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/28995
[ "New Feature", "API", "Needs Decision", "RFC", "module:metrics" ]
Add "scoring" argument to estimator's ``score`` method ### Describe the workflow you want to enable I want to enable non-accuracy metrics to ``estimator.score``, and ultimately deprecate the default values of ``accuracy`` and ``r2``. I would call it ``scoring`` though it's a bit redundant but consistent. That woul...
28,995
[ -0.010190000757575035, 0.10270854085683823, 0.05647295340895653, -0.024012291803956032, 0.025094304233789444, 0.008990094065666199, 0.02641894668340683, 0.017209326848387718, 0.02139352075755596, -0.024918755516409874, -0.016154460608959198, 0.046662501990795135, 0.002157321199774742, 0.08...
https://github.com/scikit-learn/scikit-learn/issues/28995
[ "New Feature", "API", "Needs Decision", "RFC", "module:metrics" ]
Add "scoring" argument to estimator's ``score`` method ### Describe the workflow you want to enable I want to enable non-accuracy metrics to ``estimator.score``, and ultimately deprecate the default values of ``accuracy`` and ``r2``. I would call it ``scoring`` though it's a bit redundant but consistent. That woul...
28,995
[ -0.013234179466962814, 0.1015443205833435, 0.05646622180938721, -0.028773292899131775, 0.03162159398198128, 0.003970704041421413, 0.013757978565990925, 0.01746634766459465, 0.036723244935274124, -0.022106124088168144, -0.017935222014784813, 0.04631204158067703, 0.0024229399859905243, 0.082...
https://github.com/scikit-learn/scikit-learn/issues/28995
[ "New Feature", "API", "Needs Decision", "RFC", "module:metrics" ]
Add "scoring" argument to estimator's ``score`` method ### Describe the workflow you want to enable I want to enable non-accuracy metrics to ``estimator.score``, and ultimately deprecate the default values of ``accuracy`` and ``r2``. I would call it ``scoring`` though it's a bit redundant but consistent. That woul...
28,995
[ -0.013652858324348927, 0.10104985535144806, 0.05474148318171501, -0.032232869416475296, 0.018582899123430252, 0.003919424954801798, 0.019962500780820847, 0.012381695210933685, 0.005902667995542288, -0.01577925868332386, -0.01772340200841427, 0.05058283731341362, -0.0061927963979542255, 0.1...
https://github.com/scikit-learn/scikit-learn/issues/28995
[ "New Feature", "API", "Needs Decision", "RFC", "module:metrics" ]
Add "scoring" argument to estimator's ``score`` method ### Describe the workflow you want to enable I want to enable non-accuracy metrics to ``estimator.score``, and ultimately deprecate the default values of ``accuracy`` and ``r2``. I would call it ``scoring`` though it's a bit redundant but consistent. That woul...
28,995
[ -0.013135265558958054, 0.10211500525474548, 0.05986562743782997, -0.02076559327542782, 0.023565957322716713, 0.00603207852691412, 0.025800256058573723, 0.017944591119885445, 0.021306462585926056, -0.01593666337430477, -0.01774013787508011, 0.044120363891124725, 0.00018319573428016156, 0.09...
https://github.com/scikit-learn/scikit-learn/issues/28995
[ "New Feature", "API", "Needs Decision", "RFC", "module:metrics" ]
Add "scoring" argument to estimator's ``score`` method ### Describe the workflow you want to enable I want to enable non-accuracy metrics to ``estimator.score``, and ultimately deprecate the default values of ``accuracy`` and ``r2``. I would call it ``scoring`` though it's a bit redundant but consistent. That woul...
28,995
[ -0.012182457372546196, 0.11357063055038452, 0.05763363465666771, -0.023668909445405006, 0.01876136288046837, 0.008325320668518543, 0.029211198911070824, 0.011327184736728668, 0.02440212108194828, -0.020159635692834854, -0.008899316191673279, 0.0320289172232151, 0.005317867733538151, 0.0885...
https://github.com/scikit-learn/scikit-learn/issues/28995
[ "New Feature", "API", "Needs Decision", "RFC", "module:metrics" ]
Add "scoring" argument to estimator's ``score`` method ### Describe the workflow you want to enable I want to enable non-accuracy metrics to ``estimator.score``, and ultimately deprecate the default values of ``accuracy`` and ``r2``. I would call it ``scoring`` though it's a bit redundant but consistent. That woul...
28,995
[ -0.004471614025533199, 0.06875015050172806, 0.06771036237478256, -0.006027781404554844, 0.060612890869379044, 0.010553332045674324, 0.015248647890985012, 0.009132389910519123, 0.059144407510757446, -0.008525034412741661, -0.02623654343187809, 0.058967120945453644, -0.0017327656969428062, 0...
https://github.com/scikit-learn/scikit-learn/issues/28995
[ "New Feature", "API", "Needs Decision", "RFC", "module:metrics" ]
Add "scoring" argument to estimator's ``score`` method ### Describe the workflow you want to enable I want to enable non-accuracy metrics to ``estimator.score``, and ultimately deprecate the default values of ``accuracy`` and ``r2``. I would call it ``scoring`` though it's a bit redundant but consistent. That woul...
28,995
[ 0.0005940371775068343, 0.08875961601734161, 0.0599479041993618, -0.03265601769089699, 0.03965786099433899, 0.0025939184706658125, 0.008081505075097084, 0.011604095809161663, 0.04746580496430397, -0.019109945744276047, -0.011025340296328068, 0.057875845581293106, -0.0010428486857563257, 0.0...
https://github.com/scikit-learn/scikit-learn/issues/28995
[ "New Feature", "API", "Needs Decision", "RFC", "module:metrics" ]
Add "scoring" argument to estimator's ``score`` method ### Describe the workflow you want to enable I want to enable non-accuracy metrics to ``estimator.score``, and ultimately deprecate the default values of ``accuracy`` and ``r2``. I would call it ``scoring`` though it's a bit redundant but consistent. That woul...
28,995
[ -0.011628678068518639, 0.10285747051239014, 0.05404175817966461, -0.026432789862155914, 0.020866116508841515, 0.008182511664927006, 0.02552717737853527, 0.019282618537545204, 0.02022438496351242, -0.023117592558264732, -0.012499754317104816, 0.043309591710567474, 0.0034396646078675985, 0.0...
https://github.com/scikit-learn/scikit-learn/issues/28995
[ "New Feature", "API", "Needs Decision", "RFC", "module:metrics" ]
Add "scoring" argument to estimator's ``score`` method ### Describe the workflow you want to enable I want to enable non-accuracy metrics to ``estimator.score``, and ultimately deprecate the default values of ``accuracy`` and ``r2``. I would call it ``scoring`` though it's a bit redundant but consistent. That woul...
28,995
[ -0.013462311588227749, 0.10303575545549393, 0.055683016777038574, -0.025352293625473976, 0.02638331800699234, 0.008634792640805244, 0.02907026931643486, 0.021763106808066368, 0.020645856857299805, -0.0210307314991951, -0.011908600106835365, 0.04170462116599083, 0.0035246736370027065, 0.092...
https://github.com/scikit-learn/scikit-learn/issues/28995
[ "New Feature", "API", "Needs Decision", "RFC", "module:metrics" ]
Add "scoring" argument to estimator's ``score`` method ### Describe the workflow you want to enable I want to enable non-accuracy metrics to ``estimator.score``, and ultimately deprecate the default values of ``accuracy`` and ``r2``. I would call it ``scoring`` though it's a bit redundant but consistent. That woul...
28,995
[ -0.0026360969059169292, 0.09142620861530304, 0.05924137309193611, -0.030872032046318054, 0.023728014901280403, 0.013533497229218483, 0.024063261225819588, 0.022631941363215446, 0.030214950442314148, -0.027575261890888214, 0.003131146775558591, 0.03982662409543991, -0.0020041323732584715, 0...
https://github.com/scikit-learn/scikit-learn/issues/28995
[ "New Feature", "API", "Needs Decision", "RFC", "module:metrics" ]
Add "scoring" argument to estimator's ``score`` method ### Describe the workflow you want to enable I want to enable non-accuracy metrics to ``estimator.score``, and ultimately deprecate the default values of ``accuracy`` and ``r2``. I would call it ``scoring`` though it's a bit redundant but consistent. That woul...
28,995
[ 0.0050235409289598465, 0.0847276970744133, 0.06969954818487167, -0.02647453546524048, 0.02900705859065056, 0.008638332597911358, 0.020514177158474922, 0.016740236431360245, 0.03982216492295265, -0.031034259125590324, -0.004671463742852211, 0.05379156023263931, 0.0021108144428581, 0.0866736...
https://github.com/scikit-learn/scikit-learn/issues/28995
[ "New Feature", "API", "Needs Decision", "RFC", "module:metrics" ]
Add "scoring" argument to estimator's ``score`` method ### Describe the workflow you want to enable I want to enable non-accuracy metrics to ``estimator.score``, and ultimately deprecate the default values of ``accuracy`` and ``r2``. I would call it ``scoring`` though it's a bit redundant but consistent. That woul...
28,995
[ 0.000007584866580145899, 0.10856098681688309, 0.052739232778549194, -0.02374986559152603, 0.018098510801792145, 0.011738913133740425, 0.013667370192706585, 0.016015592962503433, 0.015042134560644627, -0.025270670652389526, -0.008164389058947563, 0.04555606469511986, 0.0051415651105344296, ...
https://github.com/scikit-learn/scikit-learn/issues/28995
[ "New Feature", "API", "Needs Decision", "RFC", "module:metrics" ]
Add "scoring" argument to estimator's ``score`` method ### Describe the workflow you want to enable I want to enable non-accuracy metrics to ``estimator.score``, and ultimately deprecate the default values of ``accuracy`` and ``r2``. I would call it ``scoring`` though it's a bit redundant but consistent. That woul...
28,995
[ 0.0005080263363197446, 0.10148116946220398, 0.06955979019403458, -0.02835799753665924, 0.02427731081843376, 0.011407479643821716, 0.02674744836986065, 0.01572534628212452, 0.04247744753956795, -0.02144649252295494, -0.009128347970545292, 0.04236028343439102, -0.00011778758198488504, 0.1007...
https://github.com/scikit-learn/scikit-learn/issues/28995
[ "New Feature", "API", "Needs Decision", "RFC", "module:metrics" ]
Add "scoring" argument to estimator's ``score`` method ### Describe the workflow you want to enable I want to enable non-accuracy metrics to ``estimator.score``, and ultimately deprecate the default values of ``accuracy`` and ``r2``. I would call it ``scoring`` though it's a bit redundant but consistent. That woul...
28,995
[ -0.005638384260237217, 0.09008435904979706, 0.06921252608299255, -0.026874154806137085, 0.028432682156562805, 0.005744593683630228, 0.029445037245750427, 0.014945680275559425, 0.03581586480140686, -0.021082306280732155, -0.009033862501382828, 0.05655520781874657, 0.0021004010923206806, 0.0...
https://github.com/scikit-learn/scikit-learn/issues/28994
[ "Documentation" ]
StratifiedShuffleSplit requires three copies of a lower class, rather than 2 ### Describe the bug When we want to use `StratifiedShuffleSplit` to train test split across classes, we would expect we need 2 samples of the lowest represented class: 1 for test, one for train. We don't get this: we need 3 samples of the...
28,994
[ -0.002950264373794198, -0.043379977345466614, 0.01604974828660488, 0.04704108461737633, 0.032756734639406204, -0.027393599972128868, 0.09670362621545792, 0.04120717942714691, -0.020323531702160835, -0.04124891385436058, 0.055328406393527985, -0.012954941019415855, -0.0005415438208729029, 0...
https://github.com/scikit-learn/scikit-learn/issues/28994
[ "Documentation" ]
StratifiedShuffleSplit requires three copies of a lower class, rather than 2 ### Describe the bug When we want to use `StratifiedShuffleSplit` to train test split across classes, we would expect we need 2 samples of the lowest represented class: 1 for test, one for train. We don't get this: we need 3 samples of the...
28,994
[ -0.002950264373794198, -0.043379977345466614, 0.01604974828660488, 0.04704108461737633, 0.032756734639406204, -0.027393599972128868, 0.09670362621545792, 0.04120717942714691, -0.020323531702160835, -0.04124891385436058, 0.055328406393527985, -0.012954941019415855, -0.0005415438208729029, 0...
https://github.com/scikit-learn/scikit-learn/issues/28993
[ "Bug" ]
MemoryLeak in `LogisticRession` ### Describe the bug repro * Repeatedly call `LogisticRegression().fit(X, y)` on same size feature matrix. Or run the attached repro-script. expected * The max memory allocated is steady regardless the number of train calls. actual * Memory usage grows linear with the number...
28,993
[ 0.031968969851732254, 0.010626370087265968, 0.03381090983748436, 0.002432381035760045, 0.0730084627866745, 0.0005487326998263597, -0.030937040224671364, 0.012391279451549053, 0.017040297389030457, 0.0024719706270843744, 0.07849561423063278, 0.04765778034925461, -0.01834406889975071, 0.0031...
https://github.com/scikit-learn/scikit-learn/issues/28993
[ "Bug" ]
MemoryLeak in `LogisticRession` ### Describe the bug repro * Repeatedly call `LogisticRegression().fit(X, y)` on same size feature matrix. Or run the attached repro-script. expected * The max memory allocated is steady regardless the number of train calls. actual * Memory usage grows linear with the number...
28,993
[ 0.031968969851732254, 0.010626370087265968, 0.03381090983748436, 0.002432381035760045, 0.0730084627866745, 0.0005487326998263597, -0.030937040224671364, 0.012391279451549053, 0.017040297389030457, 0.0024719706270843744, 0.07849561423063278, 0.04765778034925461, -0.01834406889975071, 0.0031...
https://github.com/scikit-learn/scikit-learn/issues/28993
[ "Bug" ]
MemoryLeak in `LogisticRession` ### Describe the bug repro * Repeatedly call `LogisticRegression().fit(X, y)` on same size feature matrix. Or run the attached repro-script. expected * The max memory allocated is steady regardless the number of train calls. actual * Memory usage grows linear with the number...
28,993
[ 0.031968969851732254, 0.010626370087265968, 0.03381090983748436, 0.002432381035760045, 0.0730084627866745, 0.0005487326998263597, -0.030937040224671364, 0.012391279451549053, 0.017040297389030457, 0.0024719706270843744, 0.07849561423063278, 0.04765778034925461, -0.01834406889975071, 0.0031...
https://github.com/scikit-learn/scikit-learn/issues/28993
[ "Bug" ]
MemoryLeak in `LogisticRession` ### Describe the bug repro * Repeatedly call `LogisticRegression().fit(X, y)` on same size feature matrix. Or run the attached repro-script. expected * The max memory allocated is steady regardless the number of train calls. actual * Memory usage grows linear with the number...
28,993
[ 0.031968969851732254, 0.010626370087265968, 0.03381090983748436, 0.002432381035760045, 0.0730084627866745, 0.0005487326998263597, -0.030937040224671364, 0.012391279451549053, 0.017040297389030457, 0.0024719706270843744, 0.07849561423063278, 0.04765778034925461, -0.01834406889975071, 0.0031...
https://github.com/scikit-learn/scikit-learn/issues/28993
[ "Bug" ]
MemoryLeak in `LogisticRession` ### Describe the bug repro * Repeatedly call `LogisticRegression().fit(X, y)` on same size feature matrix. Or run the attached repro-script. expected * The max memory allocated is steady regardless the number of train calls. actual * Memory usage grows linear with the number...
28,993
[ 0.031968969851732254, 0.010626370087265968, 0.03381090983748436, 0.002432381035760045, 0.0730084627866745, 0.0005487326998263597, -0.030937040224671364, 0.012391279451549053, 0.017040297389030457, 0.0024719706270843744, 0.07849561423063278, 0.04765778034925461, -0.01834406889975071, 0.0031...
https://github.com/scikit-learn/scikit-learn/issues/28993
[ "Bug" ]
MemoryLeak in `LogisticRession` ### Describe the bug repro * Repeatedly call `LogisticRegression().fit(X, y)` on same size feature matrix. Or run the attached repro-script. expected * The max memory allocated is steady regardless the number of train calls. actual * Memory usage grows linear with the number...
28,993
[ 0.031968969851732254, 0.010626370087265968, 0.03381090983748436, 0.002432381035760045, 0.0730084627866745, 0.0005487326998263597, -0.030937040224671364, 0.012391279451549053, 0.017040297389030457, 0.0024719706270843744, 0.07849561423063278, 0.04765778034925461, -0.01834406889975071, 0.0031...
https://github.com/scikit-learn/scikit-learn/issues/28993
[ "Bug" ]
MemoryLeak in `LogisticRession` ### Describe the bug repro * Repeatedly call `LogisticRegression().fit(X, y)` on same size feature matrix. Or run the attached repro-script. expected * The max memory allocated is steady regardless the number of train calls. actual * Memory usage grows linear with the number...
28,993
[ 0.031968969851732254, 0.010626370087265968, 0.03381090983748436, 0.002432381035760045, 0.0730084627866745, 0.0005487326998263597, -0.030937040224671364, 0.012391279451549053, 0.017040297389030457, 0.0024719706270843744, 0.07849561423063278, 0.04765778034925461, -0.01834406889975071, 0.0031...
https://github.com/scikit-learn/scikit-learn/issues/28993
[ "Bug" ]
MemoryLeak in `LogisticRession` ### Describe the bug repro * Repeatedly call `LogisticRegression().fit(X, y)` on same size feature matrix. Or run the attached repro-script. expected * The max memory allocated is steady regardless the number of train calls. actual * Memory usage grows linear with the number...
28,993
[ 0.031968969851732254, 0.010626370087265968, 0.03381090983748436, 0.002432381035760045, 0.0730084627866745, 0.0005487326998263597, -0.030937040224671364, 0.012391279451549053, 0.017040297389030457, 0.0024719706270843744, 0.07849561423063278, 0.04765778034925461, -0.01834406889975071, 0.0031...
https://github.com/scikit-learn/scikit-learn/issues/28993
[ "Bug" ]
MemoryLeak in `LogisticRession` ### Describe the bug repro * Repeatedly call `LogisticRegression().fit(X, y)` on same size feature matrix. Or run the attached repro-script. expected * The max memory allocated is steady regardless the number of train calls. actual * Memory usage grows linear with the number...
28,993
[ 0.031968969851732254, 0.010626370087265968, 0.03381090983748436, 0.002432381035760045, 0.0730084627866745, 0.0005487326998263597, -0.030937040224671364, 0.012391279451549053, 0.017040297389030457, 0.0024719706270843744, 0.07849561423063278, 0.04765778034925461, -0.01834406889975071, 0.0031...
https://github.com/scikit-learn/scikit-learn/issues/28993
[ "Bug" ]
MemoryLeak in `LogisticRession` ### Describe the bug repro * Repeatedly call `LogisticRegression().fit(X, y)` on same size feature matrix. Or run the attached repro-script. expected * The max memory allocated is steady regardless the number of train calls. actual * Memory usage grows linear with the number...
28,993
[ 0.031968969851732254, 0.010626370087265968, 0.03381090983748436, 0.002432381035760045, 0.0730084627866745, 0.0005487326998263597, -0.030937040224671364, 0.012391279451549053, 0.017040297389030457, 0.0024719706270843744, 0.07849561423063278, 0.04765778034925461, -0.01834406889975071, 0.0031...
https://github.com/scikit-learn/scikit-learn/issues/28993
[ "Bug" ]
MemoryLeak in `LogisticRession` ### Describe the bug repro * Repeatedly call `LogisticRegression().fit(X, y)` on same size feature matrix. Or run the attached repro-script. expected * The max memory allocated is steady regardless the number of train calls. actual * Memory usage grows linear with the number...
28,993
[ 0.031968969851732254, 0.010626370087265968, 0.03381090983748436, 0.002432381035760045, 0.0730084627866745, 0.0005487326998263597, -0.030937040224671364, 0.012391279451549053, 0.017040297389030457, 0.0024719706270843744, 0.07849561423063278, 0.04765778034925461, -0.01834406889975071, 0.0031...
https://github.com/scikit-learn/scikit-learn/issues/28993
[ "Bug" ]
MemoryLeak in `LogisticRession` ### Describe the bug repro * Repeatedly call `LogisticRegression().fit(X, y)` on same size feature matrix. Or run the attached repro-script. expected * The max memory allocated is steady regardless the number of train calls. actual * Memory usage grows linear with the number...
28,993
[ 0.031968969851732254, 0.010626370087265968, 0.03381090983748436, 0.002432381035760045, 0.0730084627866745, 0.0005487326998263597, -0.030937040224671364, 0.012391279451549053, 0.017040297389030457, 0.0024719706270843744, 0.07849561423063278, 0.04765778034925461, -0.01834406889975071, 0.0031...
https://github.com/scikit-learn/scikit-learn/issues/28993
[ "Bug" ]
MemoryLeak in `LogisticRession` ### Describe the bug repro * Repeatedly call `LogisticRegression().fit(X, y)` on same size feature matrix. Or run the attached repro-script. expected * The max memory allocated is steady regardless the number of train calls. actual * Memory usage grows linear with the number...
28,993
[ 0.031968969851732254, 0.010626370087265968, 0.03381090983748436, 0.002432381035760045, 0.0730084627866745, 0.0005487326998263597, -0.030937040224671364, 0.012391279451549053, 0.017040297389030457, 0.0024719706270843744, 0.07849561423063278, 0.04765778034925461, -0.01834406889975071, 0.0031...
https://github.com/scikit-learn/scikit-learn/issues/28985
[ "Documentation", "Needs Triage" ]
What about negative coefficients / feature weights? ### Describe the issue linked to the documentation https://scikit-learn.org/stable/auto_examples/text/plot_document_classification_20newsgroups.html#model-without-metadata-stripping In this example, in the code for the function `plot_feature_effects` it sorts the...
28,985
[ -0.011530818417668343, 0.033603038638830185, 0.019776172935962677, 0.0038380268961191177, 0.02008328214287758, -0.01151364203542471, -0.007573713082820177, 0.006563230417668819, 0.004703938961029053, -0.030936002731323242, 0.008386239409446716, 0.01653842255473137, 0.04047270864248276, 0.0...
https://github.com/scikit-learn/scikit-learn/issues/28985
[ "Documentation", "Needs Triage" ]
What about negative coefficients / feature weights? ### Describe the issue linked to the documentation https://scikit-learn.org/stable/auto_examples/text/plot_document_classification_20newsgroups.html#model-without-metadata-stripping In this example, in the code for the function `plot_feature_effects` it sorts the...
28,985
[ 0.005592187866568565, -0.007047914434224367, 0.002132987603545189, 0.0007649389444850385, 0.010710598900914192, 7.496884535385107e-8, 0.005420878995209932, -0.0011681705946102738, -0.025332428514957428, -0.029117442667484283, 0.02182074449956417, 0.03709055855870247, 0.036195430904626846, ...
https://github.com/scikit-learn/scikit-learn/issues/28985
[ "Documentation", "Needs Triage" ]
What about negative coefficients / feature weights? ### Describe the issue linked to the documentation https://scikit-learn.org/stable/auto_examples/text/plot_document_classification_20newsgroups.html#model-without-metadata-stripping In this example, in the code for the function `plot_feature_effects` it sorts the...
28,985
[ 0.0022604644764214754, 0.014422833919525146, -0.004966699983924627, 0.005370474886149168, -0.0018329106969758868, -0.00043223483953624964, -0.002168295904994011, -0.007875187322497368, -0.022643636912107468, -0.0310855433344841, 0.03171546757221222, 0.022463031113147736, 0.04523060470819473,...
https://github.com/scikit-learn/scikit-learn/issues/28985
[ "Documentation", "Needs Triage" ]
What about negative coefficients / feature weights? ### Describe the issue linked to the documentation https://scikit-learn.org/stable/auto_examples/text/plot_document_classification_20newsgroups.html#model-without-metadata-stripping In this example, in the code for the function `plot_feature_effects` it sorts the...
28,985
[ -0.0006933552213013172, 0.0797325000166893, 0.00757664255797863, -0.0027971575036644936, 0.007894798181951046, 0.003226812928915024, -0.010781473480165005, 0.039840925484895706, 0.005829093977808952, -0.016710298135876656, 0.03275981917977333, 0.03841389715671539, 0.002024151384830475, 0.0...
https://github.com/scikit-learn/scikit-learn/issues/28985
[ "Documentation", "Needs Triage" ]
What about negative coefficients / feature weights? ### Describe the issue linked to the documentation https://scikit-learn.org/stable/auto_examples/text/plot_document_classification_20newsgroups.html#model-without-metadata-stripping In this example, in the code for the function `plot_feature_effects` it sorts the...
28,985
[ -0.016354646533727646, 0.033679962158203125, 0.002665288047865033, 0.004744523670524359, 0.016325099393725395, -0.010817774571478367, 0.02869196981191635, 0.016138756647706032, 0.014309477992355824, -0.03264695778489113, 0.020842628553509712, 0.05482242628931999, 0.02498963288962841, 0.060...
https://github.com/scikit-learn/scikit-learn/issues/28985
[ "Documentation", "Needs Triage" ]
What about negative coefficients / feature weights? ### Describe the issue linked to the documentation https://scikit-learn.org/stable/auto_examples/text/plot_document_classification_20newsgroups.html#model-without-metadata-stripping In this example, in the code for the function `plot_feature_effects` it sorts the...
28,985
[ -0.009881095960736275, 0.014309232123196125, 0.012756823562085629, 0.0035234512761235237, 0.026885798200964928, 0.006459245923906565, -0.0027533487882465124, -0.00015149472164921463, 0.025836672633886337, -0.012598969973623753, -0.005632507149130106, 0.02582494728267193, 0.023550523445010185...
https://github.com/scikit-learn/scikit-learn/issues/28985
[ "Documentation", "Needs Triage" ]
What about negative coefficients / feature weights? ### Describe the issue linked to the documentation https://scikit-learn.org/stable/auto_examples/text/plot_document_classification_20newsgroups.html#model-without-metadata-stripping In this example, in the code for the function `plot_feature_effects` it sorts the...
28,985
[ -0.001191207324154675, 0.03555157408118248, -0.0007349244551733136, -0.03129582479596138, 0.01257712859660387, 0.0033751986920833588, -0.002335047349333763, 0.027560260146856308, -0.0043596611358225346, -0.04421981796622276, 0.016641434282064438, 0.054808348417282104, 0.017412113025784492, ...
https://github.com/scikit-learn/scikit-learn/issues/28985
[ "Documentation", "Needs Triage" ]
What about negative coefficients / feature weights? ### Describe the issue linked to the documentation https://scikit-learn.org/stable/auto_examples/text/plot_document_classification_20newsgroups.html#model-without-metadata-stripping In this example, in the code for the function `plot_feature_effects` it sorts the...
28,985
[ 0.012002668343484402, 0.03498551994562149, 0.00998527742922306, -0.00033914591767825186, 0.010366433300077915, 0.004716286435723305, -0.006539531517773867, 0.03632570803165436, -0.0005212576943449676, -0.06385476887226105, 0.035114895552396774, 0.03294233977794647, 0.02190752699971199, 0.0...
https://github.com/scikit-learn/scikit-learn/issues/28985
[ "Documentation", "Needs Triage" ]
What about negative coefficients / feature weights? ### Describe the issue linked to the documentation https://scikit-learn.org/stable/auto_examples/text/plot_document_classification_20newsgroups.html#model-without-metadata-stripping In this example, in the code for the function `plot_feature_effects` it sorts the...
28,985
[ -0.008981147781014442, 0.007173687685281038, 0.02460700273513794, 0.02457767352461815, 0.04099734127521515, -0.007927429862320423, 0.024754781275987625, 0.020848602056503296, 0.020134473219513893, -0.027188053354620934, -0.017394091933965683, 0.042009077966213226, 0.034588027745485306, 0.0...
https://github.com/scikit-learn/scikit-learn/issues/28985
[ "Documentation", "Needs Triage" ]
What about negative coefficients / feature weights? ### Describe the issue linked to the documentation https://scikit-learn.org/stable/auto_examples/text/plot_document_classification_20newsgroups.html#model-without-metadata-stripping In this example, in the code for the function `plot_feature_effects` it sorts the...
28,985
[ -0.009182913228869438, 0.027464091777801514, 0.00899556465446949, 0.005444932729005814, 0.01602013222873211, -0.01615184359252453, 0.005255792755633593, 0.0161391980946064, 0.005830283276736736, -0.025918379426002502, 0.02315145917236805, 0.015511637553572655, 0.03810112923383713, 0.077381...
https://github.com/scikit-learn/scikit-learn/issues/28983
[ "Bug", "Needs Triage" ]
Saving and loading calibratedclassifierCV model (ensemble) ### Describe the bug Unable to load the saved calibratedclassifierCV model to a pickle file (.pkl) trained with cv=n as that is a list of models ### Steps/Code to Reproduce calibratedclassifier.dump('model.pkl') model= pickle.load('model.pkl') ### Expect...
28,983
[ -0.011021286249160767, 0.005693117156624794, 0.021642319858074188, 0.004336570389568806, 0.04086422920227051, 0.023129254579544067, 0.02755531296133995, 0.0209545586258173, 0.049655452370643616, -0.0193308237940073, 0.005874099209904671, 0.08112736791372299, 0.014089012518525124, -0.023987...
https://github.com/scikit-learn/scikit-learn/issues/28983
[ "Bug", "Needs Triage" ]
Saving and loading calibratedclassifierCV model (ensemble) ### Describe the bug Unable to load the saved calibratedclassifierCV model to a pickle file (.pkl) trained with cv=n as that is a list of models ### Steps/Code to Reproduce calibratedclassifier.dump('model.pkl') model= pickle.load('model.pkl') ### Expect...
28,983
[ -0.014334672130644321, -0.007559380494058132, 0.017236560583114624, 0.0056441486813127995, 0.05178380757570267, 0.026083456352353096, 0.0302931759506464, 0.01730365864932537, 0.06601755321025848, -0.008475661277770996, 0.006170032080262899, 0.07498762011528015, 0.00934007577598095, -0.0012...
https://github.com/scikit-learn/scikit-learn/issues/28983
[ "Bug", "Needs Triage" ]
Saving and loading calibratedclassifierCV model (ensemble) ### Describe the bug Unable to load the saved calibratedclassifierCV model to a pickle file (.pkl) trained with cv=n as that is a list of models ### Steps/Code to Reproduce calibratedclassifier.dump('model.pkl') model= pickle.load('model.pkl') ### Expect...
28,983
[ -0.013591731898486614, 0.004029980394989252, 0.020727772265672684, -0.0035197956021875143, 0.030603915452957153, 0.01661400869488716, 0.021903088316321373, 0.01601565070450306, 0.063931904733181, -0.016021881252527237, 0.0261515025049448, 0.07820668816566467, 0.011440301313996315, 0.011024...
https://github.com/scikit-learn/scikit-learn/issues/28982
[ "Enhancement" ]
Add zero_division for single class prediction in MCC ### Describe the bug I have found a potential edge case issue with _sklearn.metrics.matthews_corrcoef_. The example provided in the documentation works as expected: ```python from sklearn.metrics import matthews_corrcoef matthews_corrcoef([1, 1, 1, -1], [1, -1...
28,982
[ -0.023953184485435486, 0.0012343137059360743, 0.04545677825808525, -0.007837574928998947, 0.04109347239136696, -0.013743645511567593, 0.04764343053102493, -0.004151601810008287, -0.07999181002378464, -0.03227755054831505, 0.05730704963207245, 0.040024418383836746, -0.00938377808779478, 0.0...
https://github.com/scikit-learn/scikit-learn/issues/28982
[ "Enhancement" ]
Add zero_division for single class prediction in MCC ### Describe the bug I have found a potential edge case issue with _sklearn.metrics.matthews_corrcoef_. The example provided in the documentation works as expected: ```python from sklearn.metrics import matthews_corrcoef matthews_corrcoef([1, 1, 1, -1], [1, -1...
28,982
[ -0.023953184485435486, 0.0012343137059360743, 0.04545677825808525, -0.007837574928998947, 0.04109347239136696, -0.013743645511567593, 0.04764343053102493, -0.004151601810008287, -0.07999181002378464, -0.03227755054831505, 0.05730704963207245, 0.040024418383836746, -0.00938377808779478, 0.0...
https://github.com/scikit-learn/scikit-learn/issues/28982
[ "Enhancement" ]
Add zero_division for single class prediction in MCC ### Describe the bug I have found a potential edge case issue with _sklearn.metrics.matthews_corrcoef_. The example provided in the documentation works as expected: ```python from sklearn.metrics import matthews_corrcoef matthews_corrcoef([1, 1, 1, -1], [1, -1...
28,982
[ -0.023953184485435486, 0.0012343137059360743, 0.04545677825808525, -0.007837574928998947, 0.04109347239136696, -0.013743645511567593, 0.04764343053102493, -0.004151601810008287, -0.07999181002378464, -0.03227755054831505, 0.05730704963207245, 0.040024418383836746, -0.00938377808779478, 0.0...
https://github.com/scikit-learn/scikit-learn/issues/28982
[ "Enhancement" ]
Add zero_division for single class prediction in MCC ### Describe the bug I have found a potential edge case issue with _sklearn.metrics.matthews_corrcoef_. The example provided in the documentation works as expected: ```python from sklearn.metrics import matthews_corrcoef matthews_corrcoef([1, 1, 1, -1], [1, -1...
28,982
[ -0.023953184485435486, 0.0012343137059360743, 0.04545677825808525, -0.007837574928998947, 0.04109347239136696, -0.013743645511567593, 0.04764343053102493, -0.004151601810008287, -0.07999181002378464, -0.03227755054831505, 0.05730704963207245, 0.040024418383836746, -0.00938377808779478, 0.0...
https://github.com/scikit-learn/scikit-learn/issues/28979
[ "Documentation" ]
Documentation says scikit-learn latest versions still supports Python 3.8 ### Describe the issue linked to the documentation https://scikit-learn.org/stable/install.html#installing-the-latest-release "Scikit-learn 1.1 and later requires Python 3.8 or newer" The latest versions of scikit-learn require Python 3.9 o...
28,979
[ 0.0253765769302845, -0.014478230848908424, -0.00475273234769702, -0.07681506872177124, 0.004183504730463028, 0.02101021073758602, 0.037928398698568344, 0.03594814985990524, 0.03958902880549431, -0.05460791662335396, 0.05541306361556053, 0.07798753678798676, -0.01219113264232874, 0.01823966...
https://github.com/scikit-learn/scikit-learn/issues/28979
[ "Documentation" ]
Documentation says scikit-learn latest versions still supports Python 3.8 ### Describe the issue linked to the documentation https://scikit-learn.org/stable/install.html#installing-the-latest-release "Scikit-learn 1.1 and later requires Python 3.8 or newer" The latest versions of scikit-learn require Python 3.9 o...
28,979
[ 0.019907061010599136, -0.01625428907573223, 0.0030371618922799826, -0.06513991206884384, 0.007569344714283943, 0.028811965137720108, 0.04367075860500336, 0.03836365416646004, 0.07435378432273865, -0.051363781094551086, 0.04526970535516739, 0.08314931392669678, -0.020789504051208496, 0.0174...
https://github.com/scikit-learn/scikit-learn/issues/28978
[ "Enhancement", "Build / CI", "free-threading" ]
Add support for Python 3.13 free-threaded build I'm currently working on adding support for the Python 3.13 free-threaded build to projects in the scientific python ecosystem. We are tracking this work at https://github.com/Quansight-Labs/free-threaded-compatibility. Right now we're focusing on projects relatively low...
28,978
[ -0.03406526520848274, 0.031072910875082016, -0.014937670901417732, -0.033101193606853485, 0.014081696979701519, 0.057966239750385284, 0.03666118159890175, 0.060641657561063766, 0.05072163790464401, -0.012288719415664673, 0.02741960994899273, 0.07102297991514206, -0.038458772003650665, 0.02...
https://github.com/scikit-learn/scikit-learn/issues/28978
[ "Enhancement", "Build / CI", "free-threading" ]
Add support for Python 3.13 free-threaded build I'm currently working on adding support for the Python 3.13 free-threaded build to projects in the scientific python ecosystem. We are tracking this work at https://github.com/Quansight-Labs/free-threaded-compatibility. Right now we're focusing on projects relatively low...
28,978
[ -0.03406526520848274, 0.031072910875082016, -0.014937670901417732, -0.033101193606853485, 0.014081696979701519, 0.057966239750385284, 0.03666118159890175, 0.060641657561063766, 0.05072163790464401, -0.012288719415664673, 0.02741960994899273, 0.07102297991514206, -0.038458772003650665, 0.02...
https://github.com/scikit-learn/scikit-learn/issues/28978
[ "Enhancement", "Build / CI", "free-threading" ]
Add support for Python 3.13 free-threaded build I'm currently working on adding support for the Python 3.13 free-threaded build to projects in the scientific python ecosystem. We are tracking this work at https://github.com/Quansight-Labs/free-threaded-compatibility. Right now we're focusing on projects relatively low...
28,978
[ -0.03406526520848274, 0.031072910875082016, -0.014937670901417732, -0.033101193606853485, 0.014081696979701519, 0.057966239750385284, 0.03666118159890175, 0.060641657561063766, 0.05072163790464401, -0.012288719415664673, 0.02741960994899273, 0.07102297991514206, -0.038458772003650665, 0.02...
https://github.com/scikit-learn/scikit-learn/issues/28978
[ "Enhancement", "Build / CI", "free-threading" ]
Add support for Python 3.13 free-threaded build I'm currently working on adding support for the Python 3.13 free-threaded build to projects in the scientific python ecosystem. We are tracking this work at https://github.com/Quansight-Labs/free-threaded-compatibility. Right now we're focusing on projects relatively low...
28,978
[ -0.03406526520848274, 0.031072910875082016, -0.014937670901417732, -0.033101193606853485, 0.014081696979701519, 0.057966239750385284, 0.03666118159890175, 0.060641657561063766, 0.05072163790464401, -0.012288719415664673, 0.02741960994899273, 0.07102297991514206, -0.038458772003650665, 0.02...
https://github.com/scikit-learn/scikit-learn/issues/28978
[ "Enhancement", "Build / CI", "free-threading" ]
Add support for Python 3.13 free-threaded build I'm currently working on adding support for the Python 3.13 free-threaded build to projects in the scientific python ecosystem. We are tracking this work at https://github.com/Quansight-Labs/free-threaded-compatibility. Right now we're focusing on projects relatively low...
28,978
[ -0.03406526520848274, 0.031072910875082016, -0.014937670901417732, -0.033101193606853485, 0.014081696979701519, 0.057966239750385284, 0.03666118159890175, 0.060641657561063766, 0.05072163790464401, -0.012288719415664673, 0.02741960994899273, 0.07102297991514206, -0.038458772003650665, 0.02...
https://github.com/scikit-learn/scikit-learn/issues/28978
[ "Enhancement", "Build / CI", "free-threading" ]
Add support for Python 3.13 free-threaded build I'm currently working on adding support for the Python 3.13 free-threaded build to projects in the scientific python ecosystem. We are tracking this work at https://github.com/Quansight-Labs/free-threaded-compatibility. Right now we're focusing on projects relatively low...
28,978
[ -0.03406526520848274, 0.031072910875082016, -0.014937670901417732, -0.033101193606853485, 0.014081696979701519, 0.057966239750385284, 0.03666118159890175, 0.060641657561063766, 0.05072163790464401, -0.012288719415664673, 0.02741960994899273, 0.07102297991514206, -0.038458772003650665, 0.02...
https://github.com/scikit-learn/scikit-learn/issues/28978
[ "Enhancement", "Build / CI", "free-threading" ]
Add support for Python 3.13 free-threaded build I'm currently working on adding support for the Python 3.13 free-threaded build to projects in the scientific python ecosystem. We are tracking this work at https://github.com/Quansight-Labs/free-threaded-compatibility. Right now we're focusing on projects relatively low...
28,978
[ -0.03406526520848274, 0.031072910875082016, -0.014937670901417732, -0.033101193606853485, 0.014081696979701519, 0.057966239750385284, 0.03666118159890175, 0.060641657561063766, 0.05072163790464401, -0.012288719415664673, 0.02741960994899273, 0.07102297991514206, -0.038458772003650665, 0.02...
https://github.com/scikit-learn/scikit-learn/issues/28978
[ "Enhancement", "Build / CI", "free-threading" ]
Add support for Python 3.13 free-threaded build I'm currently working on adding support for the Python 3.13 free-threaded build to projects in the scientific python ecosystem. We are tracking this work at https://github.com/Quansight-Labs/free-threaded-compatibility. Right now we're focusing on projects relatively low...
28,978
[ -0.03406526520848274, 0.031072910875082016, -0.014937670901417732, -0.033101193606853485, 0.014081696979701519, 0.057966239750385284, 0.03666118159890175, 0.060641657561063766, 0.05072163790464401, -0.012288719415664673, 0.02741960994899273, 0.07102297991514206, -0.038458772003650665, 0.02...
https://github.com/scikit-learn/scikit-learn/issues/28978
[ "Enhancement", "Build / CI", "free-threading" ]
Add support for Python 3.13 free-threaded build I'm currently working on adding support for the Python 3.13 free-threaded build to projects in the scientific python ecosystem. We are tracking this work at https://github.com/Quansight-Labs/free-threaded-compatibility. Right now we're focusing on projects relatively low...
28,978
[ -0.03406526520848274, 0.031072910875082016, -0.014937670901417732, -0.033101193606853485, 0.014081696979701519, 0.057966239750385284, 0.03666118159890175, 0.060641657561063766, 0.05072163790464401, -0.012288719415664673, 0.02741960994899273, 0.07102297991514206, -0.038458772003650665, 0.02...
https://github.com/scikit-learn/scikit-learn/issues/28978
[ "Enhancement", "Build / CI", "free-threading" ]
Add support for Python 3.13 free-threaded build I'm currently working on adding support for the Python 3.13 free-threaded build to projects in the scientific python ecosystem. We are tracking this work at https://github.com/Quansight-Labs/free-threaded-compatibility. Right now we're focusing on projects relatively low...
28,978
[ -0.03406526520848274, 0.031072910875082016, -0.014937670901417732, -0.033101193606853485, 0.014081696979701519, 0.057966239750385284, 0.03666118159890175, 0.060641657561063766, 0.05072163790464401, -0.012288719415664673, 0.02741960994899273, 0.07102297991514206, -0.038458772003650665, 0.02...
https://github.com/scikit-learn/scikit-learn/issues/28978
[ "Enhancement", "Build / CI", "free-threading" ]
Add support for Python 3.13 free-threaded build I'm currently working on adding support for the Python 3.13 free-threaded build to projects in the scientific python ecosystem. We are tracking this work at https://github.com/Quansight-Labs/free-threaded-compatibility. Right now we're focusing on projects relatively low...
28,978
[ -0.03406526520848274, 0.031072910875082016, -0.014937670901417732, -0.033101193606853485, 0.014081696979701519, 0.057966239750385284, 0.03666118159890175, 0.060641657561063766, 0.05072163790464401, -0.012288719415664673, 0.02741960994899273, 0.07102297991514206, -0.038458772003650665, 0.02...
https://github.com/scikit-learn/scikit-learn/issues/28978
[ "Enhancement", "Build / CI", "free-threading" ]
Add support for Python 3.13 free-threaded build I'm currently working on adding support for the Python 3.13 free-threaded build to projects in the scientific python ecosystem. We are tracking this work at https://github.com/Quansight-Labs/free-threaded-compatibility. Right now we're focusing on projects relatively low...
28,978
[ -0.03406526520848274, 0.031072910875082016, -0.014937670901417732, -0.033101193606853485, 0.014081696979701519, 0.057966239750385284, 0.03666118159890175, 0.060641657561063766, 0.05072163790464401, -0.012288719415664673, 0.02741960994899273, 0.07102297991514206, -0.038458772003650665, 0.02...
https://github.com/scikit-learn/scikit-learn/issues/28978
[ "Enhancement", "Build / CI", "free-threading" ]
Add support for Python 3.13 free-threaded build I'm currently working on adding support for the Python 3.13 free-threaded build to projects in the scientific python ecosystem. We are tracking this work at https://github.com/Quansight-Labs/free-threaded-compatibility. Right now we're focusing on projects relatively low...
28,978
[ -0.03406526520848274, 0.031072910875082016, -0.014937670901417732, -0.033101193606853485, 0.014081696979701519, 0.057966239750385284, 0.03666118159890175, 0.060641657561063766, 0.05072163790464401, -0.012288719415664673, 0.02741960994899273, 0.07102297991514206, -0.038458772003650665, 0.02...
https://github.com/scikit-learn/scikit-learn/issues/28978
[ "Enhancement", "Build / CI", "free-threading" ]
Add support for Python 3.13 free-threaded build I'm currently working on adding support for the Python 3.13 free-threaded build to projects in the scientific python ecosystem. We are tracking this work at https://github.com/Quansight-Labs/free-threaded-compatibility. Right now we're focusing on projects relatively low...
28,978
[ -0.03406526520848274, 0.031072910875082016, -0.014937670901417732, -0.033101193606853485, 0.014081696979701519, 0.057966239750385284, 0.03666118159890175, 0.060641657561063766, 0.05072163790464401, -0.012288719415664673, 0.02741960994899273, 0.07102297991514206, -0.038458772003650665, 0.02...
https://github.com/scikit-learn/scikit-learn/issues/28978
[ "Enhancement", "Build / CI", "free-threading" ]
Add support for Python 3.13 free-threaded build I'm currently working on adding support for the Python 3.13 free-threaded build to projects in the scientific python ecosystem. We are tracking this work at https://github.com/Quansight-Labs/free-threaded-compatibility. Right now we're focusing on projects relatively low...
28,978
[ -0.03406526520848274, 0.031072910875082016, -0.014937670901417732, -0.033101193606853485, 0.014081696979701519, 0.057966239750385284, 0.03666118159890175, 0.060641657561063766, 0.05072163790464401, -0.012288719415664673, 0.02741960994899273, 0.07102297991514206, -0.038458772003650665, 0.02...
https://github.com/scikit-learn/scikit-learn/issues/28978
[ "Enhancement", "Build / CI", "free-threading" ]
Add support for Python 3.13 free-threaded build I'm currently working on adding support for the Python 3.13 free-threaded build to projects in the scientific python ecosystem. We are tracking this work at https://github.com/Quansight-Labs/free-threaded-compatibility. Right now we're focusing on projects relatively low...
28,978
[ -0.03406526520848274, 0.031072910875082016, -0.014937670901417732, -0.033101193606853485, 0.014081696979701519, 0.057966239750385284, 0.03666118159890175, 0.060641657561063766, 0.05072163790464401, -0.012288719415664673, 0.02741960994899273, 0.07102297991514206, -0.038458772003650665, 0.02...
https://github.com/scikit-learn/scikit-learn/issues/28978
[ "Enhancement", "Build / CI", "free-threading" ]
Add support for Python 3.13 free-threaded build I'm currently working on adding support for the Python 3.13 free-threaded build to projects in the scientific python ecosystem. We are tracking this work at https://github.com/Quansight-Labs/free-threaded-compatibility. Right now we're focusing on projects relatively low...
28,978
[ -0.03406526520848274, 0.031072910875082016, -0.014937670901417732, -0.033101193606853485, 0.014081696979701519, 0.057966239750385284, 0.03666118159890175, 0.060641657561063766, 0.05072163790464401, -0.012288719415664673, 0.02741960994899273, 0.07102297991514206, -0.038458772003650665, 0.02...
https://github.com/scikit-learn/scikit-learn/issues/28978
[ "Enhancement", "Build / CI", "free-threading" ]
Add support for Python 3.13 free-threaded build I'm currently working on adding support for the Python 3.13 free-threaded build to projects in the scientific python ecosystem. We are tracking this work at https://github.com/Quansight-Labs/free-threaded-compatibility. Right now we're focusing on projects relatively low...
28,978
[ -0.03406526520848274, 0.031072910875082016, -0.014937670901417732, -0.033101193606853485, 0.014081696979701519, 0.057966239750385284, 0.03666118159890175, 0.060641657561063766, 0.05072163790464401, -0.012288719415664673, 0.02741960994899273, 0.07102297991514206, -0.038458772003650665, 0.02...
https://github.com/scikit-learn/scikit-learn/issues/28978
[ "Enhancement", "Build / CI", "free-threading" ]
Add support for Python 3.13 free-threaded build I'm currently working on adding support for the Python 3.13 free-threaded build to projects in the scientific python ecosystem. We are tracking this work at https://github.com/Quansight-Labs/free-threaded-compatibility. Right now we're focusing on projects relatively low...
28,978
[ -0.03406526520848274, 0.031072910875082016, -0.014937670901417732, -0.033101193606853485, 0.014081696979701519, 0.057966239750385284, 0.03666118159890175, 0.060641657561063766, 0.05072163790464401, -0.012288719415664673, 0.02741960994899273, 0.07102297991514206, -0.038458772003650665, 0.02...
https://github.com/scikit-learn/scikit-learn/issues/28978
[ "Enhancement", "Build / CI", "free-threading" ]
Add support for Python 3.13 free-threaded build I'm currently working on adding support for the Python 3.13 free-threaded build to projects in the scientific python ecosystem. We are tracking this work at https://github.com/Quansight-Labs/free-threaded-compatibility. Right now we're focusing on projects relatively low...
28,978
[ -0.03406526520848274, 0.031072910875082016, -0.014937670901417732, -0.033101193606853485, 0.014081696979701519, 0.057966239750385284, 0.03666118159890175, 0.060641657561063766, 0.05072163790464401, -0.012288719415664673, 0.02741960994899273, 0.07102297991514206, -0.038458772003650665, 0.02...
https://github.com/scikit-learn/scikit-learn/issues/28978
[ "Enhancement", "Build / CI", "free-threading" ]
Add support for Python 3.13 free-threaded build I'm currently working on adding support for the Python 3.13 free-threaded build to projects in the scientific python ecosystem. We are tracking this work at https://github.com/Quansight-Labs/free-threaded-compatibility. Right now we're focusing on projects relatively low...
28,978
[ -0.03406526520848274, 0.031072910875082016, -0.014937670901417732, -0.033101193606853485, 0.014081696979701519, 0.057966239750385284, 0.03666118159890175, 0.060641657561063766, 0.05072163790464401, -0.012288719415664673, 0.02741960994899273, 0.07102297991514206, -0.038458772003650665, 0.02...
https://github.com/scikit-learn/scikit-learn/issues/28978
[ "Enhancement", "Build / CI", "free-threading" ]
Add support for Python 3.13 free-threaded build I'm currently working on adding support for the Python 3.13 free-threaded build to projects in the scientific python ecosystem. We are tracking this work at https://github.com/Quansight-Labs/free-threaded-compatibility. Right now we're focusing on projects relatively low...
28,978
[ -0.03406526520848274, 0.031072910875082016, -0.014937670901417732, -0.033101193606853485, 0.014081696979701519, 0.057966239750385284, 0.03666118159890175, 0.060641657561063766, 0.05072163790464401, -0.012288719415664673, 0.02741960994899273, 0.07102297991514206, -0.038458772003650665, 0.02...
https://github.com/scikit-learn/scikit-learn/issues/28978
[ "Enhancement", "Build / CI", "free-threading" ]
Add support for Python 3.13 free-threaded build I'm currently working on adding support for the Python 3.13 free-threaded build to projects in the scientific python ecosystem. We are tracking this work at https://github.com/Quansight-Labs/free-threaded-compatibility. Right now we're focusing on projects relatively low...
28,978
[ -0.03406526520848274, 0.031072910875082016, -0.014937670901417732, -0.033101193606853485, 0.014081696979701519, 0.057966239750385284, 0.03666118159890175, 0.060641657561063766, 0.05072163790464401, -0.012288719415664673, 0.02741960994899273, 0.07102297991514206, -0.038458772003650665, 0.02...
https://github.com/scikit-learn/scikit-learn/issues/28978
[ "Enhancement", "Build / CI", "free-threading" ]
Add support for Python 3.13 free-threaded build I'm currently working on adding support for the Python 3.13 free-threaded build to projects in the scientific python ecosystem. We are tracking this work at https://github.com/Quansight-Labs/free-threaded-compatibility. Right now we're focusing on projects relatively low...
28,978
[ -0.03406526520848274, 0.031072910875082016, -0.014937670901417732, -0.033101193606853485, 0.014081696979701519, 0.057966239750385284, 0.03666118159890175, 0.060641657561063766, 0.05072163790464401, -0.012288719415664673, 0.02741960994899273, 0.07102297991514206, -0.038458772003650665, 0.02...
https://github.com/scikit-learn/scikit-learn/issues/28978
[ "Enhancement", "Build / CI", "free-threading" ]
Add support for Python 3.13 free-threaded build I'm currently working on adding support for the Python 3.13 free-threaded build to projects in the scientific python ecosystem. We are tracking this work at https://github.com/Quansight-Labs/free-threaded-compatibility. Right now we're focusing on projects relatively low...
28,978
[ -0.03406526520848274, 0.031072910875082016, -0.014937670901417732, -0.033101193606853485, 0.014081696979701519, 0.057966239750385284, 0.03666118159890175, 0.060641657561063766, 0.05072163790464401, -0.012288719415664673, 0.02741960994899273, 0.07102297991514206, -0.038458772003650665, 0.02...
https://github.com/scikit-learn/scikit-learn/issues/28978
[ "Enhancement", "Build / CI", "free-threading" ]
Add support for Python 3.13 free-threaded build I'm currently working on adding support for the Python 3.13 free-threaded build to projects in the scientific python ecosystem. We are tracking this work at https://github.com/Quansight-Labs/free-threaded-compatibility. Right now we're focusing on projects relatively low...
28,978
[ -0.03406526520848274, 0.031072910875082016, -0.014937670901417732, -0.033101193606853485, 0.014081696979701519, 0.057966239750385284, 0.03666118159890175, 0.060641657561063766, 0.05072163790464401, -0.012288719415664673, 0.02741960994899273, 0.07102297991514206, -0.038458772003650665, 0.02...
https://github.com/scikit-learn/scikit-learn/issues/28978
[ "Enhancement", "Build / CI", "free-threading" ]
Add support for Python 3.13 free-threaded build I'm currently working on adding support for the Python 3.13 free-threaded build to projects in the scientific python ecosystem. We are tracking this work at https://github.com/Quansight-Labs/free-threaded-compatibility. Right now we're focusing on projects relatively low...
28,978
[ -0.03406526520848274, 0.031072910875082016, -0.014937670901417732, -0.033101193606853485, 0.014081696979701519, 0.057966239750385284, 0.03666118159890175, 0.060641657561063766, 0.05072163790464401, -0.012288719415664673, 0.02741960994899273, 0.07102297991514206, -0.038458772003650665, 0.02...
https://github.com/scikit-learn/scikit-learn/issues/28978
[ "Enhancement", "Build / CI", "free-threading" ]
Add support for Python 3.13 free-threaded build I'm currently working on adding support for the Python 3.13 free-threaded build to projects in the scientific python ecosystem. We are tracking this work at https://github.com/Quansight-Labs/free-threaded-compatibility. Right now we're focusing on projects relatively low...
28,978
[ -0.03406526520848274, 0.031072910875082016, -0.014937670901417732, -0.033101193606853485, 0.014081696979701519, 0.057966239750385284, 0.03666118159890175, 0.060641657561063766, 0.05072163790464401, -0.012288719415664673, 0.02741960994899273, 0.07102297991514206, -0.038458772003650665, 0.02...
https://github.com/scikit-learn/scikit-learn/issues/28978
[ "Enhancement", "Build / CI", "free-threading" ]
Add support for Python 3.13 free-threaded build I'm currently working on adding support for the Python 3.13 free-threaded build to projects in the scientific python ecosystem. We are tracking this work at https://github.com/Quansight-Labs/free-threaded-compatibility. Right now we're focusing on projects relatively low...
28,978
[ -0.03406526520848274, 0.031072910875082016, -0.014937670901417732, -0.033101193606853485, 0.014081696979701519, 0.057966239750385284, 0.03666118159890175, 0.060641657561063766, 0.05072163790464401, -0.012288719415664673, 0.02741960994899273, 0.07102297991514206, -0.038458772003650665, 0.02...
https://github.com/scikit-learn/scikit-learn/issues/28978
[ "Enhancement", "Build / CI", "free-threading" ]
Add support for Python 3.13 free-threaded build I'm currently working on adding support for the Python 3.13 free-threaded build to projects in the scientific python ecosystem. We are tracking this work at https://github.com/Quansight-Labs/free-threaded-compatibility. Right now we're focusing on projects relatively low...
28,978
[ -0.03406526520848274, 0.031072910875082016, -0.014937670901417732, -0.033101193606853485, 0.014081696979701519, 0.057966239750385284, 0.03666118159890175, 0.060641657561063766, 0.05072163790464401, -0.012288719415664673, 0.02741960994899273, 0.07102297991514206, -0.038458772003650665, 0.02...
https://github.com/scikit-learn/scikit-learn/issues/28977
[ "Bug", "free-threading" ]
Consider bumping C standard in meson.build from C99 to C17 ### Describe the bug Currently, trying to build scikit-learn with the python 3.13 free-threaded build leads to a compilation error related to usage of `static_assert` in CPython internals. This leaks into public code via cython's adding `#include "internal/py...
28,977
[ -0.011413424275815487, 0.020646750926971436, 0.00240618665702641, -0.010219220072031021, 0.04794389382004738, 0.04026980698108673, -0.032476894557476044, 0.005306183360517025, -0.04096498712897301, -0.032038651406764984, 0.057861898094415665, 0.060229938477277756, -0.02992292121052742, 0.0...
https://github.com/scikit-learn/scikit-learn/issues/28977
[ "Bug", "free-threading" ]
Consider bumping C standard in meson.build from C99 to C17 ### Describe the bug Currently, trying to build scikit-learn with the python 3.13 free-threaded build leads to a compilation error related to usage of `static_assert` in CPython internals. This leaks into public code via cython's adding `#include "internal/py...
28,977
[ -0.011413424275815487, 0.020646750926971436, 0.00240618665702641, -0.010219220072031021, 0.04794389382004738, 0.04026980698108673, -0.032476894557476044, 0.005306183360517025, -0.04096498712897301, -0.032038651406764984, 0.057861898094415665, 0.060229938477277756, -0.02992292121052742, 0.0...
https://github.com/scikit-learn/scikit-learn/issues/28976
[ "Documentation", "help wanted" ]
`min_samples` in HDSCAN ### Describe the issue linked to the documentation I find the description of the `min_samples` argument in sklearn.cluster.HDBSCAN confusing. It says "The number of samples in a neighborhood for a point to be considered as a core point. This includes the point itself." But if I understan...
28,976
[ -0.016177332028746605, -0.12555009126663208, 0.0021672651637345552, -0.0409870371222496, -0.07424838095903397, 0.02903672121465206, 0.055093955248594284, 0.012715560384094715, 0.02934245578944683, 0.038583047688007355, 0.048613812774419785, 0.001634593354538083, 0.052212346345186234, -0.04...
https://github.com/scikit-learn/scikit-learn/issues/28976
[ "Documentation", "help wanted" ]
`min_samples` in HDSCAN ### Describe the issue linked to the documentation I find the description of the `min_samples` argument in sklearn.cluster.HDBSCAN confusing. It says "The number of samples in a neighborhood for a point to be considered as a core point. This includes the point itself." But if I understan...
28,976
[ -0.016177332028746605, -0.12555009126663208, 0.0021672651637345552, -0.0409870371222496, -0.07424838095903397, 0.02903672121465206, 0.055093955248594284, 0.012715560384094715, 0.02934245578944683, 0.038583047688007355, 0.048613812774419785, 0.001634593354538083, 0.052212346345186234, -0.04...
https://github.com/scikit-learn/scikit-learn/issues/28976
[ "Documentation", "help wanted" ]
`min_samples` in HDSCAN ### Describe the issue linked to the documentation I find the description of the `min_samples` argument in sklearn.cluster.HDBSCAN confusing. It says "The number of samples in a neighborhood for a point to be considered as a core point. This includes the point itself." But if I understan...
28,976
[ -0.016177332028746605, -0.12555009126663208, 0.0021672651637345552, -0.0409870371222496, -0.07424838095903397, 0.02903672121465206, 0.055093955248594284, 0.012715560384094715, 0.02934245578944683, 0.038583047688007355, 0.048613812774419785, 0.001634593354538083, 0.052212346345186234, -0.04...
https://github.com/scikit-learn/scikit-learn/issues/28970
[ "New Feature", "Needs Triage" ]
User Should Have An Option To Assign Different criterions With Different Percentage Of Trees In Random Forest ## Describe the workflow you want to enable ### **Detailed Explanation Of Proposed Workflow** User can mention how many percentage of trees in `sklearn.ensemble.RandomForestClassifier` & `sklearn.ensembl...
28,970
[ 0.04678104817867279, 0.013721492141485214, 0.01503198966383934, -0.022904638200998306, -0.005829210393130779, -0.024493753910064697, -0.04277343675494194, 0.022958720102906227, -0.01677621714770794, -0.03856397420167923, -0.015632594004273415, 0.01122595090419054, -0.04384559392929077, 0.0...
https://github.com/scikit-learn/scikit-learn/issues/28970
[ "New Feature", "Needs Triage" ]
User Should Have An Option To Assign Different criterions With Different Percentage Of Trees In Random Forest ## Describe the workflow you want to enable ### **Detailed Explanation Of Proposed Workflow** User can mention how many percentage of trees in `sklearn.ensemble.RandomForestClassifier` & `sklearn.ensembl...
28,970
[ 0.04678104817867279, 0.013721492141485214, 0.01503198966383934, -0.022904638200998306, -0.005829210393130779, -0.024493753910064697, -0.04277343675494194, 0.022958720102906227, -0.01677621714770794, -0.03856397420167923, -0.015632594004273415, 0.01122595090419054, -0.04384559392929077, 0.0...
https://github.com/scikit-learn/scikit-learn/issues/28970
[ "New Feature", "Needs Triage" ]
User Should Have An Option To Assign Different criterions With Different Percentage Of Trees In Random Forest ## Describe the workflow you want to enable ### **Detailed Explanation Of Proposed Workflow** User can mention how many percentage of trees in `sklearn.ensemble.RandomForestClassifier` & `sklearn.ensembl...
28,970
[ 0.04678104817867279, 0.013721492141485214, 0.01503198966383934, -0.022904638200998306, -0.005829210393130779, -0.024493753910064697, -0.04277343675494194, 0.022958720102906227, -0.01677621714770794, -0.03856397420167923, -0.015632594004273415, 0.01122595090419054, -0.04384559392929077, 0.0...
https://github.com/scikit-learn/scikit-learn/issues/28966
[ "Documentation", "Developer API" ]
Is it intention to drop `check_estimator_sparse_data` in 1.5? ### Describe the bug While running the 1.5.0 release candidate, my collaborator @FBruzzesi on scikit-lego ran our testing suite and [noticed something breaking](https://github.com/FBruzzesi/scikit-lego/actions/runs/8975596456/job/24650556520). Here's the e...
28,966
[ 0.013902181759476662, 0.05720460042357445, 0.004220428876578808, -0.012677812948822975, 0.007223752327263355, 0.0015129304956644773, 0.07057303190231323, 0.026346584782004356, 0.0027288724668323994, 0.0011211953824386, 0.04373392090201378, 0.012030712328851223, -0.001041959272697568, 0.008...
https://github.com/scikit-learn/scikit-learn/issues/28966
[ "Documentation", "Developer API" ]
Is it intention to drop `check_estimator_sparse_data` in 1.5? ### Describe the bug While running the 1.5.0 release candidate, my collaborator @FBruzzesi on scikit-lego ran our testing suite and [noticed something breaking](https://github.com/FBruzzesi/scikit-lego/actions/runs/8975596456/job/24650556520). Here's the e...
28,966
[ 0.013902181759476662, 0.05720460042357445, 0.004220428876578808, -0.012677812948822975, 0.007223752327263355, 0.0015129304956644773, 0.07057303190231323, 0.026346584782004356, 0.0027288724668323994, 0.0011211953824386, 0.04373392090201378, 0.012030712328851223, -0.001041959272697568, 0.008...
https://github.com/scikit-learn/scikit-learn/issues/28966
[ "Documentation", "Developer API" ]
Is it intention to drop `check_estimator_sparse_data` in 1.5? ### Describe the bug While running the 1.5.0 release candidate, my collaborator @FBruzzesi on scikit-lego ran our testing suite and [noticed something breaking](https://github.com/FBruzzesi/scikit-lego/actions/runs/8975596456/job/24650556520). Here's the e...
28,966
[ 0.013902181759476662, 0.05720460042357445, 0.004220428876578808, -0.012677812948822975, 0.007223752327263355, 0.0015129304956644773, 0.07057303190231323, 0.026346584782004356, 0.0027288724668323994, 0.0011211953824386, 0.04373392090201378, 0.012030712328851223, -0.001041959272697568, 0.008...
https://github.com/scikit-learn/scikit-learn/issues/28966
[ "Documentation", "Developer API" ]
Is it intention to drop `check_estimator_sparse_data` in 1.5? ### Describe the bug While running the 1.5.0 release candidate, my collaborator @FBruzzesi on scikit-lego ran our testing suite and [noticed something breaking](https://github.com/FBruzzesi/scikit-lego/actions/runs/8975596456/job/24650556520). Here's the e...
28,966
[ 0.013902181759476662, 0.05720460042357445, 0.004220428876578808, -0.012677812948822975, 0.007223752327263355, 0.0015129304956644773, 0.07057303190231323, 0.026346584782004356, 0.0027288724668323994, 0.0011211953824386, 0.04373392090201378, 0.012030712328851223, -0.001041959272697568, 0.008...
https://github.com/scikit-learn/scikit-learn/issues/28966
[ "Documentation", "Developer API" ]
Is it intention to drop `check_estimator_sparse_data` in 1.5? ### Describe the bug While running the 1.5.0 release candidate, my collaborator @FBruzzesi on scikit-lego ran our testing suite and [noticed something breaking](https://github.com/FBruzzesi/scikit-lego/actions/runs/8975596456/job/24650556520). Here's the e...
28,966
[ 0.013902181759476662, 0.05720460042357445, 0.004220428876578808, -0.012677812948822975, 0.007223752327263355, 0.0015129304956644773, 0.07057303190231323, 0.026346584782004356, 0.0027288724668323994, 0.0011211953824386, 0.04373392090201378, 0.012030712328851223, -0.001041959272697568, 0.008...
https://github.com/scikit-learn/scikit-learn/issues/28966
[ "Documentation", "Developer API" ]
Is it intention to drop `check_estimator_sparse_data` in 1.5? ### Describe the bug While running the 1.5.0 release candidate, my collaborator @FBruzzesi on scikit-lego ran our testing suite and [noticed something breaking](https://github.com/FBruzzesi/scikit-lego/actions/runs/8975596456/job/24650556520). Here's the e...
28,966
[ 0.013902181759476662, 0.05720460042357445, 0.004220428876578808, -0.012677812948822975, 0.007223752327263355, 0.0015129304956644773, 0.07057303190231323, 0.026346584782004356, 0.0027288724668323994, 0.0011211953824386, 0.04373392090201378, 0.012030712328851223, -0.001041959272697568, 0.008...
https://github.com/scikit-learn/scikit-learn/issues/28960
[ "New Feature" ]
Base function to check if the model is a clusterer (analogous to `base.is_classifier()` and `base.is_regressor()`)? ### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/28904 <div type='discussions-op-text'> <sup>Originally posted by **aoot** April 26, 2024</sup> According to [the note on f...
28,960
[ -0.02800382487475872, -0.0014613610692322254, 0.02543913759291172, 0.01675877347588539, 0.019644059240818024, 0.008897200226783752, 0.062208909541368484, 0.03699275851249695, 0.06500978022813797, -0.0031746409367769957, 0.08312278240919113, 0.04070024937391281, -0.015527194365859032, 0.013...
https://github.com/scikit-learn/scikit-learn/issues/28960
[ "New Feature" ]
Base function to check if the model is a clusterer (analogous to `base.is_classifier()` and `base.is_regressor()`)? ### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/28904 <div type='discussions-op-text'> <sup>Originally posted by **aoot** April 26, 2024</sup> According to [the note on f...
28,960
[ -0.025502383708953857, 0.008901095949113369, 0.020251654088497162, 0.023681819438934326, 0.02692021057009697, 0.007412453182041645, 0.06660919636487961, 0.03564107418060303, 0.08394210785627365, -0.00784099381417036, 0.08531206101179123, 0.04064013436436653, -0.01444484293460846, 0.0128881...
https://github.com/scikit-learn/scikit-learn/issues/28960
[ "New Feature" ]
Base function to check if the model is a clusterer (analogous to `base.is_classifier()` and `base.is_regressor()`)? ### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/28904 <div type='discussions-op-text'> <sup>Originally posted by **aoot** April 26, 2024</sup> According to [the note on f...
28,960
[ -0.024279799312353134, -0.0026380065828561783, 0.029007326811552048, 0.03221869096159935, 0.03412521630525589, 0.002819554414600134, 0.05147305876016617, 0.030588848516345024, 0.08281151950359344, -0.008129783906042576, 0.07453527301549911, 0.04336317256093025, -0.010112077929079533, 0.018...
https://github.com/scikit-learn/scikit-learn/issues/28960
[ "New Feature" ]
Base function to check if the model is a clusterer (analogous to `base.is_classifier()` and `base.is_regressor()`)? ### Discussed in https://github.com/scikit-learn/scikit-learn/discussions/28904 <div type='discussions-op-text'> <sup>Originally posted by **aoot** April 26, 2024</sup> According to [the note on f...
28,960
[ -0.024909058585762978, -0.0038773061241954565, 0.030445978045463562, 0.030717525631189346, 0.036437761038541794, 0.007295833434909582, 0.053210578858852386, 0.03317328914999962, 0.09357025474309921, -0.005821790546178818, 0.07644832134246826, 0.045806556940078735, -0.018720950931310654, 0....
https://github.com/scikit-learn/scikit-learn/issues/28959
[ "Numerical Stability" ]
Local testing of global_random_seed is not enough When adding ``global_random_seed`` to a test, it's not enough to check it locally, i.e. on a single machine. Numerical precision issues can come from various factors like OS, CPU, BLAS, ... When adding ``global_random_seed``, it's important to test **all** random se...
28,959
[ -0.030640991404652596, 0.018861111253499985, -0.020819708704948425, 0.0008432423346675932, 0.0225635077804327, 0.004955739714205265, 0.06861560046672821, 0.008051990531384945, 0.03802475333213806, 0.03937596455216408, 0.05791868641972542, -0.021988006308674812, -0.015741098672151566, 0.029...
https://github.com/scikit-learn/scikit-learn/issues/28959
[ "Numerical Stability" ]
Local testing of global_random_seed is not enough When adding ``global_random_seed`` to a test, it's not enough to check it locally, i.e. on a single machine. Numerical precision issues can come from various factors like OS, CPU, BLAS, ... When adding ``global_random_seed``, it's important to test **all** random se...
28,959
[ -0.028521202504634857, 0.01068254467099905, -0.012629833072423935, -0.009770467877388, 0.030230648815631866, -0.0027272733859717846, 0.0346069261431694, 0.02713317796587944, 0.022628942504525185, 0.015811895951628685, 0.06658817827701569, -0.011984946206212044, -0.012884283438324928, 0.033...
https://github.com/scikit-learn/scikit-learn/issues/28959
[ "Numerical Stability" ]
Local testing of global_random_seed is not enough When adding ``global_random_seed`` to a test, it's not enough to check it locally, i.e. on a single machine. Numerical precision issues can come from various factors like OS, CPU, BLAS, ... When adding ``global_random_seed``, it's important to test **all** random se...
28,959
[ -0.03419569134712219, 0.0007433209102600813, -0.007698507513850927, -0.0007268705521710217, 0.02883254922926426, -0.01352972723543644, 0.028877273201942444, 0.023348834365606308, 0.031140390783548355, 0.02013787068426609, 0.07065332680940628, -0.010916572995483875, -0.017756586894392967, 0...
https://github.com/scikit-learn/scikit-learn/issues/28959
[ "Numerical Stability" ]
Local testing of global_random_seed is not enough When adding ``global_random_seed`` to a test, it's not enough to check it locally, i.e. on a single machine. Numerical precision issues can come from various factors like OS, CPU, BLAS, ... When adding ``global_random_seed``, it's important to test **all** random se...
28,959
[ -0.0213957317173481, 0.007399781607091427, -0.014898724853992462, -0.0008749138214625418, 0.017907535657286644, 0.004122027195990086, 0.05888619273900986, 0.026089992374181747, 0.04038548097014427, 0.02793530561029911, 0.0765501856803894, -0.012027678079903126, -0.010804344899952412, 0.040...