
0.03704183176159859,
-0.030994784086942673,
0.029268713667988777,
-0.031603019684553146,
0.04... |
https://github.com/scikit-learn/scikit-learn/issues/27592 | [
"New Feature"
] | Using tqdm or progress bars while downloading datasets using `urlretreve`
### Describe the workflow you want to enable
https://github.com/scikit-learn/scikit-learn/blob/4ca01961969a0c9e1c7c48410e0976bb04a92703/sklearn/datasets/_base.py#L1368-L1399
When we fetch remote data using the function `_fetch_remote`, we ... | 27,592 | [
-0.022352702915668488,
0.05964532122015953,
0.002031581476330757,
-0.03508996590971947,
0.017194973304867744,
0.003987724427133799,
0.005360778421163559,
0.021875614300370216,
0.00306242099031806,
0.04446292668581009,
-0.024556059390306473,
0.011397182941436768,
-0.032790958881378174,
0.04... |
https://github.com/scikit-learn/scikit-learn/issues/27592 | [
"New Feature"
] | Using tqdm or progress bars while downloading datasets using `urlretreve`
### Describe the workflow you want to enable
https://github.com/scikit-learn/scikit-learn/blob/4ca01961969a0c9e1c7c48410e0976bb04a92703/sklearn/datasets/_base.py#L1368-L1399
When we fetch remote data using the function `_fetch_remote`, we ... | 27,592 | [
-0.01905987784266472,
0.06587131321430206,
0.008433469571173191,
-0.03410088270902634,
0.019541900604963303,
0.002013490069657564,
0.009005223400890827,
0.0228444691747427,
0.016424650326371193,
0.039998479187488556,
-0.019080275669693947,
0.02437688037753105,
-0.029539048671722412,
0.0541... |
https://github.com/scikit-learn/scikit-learn/issues/27592 | [
"New Feature"
] | Using tqdm or progress bars while downloading datasets using `urlretreve`
### Describe the workflow you want to enable
https://github.com/scikit-learn/scikit-learn/blob/4ca01961969a0c9e1c7c48410e0976bb04a92703/sklearn/datasets/_base.py#L1368-L1399
When we fetch remote data using the function `_fetch_remote`, we ... | 27,592 | [
-0.020552335307002068,
0.07053007930517197,
0.004147717729210854,
-0.041000209748744965,
0.01707080379128456,
0.0071210796013474464,
0.009406691417098045,
0.01647658459842205,
0.009743600152432919,
0.04359188303351402,
-0.019478587433695793,
0.013439367525279522,
-0.03407570347189903,
0.05... |
https://github.com/scikit-learn/scikit-learn/issues/27592 | [
"New Feature"
] | Using tqdm or progress bars while downloading datasets using `urlretreve`
### Describe the workflow you want to enable
https://github.com/scikit-learn/scikit-learn/blob/4ca01961969a0c9e1c7c48410e0976bb04a92703/sklearn/datasets/_base.py#L1368-L1399
When we fetch remote data using the function `_fetch_remote`, we ... | 27,592 | [
-0.02431272529065609,
0.06225579231977463,
0.004234787542372942,
-0.037616848945617676,
0.020838789641857147,
0.0008681212202645838,
0.005150257609784603,
0.020010478794574738,
0.00465560844168067,
0.04432257264852524,
-0.02492624893784523,
0.01656629517674446,
-0.03118165396153927,
0.0500... |
https://github.com/scikit-learn/scikit-learn/issues/27592 | [
"New Feature"
] | Using tqdm or progress bars while downloading datasets using `urlretreve`
### Describe the workflow you want to enable
https://github.com/scikit-learn/scikit-learn/blob/4ca01961969a0c9e1c7c48410e0976bb04a92703/sklearn/datasets/_base.py#L1368-L1399
When we fetch remote data using the function `_fetch_remote`, we ... | 27,592 | [
-0.021857891231775284,
0.06008858233690262,
0.009864160791039467,
-0.03842765465378761,
0.022965239360928535,
0.005209135822951794,
0.0053541772067546844,
0.018819721415638924,
0.002608671085909009,
0.045859720557928085,
-0.03242385759949684,
0.016890957951545715,
-0.028316088020801544,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/27592 | [
"New Feature"
] | Using tqdm or progress bars while downloading datasets using `urlretreve`
### Describe the workflow you want to enable
https://github.com/scikit-learn/scikit-learn/blob/4ca01961969a0c9e1c7c48410e0976bb04a92703/sklearn/datasets/_base.py#L1368-L1399
When we fetch remote data using the function `_fetch_remote`, we ... | 27,592 | [
-0.01503712497651577,
0.07059767097234726,
0.006329374387860298,
-0.042503684759140015,
0.01250107865780592,
-0.0011072626803070307,
0.00612536771222949,
0.0038441717624664307,
0.0006451014778576791,
0.04357610642910004,
-0.017302585765719414,
0.010689368471503258,
-0.02886161394417286,
0.... |
https://github.com/scikit-learn/scikit-learn/issues/27592 | [
"New Feature"
] | Using tqdm or progress bars while downloading datasets using `urlretreve`
### Describe the workflow you want to enable
https://github.com/scikit-learn/scikit-learn/blob/4ca01961969a0c9e1c7c48410e0976bb04a92703/sklearn/datasets/_base.py#L1368-L1399
When we fetch remote data using the function `_fetch_remote`, we ... | 27,592 | [
-0.0208498053252697,
0.06003207713365555,
0.002674111630767584,
-0.03605050966143608,
0.02264478988945484,
0.0026752122212201357,
0.0006279493682086468,
0.02044442482292652,
0.005888998042792082,
0.04488276690244675,
-0.02238486148416996,
0.019251862540841103,
-0.030679890885949135,
0.0504... |
https://github.com/scikit-learn/scikit-learn/issues/27592 | [
"New Feature"
] | Using tqdm or progress bars while downloading datasets using `urlretreve`
### Describe the workflow you want to enable
https://github.com/scikit-learn/scikit-learn/blob/4ca01961969a0c9e1c7c48410e0976bb04a92703/sklearn/datasets/_base.py#L1368-L1399
When we fetch remote data using the function `_fetch_remote`, we ... | 27,592 | [
-0.015071945264935493,
0.058629684150218964,
0.005974023137241602,
-0.0406610369682312,
0.015774283558130264,
0.0008534328080713749,
0.009270746260881424,
0.02027633786201477,
-0.0057198042050004005,
0.04063734412193298,
-0.023321740329265594,
0.011767355725169182,
-0.030410712584853172,
0... |
https://github.com/scikit-learn/scikit-learn/issues/27592 | [
"New Feature"
] | Using tqdm or progress bars while downloading datasets using `urlretreve`
### Describe the workflow you want to enable
https://github.com/scikit-learn/scikit-learn/blob/4ca01961969a0c9e1c7c48410e0976bb04a92703/sklearn/datasets/_base.py#L1368-L1399
When we fetch remote data using the function `_fetch_remote`, we ... | 27,592 | [
-0.02062525600194931,
0.0614059753715992,
0.0013314721873030066,
-0.03340325132012367,
0.019755806773900986,
0.005850949790328741,
-0.003802557708695531,
0.021230507642030716,
0.007156234234571457,
0.04563039541244507,
-0.016665279865264893,
0.01233393233269453,
-0.028762592002749443,
0.04... |
https://github.com/scikit-learn/scikit-learn/issues/27591 | [
"Build / CI"
] | Bumping minimum NumPy version to support NumPy 1.X and 2.0
According to [NumPy's build-time dependency docs](https://numpy.org/devdocs//dev/depending_on_numpy.html#build-time-dependency), NumPy 1.25 is backward compatible with NumPy 1.19. (We'll no longer need [oldest-supported-numpy](https://github.com/scipy/oldest-s... | 27,591 | [
0.0006550506805069745,
0.1097261980175972,
0.004568474367260933,
-0.07274318486452103,
-0.023263009265065193,
0.009728735312819481,
-0.004447114188224077,
0.047758862376213074,
0.005507877562195063,
0.002668501576408744,
0.06544231623411179,
0.03462366759777069,
-0.0017053047195076942,
0.0... |
https://github.com/scikit-learn/scikit-learn/issues/27591 | [
"Build / CI"
] | Bumping minimum NumPy version to support NumPy 1.X and 2.0
According to [NumPy's build-time dependency docs](https://numpy.org/devdocs//dev/depending_on_numpy.html#build-time-dependency), NumPy 1.25 is backward compatible with NumPy 1.19. (We'll no longer need [oldest-supported-numpy](https://github.com/scipy/oldest-s... | 27,591 | [
0.0061782654374837875,
0.11018414795398712,
0.011075460352003574,
-0.07360116392374039,
-0.01720762811601162,
0.008684596978127956,
0.02221156843006611,
0.04517654329538345,
0.020017104223370552,
0.011846841312944889,
0.060135673731565475,
0.017782675102353096,
0.0009249747381545603,
0.017... |
https://github.com/scikit-learn/scikit-learn/issues/27591 | [
"Build / CI"
] | Bumping minimum NumPy version to support NumPy 1.X and 2.0
According to [NumPy's build-time dependency docs](https://numpy.org/devdocs//dev/depending_on_numpy.html#build-time-dependency), NumPy 1.25 is backward compatible with NumPy 1.19. (We'll no longer need [oldest-supported-numpy](https://github.com/scipy/oldest-s... | 27,591 | [
-0.003325690748170018,
0.10050170123577118,
-0.0015198836335912347,
-0.07717422395944595,
-0.014883102849125862,
0.015273021534085274,
0.0024991671089082956,
0.04008886218070984,
0.0010249561164528131,
-0.0017153093358501792,
0.0633963942527771,
0.00037375965621322393,
0.016975579783320427,
... |
https://github.com/scikit-learn/scikit-learn/issues/27590 | [
"Bug",
"Needs Triage"
] | Error in joblib forking when using RandomForestClassifier
### Describe the bug
When using `lithops` joblib backend, a grid search with the RandomForestClassifier causes an error from joblib. The error complains that the system doesn't support forking, but MacOS does. Running a very close example with either a differe... | 27,590 | [
0.00877450592815876,
-0.007760900072753429,
-0.003118047723546624,
-0.0027696157339960337,
0.03446930646896362,
-0.021863754838705063,
0.027086667716503143,
0.01851085014641285,
-0.027103789150714874,
-0.016342444345355034,
0.014052783139050007,
0.05599562078714371,
-0.02105453610420227,
-... |
https://github.com/scikit-learn/scikit-learn/issues/27579 | [
"Bug"
] | set_config(transform_output="pandas") causes error in Isomap
### Describe the bug
I am getting an error when using the awesome `set_config(transform_output="pandas")` in combination with Isomap. The Error says "AttributeError: 'DataFrame' object has no attribute 'dtype'", so my temporary solution is to switch back ... | 27,579 | [
-0.003388260258361697,
0.011434289626777172,
0.025351127609610558,
-0.013590740971267223,
0.05578997731208801,
0.01884402148425579,
0.060428470373153687,
0.0239203292876482,
0.0074674217030406,
-0.05730242282152176,
-0.024578765034675598,
0.035254161804914474,
0.025861265137791634,
0.01714... |
https://github.com/scikit-learn/scikit-learn/issues/27579 | [
"Bug"
] | set_config(transform_output="pandas") causes error in Isomap
### Describe the bug
I am getting an error when using the awesome `set_config(transform_output="pandas")` in combination with Isomap. The Error says "AttributeError: 'DataFrame' object has no attribute 'dtype'", so my temporary solution is to switch back ... | 27,579 | [
-0.003388260258361697,
0.011434289626777172,
0.025351127609610558,
-0.013590740971267223,
0.05578997731208801,
0.01884402148425579,
0.060428470373153687,
0.0239203292876482,
0.0074674217030406,
-0.05730242282152176,
-0.024578765034675598,
0.035254161804914474,
0.025861265137791634,
0.01714... |
https://github.com/scikit-learn/scikit-learn/issues/27579 | [
"Bug"
] | set_config(transform_output="pandas") causes error in Isomap
### Describe the bug
I am getting an error when using the awesome `set_config(transform_output="pandas")` in combination with Isomap. The Error says "AttributeError: 'DataFrame' object has no attribute 'dtype'", so my temporary solution is to switch back ... | 27,579 | [
-0.003388260258361697,
0.011434289626777172,
0.025351127609610558,
-0.013590740971267223,
0.05578997731208801,
0.01884402148425579,
0.060428470373153687,
0.0239203292876482,
0.0074674217030406,
-0.05730242282152176,
-0.024578765034675598,
0.035254161804914474,
0.025861265137791634,
0.01714... |
https://github.com/scikit-learn/scikit-learn/issues/27579 | [
"Bug"
] | set_config(transform_output="pandas") causes error in Isomap
### Describe the bug
I am getting an error when using the awesome `set_config(transform_output="pandas")` in combination with Isomap. The Error says "AttributeError: 'DataFrame' object has no attribute 'dtype'", so my temporary solution is to switch back ... | 27,579 | [
-0.003388260258361697,
0.011434289626777172,
0.025351127609610558,
-0.013590740971267223,
0.05578997731208801,
0.01884402148425579,
0.060428470373153687,
0.0239203292876482,
0.0074674217030406,
-0.05730242282152176,
-0.024578765034675598,
0.035254161804914474,
0.025861265137791634,
0.01714... |
https://github.com/scikit-learn/scikit-learn/issues/27579 | [
"Bug"
] | set_config(transform_output="pandas") causes error in Isomap
### Describe the bug
I am getting an error when using the awesome `set_config(transform_output="pandas")` in combination with Isomap. The Error says "AttributeError: 'DataFrame' object has no attribute 'dtype'", so my temporary solution is to switch back ... | 27,579 | [
-0.003388260258361697,
0.011434289626777172,
0.025351127609610558,
-0.013590740971267223,
0.05578997731208801,
0.01884402148425579,
0.060428470373153687,
0.0239203292876482,
0.0074674217030406,
-0.05730242282152176,
-0.024578765034675598,
0.035254161804914474,
0.025861265137791634,
0.01714... |
https://github.com/scikit-learn/scikit-learn/issues/27564 | [
"New Feature",
"Needs Triage"
] | Decision Rules in If/Then format
### Describe the workflow you want to enable
Although Decision tree has the following to print rules,
```
from sklearn.datasets import load_iris
from sklearn.tree import DecisionTreeClassifier
from sklearn.tree import export_text
iris = load_iris()
X = iris['data']
y = ir... | 27,564 | [
-0.01928033120930195,
-0.013190951198339462,
-0.019908994436264038,
-0.009630261920392513,
-0.0019271972123533487,
-0.02079695463180542,
-0.050950031727552414,
0.038707390427589417,
-0.019877934828400612,
-0.016172297298908234,
0.03750132396817207,
0.03897560015320778,
0.00585193932056427,
... |
https://github.com/scikit-learn/scikit-learn/issues/27564 | [
"New Feature",
"Needs Triage"
] | Decision Rules in If/Then format
### Describe the workflow you want to enable
Although Decision tree has the following to print rules,
```
from sklearn.datasets import load_iris
from sklearn.tree import DecisionTreeClassifier
from sklearn.tree import export_text
iris = load_iris()
X = iris['data']
y = ir... | 27,564 | [
-0.01928033120930195,
-0.013190951198339462,
-0.019908994436264038,
-0.009630261920392513,
-0.0019271972123533487,
-0.02079695463180542,
-0.050950031727552414,
0.038707390427589417,
-0.019877934828400612,
-0.016172297298908234,
0.03750132396817207,
0.03897560015320778,
0.00585193932056427,
... |
https://github.com/scikit-learn/scikit-learn/issues/27564 | [
"New Feature",
"Needs Triage"
] | Decision Rules in If/Then format
### Describe the workflow you want to enable
Although Decision tree has the following to print rules,
```
from sklearn.datasets import load_iris
from sklearn.tree import DecisionTreeClassifier
from sklearn.tree import export_text
iris = load_iris()
X = iris['data']
y = ir... | 27,564 | [
-0.01928033120930195,
-0.013190951198339462,
-0.019908994436264038,
-0.009630261920392513,
-0.0019271972123533487,
-0.02079695463180542,
-0.050950031727552414,
0.038707390427589417,
-0.019877934828400612,
-0.016172297298908234,
0.03750132396817207,
0.03897560015320778,
0.00585193932056427,
... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.