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https://github.com/scikit-learn/scikit-learn/issues/29107
[ "Bug", "Regression", "Array API" ]
Incorrect invalid device error introduced in #25956 ### Describe the bug #25956 introduced a new `sklearn.utils._array_api._check_device_cpu` function to test whether a tensor is on CPU. However, the implementation of the test, which is `device not in {"cpu", None}`, is incorrect -- the device will actually not be ...
29,107
[ 0.012658174149692059, -0.03723932057619095, -0.015977950766682625, -0.03496240824460983, 0.05507814884185791, 0.034053441137075424, 0.0894760936498642, 0.043827034533023834, 0.03414347022771835, -0.022205688059329987, 0.018164807930588722, 0.03514901176095009, 0.018658174201846123, -0.0222...
https://github.com/scikit-learn/scikit-learn/issues/29107
[ "Bug", "Regression", "Array API" ]
Incorrect invalid device error introduced in #25956 ### Describe the bug #25956 introduced a new `sklearn.utils._array_api._check_device_cpu` function to test whether a tensor is on CPU. However, the implementation of the test, which is `device not in {"cpu", None}`, is incorrect -- the device will actually not be ...
29,107
[ 0.012658174149692059, -0.03723932057619095, -0.015977950766682625, -0.03496240824460983, 0.05507814884185791, 0.034053441137075424, 0.0894760936498642, 0.043827034533023834, 0.03414347022771835, -0.022205688059329987, 0.018164807930588722, 0.03514901176095009, 0.018658174201846123, -0.0222...
https://github.com/scikit-learn/scikit-learn/issues/29107
[ "Bug", "Regression", "Array API" ]
Incorrect invalid device error introduced in #25956 ### Describe the bug #25956 introduced a new `sklearn.utils._array_api._check_device_cpu` function to test whether a tensor is on CPU. However, the implementation of the test, which is `device not in {"cpu", None}`, is incorrect -- the device will actually not be ...
29,107
[ 0.012658174149692059, -0.03723932057619095, -0.015977950766682625, -0.03496240824460983, 0.05507814884185791, 0.034053441137075424, 0.0894760936498642, 0.043827034533023834, 0.03414347022771835, -0.022205688059329987, 0.018164807930588722, 0.03514901176095009, 0.018658174201846123, -0.0222...
https://github.com/scikit-learn/scikit-learn/issues/29107
[ "Bug", "Regression", "Array API" ]
Incorrect invalid device error introduced in #25956 ### Describe the bug #25956 introduced a new `sklearn.utils._array_api._check_device_cpu` function to test whether a tensor is on CPU. However, the implementation of the test, which is `device not in {"cpu", None}`, is incorrect -- the device will actually not be ...
29,107
[ 0.012658174149692059, -0.03723932057619095, -0.015977950766682625, -0.03496240824460983, 0.05507814884185791, 0.034053441137075424, 0.0894760936498642, 0.043827034533023834, 0.03414347022771835, -0.022205688059329987, 0.018164807930588722, 0.03514901176095009, 0.018658174201846123, -0.0222...
https://github.com/scikit-learn/scikit-learn/issues/29107
[ "Bug", "Regression", "Array API" ]
Incorrect invalid device error introduced in #25956 ### Describe the bug #25956 introduced a new `sklearn.utils._array_api._check_device_cpu` function to test whether a tensor is on CPU. However, the implementation of the test, which is `device not in {"cpu", None}`, is incorrect -- the device will actually not be ...
29,107
[ 0.012658174149692059, -0.03723932057619095, -0.015977950766682625, -0.03496240824460983, 0.05507814884185791, 0.034053441137075424, 0.0894760936498642, 0.043827034533023834, 0.03414347022771835, -0.022205688059329987, 0.018164807930588722, 0.03514901176095009, 0.018658174201846123, -0.0222...
https://github.com/scikit-learn/scikit-learn/issues/29107
[ "Bug", "Regression", "Array API" ]
Incorrect invalid device error introduced in #25956 ### Describe the bug #25956 introduced a new `sklearn.utils._array_api._check_device_cpu` function to test whether a tensor is on CPU. However, the implementation of the test, which is `device not in {"cpu", None}`, is incorrect -- the device will actually not be ...
29,107
[ 0.012658174149692059, -0.03723932057619095, -0.015977950766682625, -0.03496240824460983, 0.05507814884185791, 0.034053441137075424, 0.0894760936498642, 0.043827034533023834, 0.03414347022771835, -0.022205688059329987, 0.018164807930588722, 0.03514901176095009, 0.018658174201846123, -0.0222...
https://github.com/scikit-learn/scikit-learn/issues/29107
[ "Bug", "Regression", "Array API" ]
Incorrect invalid device error introduced in #25956 ### Describe the bug #25956 introduced a new `sklearn.utils._array_api._check_device_cpu` function to test whether a tensor is on CPU. However, the implementation of the test, which is `device not in {"cpu", None}`, is incorrect -- the device will actually not be ...
29,107
[ 0.012658174149692059, -0.03723932057619095, -0.015977950766682625, -0.03496240824460983, 0.05507814884185791, 0.034053441137075424, 0.0894760936498642, 0.043827034533023834, 0.03414347022771835, -0.022205688059329987, 0.018164807930588722, 0.03514901176095009, 0.018658174201846123, -0.0222...
https://github.com/scikit-learn/scikit-learn/issues/29107
[ "Bug", "Regression", "Array API" ]
Incorrect invalid device error introduced in #25956 ### Describe the bug #25956 introduced a new `sklearn.utils._array_api._check_device_cpu` function to test whether a tensor is on CPU. However, the implementation of the test, which is `device not in {"cpu", None}`, is incorrect -- the device will actually not be ...
29,107
[ 0.012658174149692059, -0.03723932057619095, -0.015977950766682625, -0.03496240824460983, 0.05507814884185791, 0.034053441137075424, 0.0894760936498642, 0.043827034533023834, 0.03414347022771835, -0.022205688059329987, 0.018164807930588722, 0.03514901176095009, 0.018658174201846123, -0.0222...
https://github.com/scikit-learn/scikit-learn/issues/29107
[ "Bug", "Regression", "Array API" ]
Incorrect invalid device error introduced in #25956 ### Describe the bug #25956 introduced a new `sklearn.utils._array_api._check_device_cpu` function to test whether a tensor is on CPU. However, the implementation of the test, which is `device not in {"cpu", None}`, is incorrect -- the device will actually not be ...
29,107
[ 0.012658174149692059, -0.03723932057619095, -0.015977950766682625, -0.03496240824460983, 0.05507814884185791, 0.034053441137075424, 0.0894760936498642, 0.043827034533023834, 0.03414347022771835, -0.022205688059329987, 0.018164807930588722, 0.03514901176095009, 0.018658174201846123, -0.0222...
https://github.com/scikit-learn/scikit-learn/issues/29107
[ "Bug", "Regression", "Array API" ]
Incorrect invalid device error introduced in #25956 ### Describe the bug #25956 introduced a new `sklearn.utils._array_api._check_device_cpu` function to test whether a tensor is on CPU. However, the implementation of the test, which is `device not in {"cpu", None}`, is incorrect -- the device will actually not be ...
29,107
[ 0.012658174149692059, -0.03723932057619095, -0.015977950766682625, -0.03496240824460983, 0.05507814884185791, 0.034053441137075424, 0.0894760936498642, 0.043827034533023834, 0.03414347022771835, -0.022205688059329987, 0.018164807930588722, 0.03514901176095009, 0.018658174201846123, -0.0222...
https://github.com/scikit-learn/scikit-learn/issues/29107
[ "Bug", "Regression", "Array API" ]
Incorrect invalid device error introduced in #25956 ### Describe the bug #25956 introduced a new `sklearn.utils._array_api._check_device_cpu` function to test whether a tensor is on CPU. However, the implementation of the test, which is `device not in {"cpu", None}`, is incorrect -- the device will actually not be ...
29,107
[ 0.012658174149692059, -0.03723932057619095, -0.015977950766682625, -0.03496240824460983, 0.05507814884185791, 0.034053441137075424, 0.0894760936498642, 0.043827034533023834, 0.03414347022771835, -0.022205688059329987, 0.018164807930588722, 0.03514901176095009, 0.018658174201846123, -0.0222...
https://github.com/scikit-learn/scikit-learn/issues/29106
[ "Bug", "Needs Triage" ]
problem with convert_sklearn and onnx opset ### Describe the bug hi, i run into the following problem that convert_sklearn seems to require opset 13 but i need opset 14 to support another operator ```operator 'aten::scaled_dot_product_attention'```: the problem is with _update_domain_version - how can i change ...
29,106
[ -0.0292536411434412, 0.04858334735035896, -0.01648721657693386, -0.03265727311372757, 0.032896336168050766, 0.017697056755423546, 0.06688152998685837, 0.012269874103367329, -0.01582358218729496, -0.015971211716532707, 0.0013236884260550141, 0.05899666249752045, -0.023413972929120064, 0.084...
https://github.com/scikit-learn/scikit-learn/issues/29102
[ "New Feature", "Needs Decision" ]
Allow users to override `_fit_and_score` of the BaseSearchCV ### Describe the workflow you want to enable Currently, the `BaseSearchCV` has some level of customization enabled with the `_run_search` method. I would like to enable more customization. In particular the `fit` method calls `_fit_and_score` function for...
29,102
[ -0.018274223431944847, 0.06282061338424683, 0.007351102773100138, 0.009824257344007492, 0.004829721990972757, -0.03942776471376419, 0.013467260636389256, 0.008134467527270317, 0.01016302965581417, -0.011417260393500328, 0.008094814606010914, 0.0766303539276123, -0.036965932697057724, 0.075...
https://github.com/scikit-learn/scikit-learn/issues/29101
[ "Documentation", "Moderate", "help wanted" ]
When a Pipeline step is changed via set_params, the set_output state is cleared ### Describe the bug When a Pipeline step is set via `set_params`, the subsequent output of `fit_transform` is a numpy ndarray even if previously the pipeline's output was set to be of type pandas.DataFrame via a call to `set_output(tra...
29,101
[ -0.021236548200249672, -0.0021742633543908596, 0.01808502897620201, -0.054275576025247574, 0.06962267309427261, -0.03296390175819397, 0.041931282728910446, 0.0037876474671065807, -0.026644280180335045, 0.015077569521963596, 0.03699434921145439, 0.03743660822510719, 0.0371873714029789, 0.05...
https://github.com/scikit-learn/scikit-learn/issues/29101
[ "Documentation", "Moderate", "help wanted" ]
When a Pipeline step is changed via set_params, the set_output state is cleared ### Describe the bug When a Pipeline step is set via `set_params`, the subsequent output of `fit_transform` is a numpy ndarray even if previously the pipeline's output was set to be of type pandas.DataFrame via a call to `set_output(tra...
29,101
[ -0.021236548200249672, -0.0021742633543908596, 0.01808502897620201, -0.054275576025247574, 0.06962267309427261, -0.03296390175819397, 0.041931282728910446, 0.0037876474671065807, -0.026644280180335045, 0.015077569521963596, 0.03699434921145439, 0.03743660822510719, 0.0371873714029789, 0.05...
https://github.com/scikit-learn/scikit-learn/issues/29101
[ "Documentation", "Moderate", "help wanted" ]
When a Pipeline step is changed via set_params, the set_output state is cleared ### Describe the bug When a Pipeline step is set via `set_params`, the subsequent output of `fit_transform` is a numpy ndarray even if previously the pipeline's output was set to be of type pandas.DataFrame via a call to `set_output(tra...
29,101
[ -0.021236548200249672, -0.0021742633543908596, 0.01808502897620201, -0.054275576025247574, 0.06962267309427261, -0.03296390175819397, 0.041931282728910446, 0.0037876474671065807, -0.026644280180335045, 0.015077569521963596, 0.03699434921145439, 0.03743660822510719, 0.0371873714029789, 0.05...
https://github.com/scikit-learn/scikit-learn/issues/29101
[ "Documentation", "Moderate", "help wanted" ]
When a Pipeline step is changed via set_params, the set_output state is cleared ### Describe the bug When a Pipeline step is set via `set_params`, the subsequent output of `fit_transform` is a numpy ndarray even if previously the pipeline's output was set to be of type pandas.DataFrame via a call to `set_output(tra...
29,101
[ -0.021236548200249672, -0.0021742633543908596, 0.01808502897620201, -0.054275576025247574, 0.06962267309427261, -0.03296390175819397, 0.041931282728910446, 0.0037876474671065807, -0.026644280180335045, 0.015077569521963596, 0.03699434921145439, 0.03743660822510719, 0.0371873714029789, 0.05...
https://github.com/scikit-learn/scikit-learn/issues/29099
[ "Documentation", "RFC" ]
RFC module location in API table for the API reference page I was looking at the API documentation on the new website. I was first not convinced to not have a different table for each module but at the end, if the search bar and the left navigation bart, I think this is just a matter to get use to it. However, I th...
29,099
[ 0.06984492391347885, 0.031917426735162735, -0.028716562315821648, 0.005597458686679602, -0.0004204419965390116, 0.01118727307766676, 0.07326412945985794, 0.0327313169836998, 0.03224756568670273, -0.02506612427532673, 0.004932379350066185, 0.02336236834526062, 0.018243148922920227, 0.024772...
https://github.com/scikit-learn/scikit-learn/issues/29099
[ "Documentation", "RFC" ]
RFC module location in API table for the API reference page I was looking at the API documentation on the new website. I was first not convinced to not have a different table for each module but at the end, if the search bar and the left navigation bart, I think this is just a matter to get use to it. However, I th...
29,099
[ 0.06708376109600067, 0.02614753320813179, -0.030954672023653984, 0.0036426291335374117, 0.0008160177385434508, 0.009842278435826302, 0.06306374818086624, 0.024817513301968575, 0.0297177042812109, -0.018702013418078423, 0.003437082516029477, 0.032197222113609314, 0.02371557243168354, 0.0119...
https://github.com/scikit-learn/scikit-learn/issues/29099
[ "Documentation", "RFC" ]
RFC module location in API table for the API reference page I was looking at the API documentation on the new website. I was first not convinced to not have a different table for each module but at the end, if the search bar and the left navigation bart, I think this is just a matter to get use to it. However, I th...
29,099
[ 0.07013539224863052, 0.021092530339956284, -0.022794010117650032, 0.0010645600268617272, -0.003738925326615572, 0.005388057325035334, 0.06678515672683716, 0.04064854606986046, 0.03531242161989212, -0.023598212748765945, 0.0027278882917016745, 0.017078856006264687, 0.022872379049658775, 0.0...
https://github.com/scikit-learn/scikit-learn/issues/29099
[ "Documentation", "RFC" ]
RFC module location in API table for the API reference page I was looking at the API documentation on the new website. I was first not convinced to not have a different table for each module but at the end, if the search bar and the left navigation bart, I think this is just a matter to get use to it. However, I th...
29,099
[ 0.08801249414682388, 0.024466080591082573, -0.02437012642621994, -0.007812591269612312, -0.005774085875600576, 0.014583471231162548, 0.07097751647233963, 0.025710677728056908, 0.02752041444182396, -0.04398062825202942, -0.007237141951918602, 0.03315868601202965, 0.031061885878443718, 0.025...
https://github.com/scikit-learn/scikit-learn/issues/29099
[ "Documentation", "RFC" ]
RFC module location in API table for the API reference page I was looking at the API documentation on the new website. I was first not convinced to not have a different table for each module but at the end, if the search bar and the left navigation bart, I think this is just a matter to get use to it. However, I th...
29,099
[ 0.08094329386949539, 0.009955344721674919, -0.0293131023645401, -0.002732431050390005, -0.009109670296311378, 0.009831920266151428, 0.0579848550260067, 0.02827828750014305, 0.025570906698703766, -0.043773289769887924, -0.007938367314636707, 0.04304688051342964, 0.027123043313622475, 0.0200...
https://github.com/scikit-learn/scikit-learn/issues/29098
[ "API", "help wanted" ]
Deprecate copy_X in TheilSenRegressor The `copy_X` parameter of ``TheilSenRegressor`` is not used anywhere and hence has no effect, so we should deprecate it. COMMENT: I can quickly address this @jeremiedbb
29,098
[ -0.009698890149593353, 0.012232055887579918, -0.0010013999417424202, -0.008436777628958225, -0.06612661480903625, 0.00843065045773983, 0.03913998231291771, 0.03842252865433693, -0.08925557136535645, -0.01906670816242695, 0.054740358144044876, 0.040560074150562286, -0.030878545716404915, -0...
https://github.com/scikit-learn/scikit-learn/issues/29092
[ "API" ]
Deprecate copy in Birch `Birch` doesn't perform inplace operations (at least not on the input array), so the `copy` parameter is useless and should be deprecated. It's even detrimental because by default it makes a copy. The only place where an inplace operation happens is in the `update` method of `_CFSubcluster`:...
29,092
[ 0.01010054349899292, -0.0601448118686676, -0.012937028892338276, 0.03278068080544472, -0.013469045050442219, -0.025215206667780876, -0.00754706421867013, -0.02582569606602192, -0.03647121042013168, 0.009055241011083126, -0.007707972079515457, 0.039892494678497314, -0.019088169559836388, 0....
https://github.com/scikit-learn/scikit-learn/issues/29089
[ "RFC" ]
RFC Future of HalvingGridSearchCV `HalvingGridSearchCV` has been in experimental mode since its conception in 2020-09, almost 4 years ago. Things to note: - we haven't seen many issues regarding these estimators, but that is probably because we are not advertising them enough, and they're in experimental mode. - ...
29,089
[ 0.005159886088222265, 0.029386164620518684, 0.025475794449448586, -0.036204345524311066, -0.03616632893681526, -0.012717556208372116, 0.022093337029218674, 0.03195421025156975, -0.005260654259473085, -0.020713340491056442, 0.10473518818616867, 0.007329587358981371, -0.04788181185722351, 0....
https://github.com/scikit-learn/scikit-learn/issues/29089
[ "RFC" ]
RFC Future of HalvingGridSearchCV `HalvingGridSearchCV` has been in experimental mode since its conception in 2020-09, almost 4 years ago. Things to note: - we haven't seen many issues regarding these estimators, but that is probably because we are not advertising them enough, and they're in experimental mode. - ...
29,089
[ 0.0013168519362807274, 0.028825799003243446, 0.024515992030501366, -0.03474390134215355, -0.03479219228029251, -0.013606084510684013, 0.01965412311255932, 0.03236221522092819, -0.0031073796562850475, -0.02009715884923935, 0.10231398791074753, 0.008790048770606518, -0.05057307332754135, 0.0...
https://github.com/scikit-learn/scikit-learn/issues/29089
[ "RFC" ]
RFC Future of HalvingGridSearchCV `HalvingGridSearchCV` has been in experimental mode since its conception in 2020-09, almost 4 years ago. Things to note: - we haven't seen many issues regarding these estimators, but that is probably because we are not advertising them enough, and they're in experimental mode. - ...
29,089
[ 0.004549974109977484, 0.027901431545615196, 0.02747862972319126, -0.03680521622300148, -0.03726697713136673, -0.011618285439908504, 0.019805889576673508, 0.03254367783665657, -0.003996884450316429, -0.020117683336138725, 0.1023150235414505, 0.010170720517635345, -0.04780878126621246, 0.043...
https://github.com/scikit-learn/scikit-learn/issues/29089
[ "RFC" ]
RFC Future of HalvingGridSearchCV `HalvingGridSearchCV` has been in experimental mode since its conception in 2020-09, almost 4 years ago. Things to note: - we haven't seen many issues regarding these estimators, but that is probably because we are not advertising them enough, and they're in experimental mode. - ...
29,089
[ 0.004947297740727663, 0.01953577995300293, 0.030881429091095924, -0.04941406846046448, -0.02469261735677719, -0.021638479083776474, 0.01605312153697014, 0.02650606445968151, -0.024899281561374664, -0.017759401351213455, 0.07509149610996246, 0.004594647325575352, -0.045347657054662704, 0.02...
https://github.com/scikit-learn/scikit-learn/issues/29088
[ "API", "Needs Decision" ]
DEP loss_function_ attribute in PassiveAggressiveClassifier #27979 deprecate the attribute `loss_function_` that accesses a Cython extension class in `SGDClassifier` and `SGDOneClassSVM`. Unfortunately, `PassiveAggressiveClassifier` also inherits the `loss_function_` attribute from `BaseSGDClassifier` and this was ove...
29,088
[ 0.010728885419666767, 0.06163926050066948, 0.014601169154047966, 0.01806599460542202, 0.05006418749690056, 0.016070429235696793, 0.001224846695549786, -0.009365922771394253, -0.05822852998971939, -0.03563141077756882, 0.0395267978310585, 0.015854952856898308, 0.007871648296713829, -0.01722...
https://github.com/scikit-learn/scikit-learn/issues/29088
[ "API", "Needs Decision" ]
DEP loss_function_ attribute in PassiveAggressiveClassifier #27979 deprecate the attribute `loss_function_` that accesses a Cython extension class in `SGDClassifier` and `SGDOneClassSVM`. Unfortunately, `PassiveAggressiveClassifier` also inherits the `loss_function_` attribute from `BaseSGDClassifier` and this was ove...
29,088
[ 0.01586388610303402, 0.07029849290847778, 0.010045593604445457, 0.018998483195900917, 0.04494868218898773, 0.0174737349152565, -0.002839157823473215, -0.002748255617916584, -0.05947304517030716, -0.037466853857040405, 0.04452882707118988, 0.023084590211510658, 0.009075723588466644, -0.0100...
https://github.com/scikit-learn/scikit-learn/issues/29085
[ "New Feature" ]
`sklearn.neighbors.NearestNeighbors` allow processing nan values ### Describe the workflow you want to enable In some cases (for example [memory-based collaborative filtering](https://en.wikipedia.org/wiki/Collaborative_filtering)) empty values is important part of the algorithm. But `sklearn.neighbors.NearestNeigh...
29,085
[ -0.0023728022351861, 0.04461870342493057, 0.04892129823565483, -0.01165141724050045, 0.0015261697117239237, -0.01530576404184103, 0.06733100861310959, 0.005464143585413694, 0.035720277577638626, 0.011077547445893288, -0.038536280393600464, -0.004852702375501394, -0.011097478680312634, 0.00...
https://github.com/scikit-learn/scikit-learn/issues/29085
[ "New Feature" ]
`sklearn.neighbors.NearestNeighbors` allow processing nan values ### Describe the workflow you want to enable In some cases (for example [memory-based collaborative filtering](https://en.wikipedia.org/wiki/Collaborative_filtering)) empty values is important part of the algorithm. But `sklearn.neighbors.NearestNeigh...
29,085
[ -0.0023728022351861, 0.04461870342493057, 0.04892129823565483, -0.01165141724050045, 0.0015261697117239237, -0.01530576404184103, 0.06733100861310959, 0.005464143585413694, 0.035720277577638626, 0.011077547445893288, -0.038536280393600464, -0.004852702375501394, -0.011097478680312634, 0.00...
https://github.com/scikit-learn/scikit-learn/issues/29085
[ "New Feature" ]
`sklearn.neighbors.NearestNeighbors` allow processing nan values ### Describe the workflow you want to enable In some cases (for example [memory-based collaborative filtering](https://en.wikipedia.org/wiki/Collaborative_filtering)) empty values is important part of the algorithm. But `sklearn.neighbors.NearestNeigh...
29,085
[ -0.0023728022351861, 0.04461870342493057, 0.04892129823565483, -0.01165141724050045, 0.0015261697117239237, -0.01530576404184103, 0.06733100861310959, 0.005464143585413694, 0.035720277577638626, 0.011077547445893288, -0.038536280393600464, -0.004852702375501394, -0.011097478680312634, 0.00...
https://github.com/scikit-learn/scikit-learn/issues/29085
[ "New Feature" ]
`sklearn.neighbors.NearestNeighbors` allow processing nan values ### Describe the workflow you want to enable In some cases (for example [memory-based collaborative filtering](https://en.wikipedia.org/wiki/Collaborative_filtering)) empty values is important part of the algorithm. But `sklearn.neighbors.NearestNeigh...
29,085
[ -0.0023728022351861, 0.04461870342493057, 0.04892129823565483, -0.01165141724050045, 0.0015261697117239237, -0.01530576404184103, 0.06733100861310959, 0.005464143585413694, 0.035720277577638626, 0.011077547445893288, -0.038536280393600464, -0.004852702375501394, -0.011097478680312634, 0.00...
https://github.com/scikit-learn/scikit-learn/issues/29085
[ "New Feature" ]
`sklearn.neighbors.NearestNeighbors` allow processing nan values ### Describe the workflow you want to enable In some cases (for example [memory-based collaborative filtering](https://en.wikipedia.org/wiki/Collaborative_filtering)) empty values is important part of the algorithm. But `sklearn.neighbors.NearestNeigh...
29,085
[ -0.0023728022351861, 0.04461870342493057, 0.04892129823565483, -0.01165141724050045, 0.0015261697117239237, -0.01530576404184103, 0.06733100861310959, 0.005464143585413694, 0.035720277577638626, 0.011077547445893288, -0.038536280393600464, -0.004852702375501394, -0.011097478680312634, 0.00...
https://github.com/scikit-learn/scikit-learn/issues/29085
[ "New Feature" ]
`sklearn.neighbors.NearestNeighbors` allow processing nan values ### Describe the workflow you want to enable In some cases (for example [memory-based collaborative filtering](https://en.wikipedia.org/wiki/Collaborative_filtering)) empty values is important part of the algorithm. But `sklearn.neighbors.NearestNeigh...
29,085
[ -0.0023728022351861, 0.04461870342493057, 0.04892129823565483, -0.01165141724050045, 0.0015261697117239237, -0.01530576404184103, 0.06733100861310959, 0.005464143585413694, 0.035720277577638626, 0.011077547445893288, -0.038536280393600464, -0.004852702375501394, -0.011097478680312634, 0.00...
https://github.com/scikit-learn/scikit-learn/issues/29085
[ "New Feature" ]
`sklearn.neighbors.NearestNeighbors` allow processing nan values ### Describe the workflow you want to enable In some cases (for example [memory-based collaborative filtering](https://en.wikipedia.org/wiki/Collaborative_filtering)) empty values is important part of the algorithm. But `sklearn.neighbors.NearestNeigh...
29,085
[ -0.0023728022351861, 0.04461870342493057, 0.04892129823565483, -0.01165141724050045, 0.0015261697117239237, -0.01530576404184103, 0.06733100861310959, 0.005464143585413694, 0.035720277577638626, 0.011077547445893288, -0.038536280393600464, -0.004852702375501394, -0.011097478680312634, 0.00...
https://github.com/scikit-learn/scikit-learn/issues/29085
[ "New Feature" ]
`sklearn.neighbors.NearestNeighbors` allow processing nan values ### Describe the workflow you want to enable In some cases (for example [memory-based collaborative filtering](https://en.wikipedia.org/wiki/Collaborative_filtering)) empty values is important part of the algorithm. But `sklearn.neighbors.NearestNeigh...
29,085
[ -0.0023728022351861, 0.04461870342493057, 0.04892129823565483, -0.01165141724050045, 0.0015261697117239237, -0.01530576404184103, 0.06733100861310959, 0.005464143585413694, 0.035720277577638626, 0.011077547445893288, -0.038536280393600464, -0.004852702375501394, -0.011097478680312634, 0.00...
https://github.com/scikit-learn/scikit-learn/issues/29079
[ "Bug" ]
Samples with nan distance are included in the computation of mean in `KNNImputer` for uniform weights ### Describe the bug The toy dataset and the distance computed by `nan_euclidean_distances` are as follows. ```python import numpy as np from sklearn.metrics.pairwise import nan_euclidean_distances X_train = [[1,...
29,079
[ 0.008846523240208626, -0.01648811623454094, 0.0312671884894371, 0.017176223918795586, 0.031196409836411476, -0.007317622657865286, 0.060059379786252975, 0.025182761251926422, -0.0010851648403331637, 0.020032973960042, 0.042721349745988846, 0.023337725549936295, 0.01938478834927082, -0.0453...
https://github.com/scikit-learn/scikit-learn/issues/29079
[ "Bug" ]
Samples with nan distance are included in the computation of mean in `KNNImputer` for uniform weights ### Describe the bug The toy dataset and the distance computed by `nan_euclidean_distances` are as follows. ```python import numpy as np from sklearn.metrics.pairwise import nan_euclidean_distances X_train = [[1,...
29,079
[ 0.008846523240208626, -0.01648811623454094, 0.0312671884894371, 0.017176223918795586, 0.031196409836411476, -0.007317622657865286, 0.060059379786252975, 0.025182761251926422, -0.0010851648403331637, 0.020032973960042, 0.042721349745988846, 0.023337725549936295, 0.01938478834927082, -0.0453...
https://github.com/scikit-learn/scikit-learn/issues/29075
[ "Documentation" ]
Fix version warning banner on the stable documentation page ### Describe the issue linked to the documentation Currently https://scikit-learn.org/stable/index.html shows the version warning banner ("This are the docs for an unstable version"). <img width="1258" alt="Screenshot 2024-05-22 at 09 08 02" src="https://gi...
29,075
[ 0.037183646112680435, -0.020136622712016106, -0.039164669811725616, -0.044746652245521545, 0.030611660331487656, 0.037963658571243286, -0.0009540022583678365, 0.020056698471307755, 0.00808221660554409, -0.02212509512901306, 0.07731392234563828, -0.0056582046672701836, 0.03563060238957405, ...
https://github.com/scikit-learn/scikit-learn/issues/29075
[ "Documentation" ]
Fix version warning banner on the stable documentation page ### Describe the issue linked to the documentation Currently https://scikit-learn.org/stable/index.html shows the version warning banner ("This are the docs for an unstable version"). <img width="1258" alt="Screenshot 2024-05-22 at 09 08 02" src="https://gi...
29,075
[ 0.041493579745292664, -0.02626010589301586, -0.038764119148254395, -0.04572804644703865, 0.035648033022880554, 0.03899943456053734, 0.00290074129588902, 0.02328445389866829, 0.010632852092385292, -0.0199382696300745, 0.0727582797408104, -0.007013223133981228, 0.029906034469604492, -0.00043...
https://github.com/scikit-learn/scikit-learn/issues/29075
[ "Documentation" ]
Fix version warning banner on the stable documentation page ### Describe the issue linked to the documentation Currently https://scikit-learn.org/stable/index.html shows the version warning banner ("This are the docs for an unstable version"). <img width="1258" alt="Screenshot 2024-05-22 at 09 08 02" src="https://gi...
29,075
[ 0.03976905345916748, -0.015812182798981667, -0.037372440099716187, -0.04723213240504265, 0.032925818115472794, 0.03918481990695, -0.005832357797771692, 0.010684673674404621, 0.0061872657388448715, -0.0191899836063385, 0.08484318852424622, -0.0058865975588560104, 0.03350958973169327, 0.0006...
https://github.com/scikit-learn/scikit-learn/issues/29075
[ "Documentation" ]
Fix version warning banner on the stable documentation page ### Describe the issue linked to the documentation Currently https://scikit-learn.org/stable/index.html shows the version warning banner ("This are the docs for an unstable version"). <img width="1258" alt="Screenshot 2024-05-22 at 09 08 02" src="https://gi...
29,075
[ 0.04243927076458931, -0.026438556611537933, -0.039775244891643524, -0.04589592665433884, 0.03689957410097122, 0.039407651871442795, 0.005939987022429705, 0.022000538185238838, 0.011725131422281265, -0.02118261530995369, 0.07389170676469803, -0.007108703255653381, 0.030696716159582138, -0.0...
https://github.com/scikit-learn/scikit-learn/issues/29075
[ "Documentation" ]
Fix version warning banner on the stable documentation page ### Describe the issue linked to the documentation Currently https://scikit-learn.org/stable/index.html shows the version warning banner ("This are the docs for an unstable version"). <img width="1258" alt="Screenshot 2024-05-22 at 09 08 02" src="https://gi...
29,075
[ 0.03939160704612732, -0.0261143259704113, -0.041012365370988846, -0.04592199996113777, 0.03415365517139435, 0.040303196758031845, 0.0004912200383841991, 0.01926504261791706, 0.012878837995231152, -0.02003788761794567, 0.07633933424949646, -0.0072365570813417435, 0.0309451874345541, 0.00077...
https://github.com/scikit-learn/scikit-learn/issues/29075
[ "Documentation" ]
Fix version warning banner on the stable documentation page ### Describe the issue linked to the documentation Currently https://scikit-learn.org/stable/index.html shows the version warning banner ("This are the docs for an unstable version"). <img width="1258" alt="Screenshot 2024-05-22 at 09 08 02" src="https://gi...
29,075
[ 0.038024626672267914, -0.01280602440237999, -0.035081490874290466, -0.04556526616215706, 0.027482159435749054, 0.03513263911008835, -0.010602188296616077, 0.0062210396863520145, -0.003798027988523245, -0.02130109816789627, 0.09410625696182251, -0.004140524193644524, 0.03378049656748772, 0....
https://github.com/scikit-learn/scikit-learn/issues/29074
[ "Bug", "Regression" ]
`GridSearchCV` with custom estimator and nested Parameter Grids raises `ValueError` in scikit-learn 1.5.0 ### Describe the bug When using `GridSearchCV` with a custom estimator that includes nested parameter grids, a `ValueError` is raised in scikit-learn 1.5.0 indicating "entry not a 2- or 3- tuple". This issue does...
29,074
[ 0.028892919421195984, 0.018637655302882195, 0.04862694442272186, -0.010954330675303936, 0.10130295902490616, -0.012626217678189278, 0.04558028653264046, 0.025874368846416473, 0.07824979722499847, -0.005611423868685961, 0.010430735535919666, 0.04329649358987808, -0.01391648594290018, -0.014...
https://github.com/scikit-learn/scikit-learn/issues/29074
[ "Bug", "Regression" ]
`GridSearchCV` with custom estimator and nested Parameter Grids raises `ValueError` in scikit-learn 1.5.0 ### Describe the bug When using `GridSearchCV` with a custom estimator that includes nested parameter grids, a `ValueError` is raised in scikit-learn 1.5.0 indicating "entry not a 2- or 3- tuple". This issue does...
29,074
[ 0.028892919421195984, 0.018637655302882195, 0.04862694442272186, -0.010954330675303936, 0.10130295902490616, -0.012626217678189278, 0.04558028653264046, 0.025874368846416473, 0.07824979722499847, -0.005611423868685961, 0.010430735535919666, 0.04329649358987808, -0.01391648594290018, -0.014...
https://github.com/scikit-learn/scikit-learn/issues/29074
[ "Bug", "Regression" ]
`GridSearchCV` with custom estimator and nested Parameter Grids raises `ValueError` in scikit-learn 1.5.0 ### Describe the bug When using `GridSearchCV` with a custom estimator that includes nested parameter grids, a `ValueError` is raised in scikit-learn 1.5.0 indicating "entry not a 2- or 3- tuple". This issue does...
29,074
[ 0.028892919421195984, 0.018637655302882195, 0.04862694442272186, -0.010954330675303936, 0.10130295902490616, -0.012626217678189278, 0.04558028653264046, 0.025874368846416473, 0.07824979722499847, -0.005611423868685961, 0.010430735535919666, 0.04329649358987808, -0.01391648594290018, -0.014...
https://github.com/scikit-learn/scikit-learn/issues/29074
[ "Bug", "Regression" ]
`GridSearchCV` with custom estimator and nested Parameter Grids raises `ValueError` in scikit-learn 1.5.0 ### Describe the bug When using `GridSearchCV` with a custom estimator that includes nested parameter grids, a `ValueError` is raised in scikit-learn 1.5.0 indicating "entry not a 2- or 3- tuple". This issue does...
29,074
[ 0.028892919421195984, 0.018637655302882195, 0.04862694442272186, -0.010954330675303936, 0.10130295902490616, -0.012626217678189278, 0.04558028653264046, 0.025874368846416473, 0.07824979722499847, -0.005611423868685961, 0.010430735535919666, 0.04329649358987808, -0.01391648594290018, -0.014...
https://github.com/scikit-learn/scikit-learn/issues/29074
[ "Bug", "Regression" ]
`GridSearchCV` with custom estimator and nested Parameter Grids raises `ValueError` in scikit-learn 1.5.0 ### Describe the bug When using `GridSearchCV` with a custom estimator that includes nested parameter grids, a `ValueError` is raised in scikit-learn 1.5.0 indicating "entry not a 2- or 3- tuple". This issue does...
29,074
[ 0.028892919421195984, 0.018637655302882195, 0.04862694442272186, -0.010954330675303936, 0.10130295902490616, -0.012626217678189278, 0.04558028653264046, 0.025874368846416473, 0.07824979722499847, -0.005611423868685961, 0.010430735535919666, 0.04329649358987808, -0.01391648594290018, -0.014...
https://github.com/scikit-learn/scikit-learn/issues/29073
[ "Documentation" ]
Sphinx search summary disappeared from 1.5 website Looks like the sphinx search summary has gone from 1.5 website. Not crucial, but showing the context of the match is handy to decide which link is more likely to have the information we want when we use the doc search bar. Maybe due to pydata-sphinx-theme switch, m...
29,073
[ 0.07342402637004852, 0.006139441393315792, -0.014210941269993782, 0.01019632164388895, 0.03801828995347023, -0.016967494040727615, 0.0023103950079530478, 0.05330784618854523, -0.04815205559134483, -0.032184503972530365, -0.035639263689517975, 0.011728493496775627, -0.001408661250025034, -0...
https://github.com/scikit-learn/scikit-learn/issues/29073
[ "Documentation" ]
Sphinx search summary disappeared from 1.5 website Looks like the sphinx search summary has gone from 1.5 website. Not crucial, but showing the context of the match is handy to decide which link is more likely to have the information we want when we use the doc search bar. Maybe due to pydata-sphinx-theme switch, m...
29,073
[ 0.08284636586904526, 0.0023360620252788067, -0.014861095696687698, 0.005188638810068369, 0.048024918884038925, -0.016085930168628693, 0.0026597296819090843, 0.05505945160984993, -0.052249595522880554, -0.02603333443403244, -0.02769366279244423, 0.022176217287778854, 0.009498976171016693, -...
https://github.com/scikit-learn/scikit-learn/issues/29073
[ "Documentation" ]
Sphinx search summary disappeared from 1.5 website Looks like the sphinx search summary has gone from 1.5 website. Not crucial, but showing the context of the match is handy to decide which link is more likely to have the information we want when we use the doc search bar. Maybe due to pydata-sphinx-theme switch, m...
29,073
[ 0.07972753047943115, 0.0010503372177481651, -0.014967682771384716, 0.0018610804108902812, 0.036605510860681534, -0.012744924984872341, -0.00133893929887563, 0.04174348711967468, -0.05393596738576889, -0.020035382360219955, -0.024172600358724594, -0.0049247113056480885, 0.005837562959641218, ...
https://github.com/scikit-learn/scikit-learn/issues/29073
[ "Documentation" ]
Sphinx search summary disappeared from 1.5 website Looks like the sphinx search summary has gone from 1.5 website. Not crucial, but showing the context of the match is handy to decide which link is more likely to have the information we want when we use the doc search bar. Maybe due to pydata-sphinx-theme switch, m...
29,073
[ 0.08264105021953583, 0.010162228718400002, -0.017978545278310776, 0.012570297345519066, 0.043579597026109695, -0.01776399277150631, -0.00205900683067739, 0.04690718650817871, -0.05225702002644539, -0.029492201283574104, -0.028214307501912117, 0.013165744952857494, -0.003380044363439083, -0...
https://github.com/scikit-learn/scikit-learn/issues/29073
[ "Documentation" ]
Sphinx search summary disappeared from 1.5 website Looks like the sphinx search summary has gone from 1.5 website. Not crucial, but showing the context of the match is handy to decide which link is more likely to have the information we want when we use the doc search bar. Maybe due to pydata-sphinx-theme switch, m...
29,073
[ 0.07741270214319229, 0.011075664311647415, -0.015307391062378883, 0.020067432895302773, 0.03949064388871193, -0.014318707399070263, 0.0026187803596258163, 0.06350387632846832, -0.05456721410155296, -0.03730210289359093, -0.03165115416049957, 0.023625049740076065, 0.010419345460832119, -0.0...
https://github.com/scikit-learn/scikit-learn/issues/29073
[ "Documentation" ]
Sphinx search summary disappeared from 1.5 website Looks like the sphinx search summary has gone from 1.5 website. Not crucial, but showing the context of the match is handy to decide which link is more likely to have the information we want when we use the doc search bar. Maybe due to pydata-sphinx-theme switch, m...
29,073
[ 0.08164488524198532, -0.006305088754743338, -0.015455578453838825, 0.009079382754862309, 0.03937069699168205, -0.01480616070330143, 0.0027405295986682177, 0.05796864256262779, -0.048371460288763046, -0.022177191451191902, -0.017919693142175674, 0.026246672496199608, 0.015242931433022022, -...
https://github.com/scikit-learn/scikit-learn/issues/29073
[ "Documentation" ]
Sphinx search summary disappeared from 1.5 website Looks like the sphinx search summary has gone from 1.5 website. Not crucial, but showing the context of the match is handy to decide which link is more likely to have the information we want when we use the doc search bar. Maybe due to pydata-sphinx-theme switch, m...
29,073
[ 0.08077286183834076, 0.004050579387694597, -0.011754226870834827, 0.005286484956741333, 0.0452779121696949, -0.013672436587512493, 0.004374807700514793, 0.0625230148434639, -0.04497496411204338, -0.028362276032567024, -0.025235190987586975, 0.021455148234963417, 0.010772302746772766, -0.02...
https://github.com/scikit-learn/scikit-learn/issues/29073
[ "Documentation" ]
Sphinx search summary disappeared from 1.5 website Looks like the sphinx search summary has gone from 1.5 website. Not crucial, but showing the context of the match is handy to decide which link is more likely to have the information we want when we use the doc search bar. Maybe due to pydata-sphinx-theme switch, m...
29,073
[ 0.07814127951860428, 0.0059064761735498905, -0.01339513249695301, 0.009855067357420921, 0.0404471792280674, -0.013221082277595997, -0.002944092731922865, 0.05052633956074715, -0.05509904399514198, -0.026587704196572304, -0.027164509519934654, 0.01767001487314701, 0.007949183695018291, -0.0...
https://github.com/scikit-learn/scikit-learn/issues/29073
[ "Documentation" ]
Sphinx search summary disappeared from 1.5 website Looks like the sphinx search summary has gone from 1.5 website. Not crucial, but showing the context of the match is handy to decide which link is more likely to have the information we want when we use the doc search bar. Maybe due to pydata-sphinx-theme switch, m...
29,073
[ 0.08775916695594788, 0.010452528484165668, -0.013691202737390995, 0.00780967902392149, 0.048292189836502075, -0.008584498427808285, 0.008415350690484047, 0.053055159747600555, -0.0504639558494091, -0.030001845210790634, -0.028360961005091667, 0.016775505617260933, 0.017906932160258293, -0....
https://github.com/scikit-learn/scikit-learn/issues/29073
[ "Documentation" ]
Sphinx search summary disappeared from 1.5 website Looks like the sphinx search summary has gone from 1.5 website. Not crucial, but showing the context of the match is handy to decide which link is more likely to have the information we want when we use the doc search bar. Maybe due to pydata-sphinx-theme switch, m...
29,073
[ 0.07739327847957611, 0.0035289868246763945, -0.013390486128628254, 0.007635548245161772, 0.0401749312877655, -0.0115040959790349, 0.0012367131421342492, 0.049631331115961075, -0.05306391417980194, -0.026311039924621582, -0.02988625131547451, 0.01703779213130474, 0.008513388223946095, -0.01...
https://github.com/scikit-learn/scikit-learn/issues/29073
[ "Documentation" ]
Sphinx search summary disappeared from 1.5 website Looks like the sphinx search summary has gone from 1.5 website. Not crucial, but showing the context of the match is handy to decide which link is more likely to have the information we want when we use the doc search bar. Maybe due to pydata-sphinx-theme switch, m...
29,073
[ 0.06940274685621262, 0.0045120301656425, -0.016399387270212173, 0.006729025859385729, 0.03475267067551613, -0.015660889446735382, 0.00048089944175444543, 0.05918287858366966, -0.051270004361867905, -0.023159857839345932, -0.031239846721291542, 0.02168169990181923, 0.0021300865337252617, -0...
https://github.com/scikit-learn/scikit-learn/issues/29070
[ "Documentation", "Needs Triage" ]
Broken link at the 1.5.0 release page ### Describe the issue linked to the documentation At the [release page](https://github.com/scikit-learn/scikit-learn/releases/tag/1.5.0) > We're happy to announce the 1.5.0 release. > > You can read the release highlights under https://scikit-learn.org/stable/auto_examples...
29,070
[ 0.03438311070203781, -0.012439494952559471, -0.014629720710217953, -0.007697097957134247, 0.016680823639035225, 0.009615576826035976, 0.02360885962843895, 0.02944674715399742, 0.003566365223377943, -0.051516879349946976, 0.05243181437253952, 0.028099073097109795, 0.03050229512155056, 0.084...
https://github.com/scikit-learn/scikit-learn/issues/29065
[ "New Feature", "Needs Triage" ]
GridSearchCV.score: support multiple scoring metrics ### Describe the workflow you want to enable `GridSearchCV` supports multiple scoring metrics using the `scoring` parameter. However, this only applies to `fit`, not to `score`. I would like to use these same scoring metrics to evaluate on the test set as well. ##...
29,065
[ -0.03584442287683487, 0.014337732456624508, 0.02306007221341133, 0.017431501299142838, 0.06745367497205734, -0.01230345293879509, 0.011163020506501198, 0.023191703483462334, 0.07234194874763489, -0.006883549969643354, -0.03462636098265648, 0.02393500879406929, -0.018339302390813828, 0.0813...
https://github.com/scikit-learn/scikit-learn/issues/29065
[ "New Feature", "Needs Triage" ]
GridSearchCV.score: support multiple scoring metrics ### Describe the workflow you want to enable `GridSearchCV` supports multiple scoring metrics using the `scoring` parameter. However, this only applies to `fit`, not to `score`. I would like to use these same scoring metrics to evaluate on the test set as well. ##...
29,065
[ -0.03584442287683487, 0.014337732456624508, 0.02306007221341133, 0.017431501299142838, 0.06745367497205734, -0.01230345293879509, 0.011163020506501198, 0.023191703483462334, 0.07234194874763489, -0.006883549969643354, -0.03462636098265648, 0.02393500879406929, -0.018339302390813828, 0.0813...
https://github.com/scikit-learn/scikit-learn/issues/29065
[ "New Feature", "Needs Triage" ]
GridSearchCV.score: support multiple scoring metrics ### Describe the workflow you want to enable `GridSearchCV` supports multiple scoring metrics using the `scoring` parameter. However, this only applies to `fit`, not to `score`. I would like to use these same scoring metrics to evaluate on the test set as well. ##...
29,065
[ -0.03584442287683487, 0.014337732456624508, 0.02306007221341133, 0.017431501299142838, 0.06745367497205734, -0.01230345293879509, 0.011163020506501198, 0.023191703483462334, 0.07234194874763489, -0.006883549969643354, -0.03462636098265648, 0.02393500879406929, -0.018339302390813828, 0.0813...
https://github.com/scikit-learn/scikit-learn/issues/29065
[ "New Feature", "Needs Triage" ]
GridSearchCV.score: support multiple scoring metrics ### Describe the workflow you want to enable `GridSearchCV` supports multiple scoring metrics using the `scoring` parameter. However, this only applies to `fit`, not to `score`. I would like to use these same scoring metrics to evaluate on the test set as well. ##...
29,065
[ -0.03584442287683487, 0.014337732456624508, 0.02306007221341133, 0.017431501299142838, 0.06745367497205734, -0.01230345293879509, 0.011163020506501198, 0.023191703483462334, 0.07234194874763489, -0.006883549969643354, -0.03462636098265648, 0.02393500879406929, -0.018339302390813828, 0.0813...
https://github.com/scikit-learn/scikit-learn/issues/29062
[ "New Feature" ]
Don't refit in FixedThresholdClassifier when original model is already trained. ### Describe the workflow you want to enable I wrote some code for a demo that looks like this: ```python from sklearn.datasets import make_classification from sklearn.linear_model import LogisticRegression from sklearn.metrics im...
29,062
[ -0.039541296660900116, 0.02491401880979538, 0.022918283939361572, -0.021450407803058624, 0.05698781460523605, 0.004310504999011755, -0.011171155609190464, 0.01630515605211258, -0.02530849538743496, -0.018446167930960655, -0.02034972421824932, -0.0028129920829087496, 0.00853319838643074, 0....
https://github.com/scikit-learn/scikit-learn/issues/29062
[ "New Feature" ]
Don't refit in FixedThresholdClassifier when original model is already trained. ### Describe the workflow you want to enable I wrote some code for a demo that looks like this: ```python from sklearn.datasets import make_classification from sklearn.linear_model import LogisticRegression from sklearn.metrics im...
29,062
[ -0.039541296660900116, 0.02491401880979538, 0.022918283939361572, -0.021450407803058624, 0.05698781460523605, 0.004310504999011755, -0.011171155609190464, 0.01630515605211258, -0.02530849538743496, -0.018446167930960655, -0.02034972421824932, -0.0028129920829087496, 0.00853319838643074, 0....
https://github.com/scikit-learn/scikit-learn/issues/29061
[ "New Feature", "Needs Triage" ]
TunedThresholdClassifierCV: add other metrics ### Describe the workflow you want to enable I figured that I might use the new tuned thresholder to turn code like this into something that's a bit more like gridsearch with all the parallism benefits. ```python from sklearn.datasets import make_classification fro...
29,061
[ -0.047108523547649384, 0.0029359629843384027, 0.025335347279906273, -0.0015900972066447139, 0.08076611161231995, -0.022704539820551872, -0.02265251614153385, 0.02334561012685299, 0.018280059099197388, -0.021198567003011703, -0.02213774062693119, 0.03342413157224655, -0.01179111935198307, 0...
https://github.com/scikit-learn/scikit-learn/issues/29061
[ "New Feature", "Needs Triage" ]
TunedThresholdClassifierCV: add other metrics ### Describe the workflow you want to enable I figured that I might use the new tuned thresholder to turn code like this into something that's a bit more like gridsearch with all the parallism benefits. ```python from sklearn.datasets import make_classification fro...
29,061
[ -0.047108523547649384, 0.0029359629843384027, 0.025335347279906273, -0.0015900972066447139, 0.08076611161231995, -0.022704539820551872, -0.02265251614153385, 0.02334561012685299, 0.018280059099197388, -0.021198567003011703, -0.02213774062693119, 0.03342413157224655, -0.01179111935198307, 0...
https://github.com/scikit-learn/scikit-learn/issues/29061
[ "New Feature", "Needs Triage" ]
TunedThresholdClassifierCV: add other metrics ### Describe the workflow you want to enable I figured that I might use the new tuned thresholder to turn code like this into something that's a bit more like gridsearch with all the parallism benefits. ```python from sklearn.datasets import make_classification fro...
29,061
[ -0.047108523547649384, 0.0029359629843384027, 0.025335347279906273, -0.0015900972066447139, 0.08076611161231995, -0.022704539820551872, -0.02265251614153385, 0.02334561012685299, 0.018280059099197388, -0.021198567003011703, -0.02213774062693119, 0.03342413157224655, -0.01179111935198307, 0...
https://github.com/scikit-learn/scikit-learn/issues/29061
[ "New Feature", "Needs Triage" ]
TunedThresholdClassifierCV: add other metrics ### Describe the workflow you want to enable I figured that I might use the new tuned thresholder to turn code like this into something that's a bit more like gridsearch with all the parallism benefits. ```python from sklearn.datasets import make_classification fro...
29,061
[ -0.047108523547649384, 0.0029359629843384027, 0.025335347279906273, -0.0015900972066447139, 0.08076611161231995, -0.022704539820551872, -0.02265251614153385, 0.02334561012685299, 0.018280059099197388, -0.021198567003011703, -0.02213774062693119, 0.03342413157224655, -0.01179111935198307, 0...
https://github.com/scikit-learn/scikit-learn/issues/29061
[ "New Feature", "Needs Triage" ]
TunedThresholdClassifierCV: add other metrics ### Describe the workflow you want to enable I figured that I might use the new tuned thresholder to turn code like this into something that's a bit more like gridsearch with all the parallism benefits. ```python from sklearn.datasets import make_classification fro...
29,061
[ -0.047108523547649384, 0.0029359629843384027, 0.025335347279906273, -0.0015900972066447139, 0.08076611161231995, -0.022704539820551872, -0.02265251614153385, 0.02334561012685299, 0.018280059099197388, -0.021198567003011703, -0.02213774062693119, 0.03342413157224655, -0.01179111935198307, 0...
https://github.com/scikit-learn/scikit-learn/issues/29061
[ "New Feature", "Needs Triage" ]
TunedThresholdClassifierCV: add other metrics ### Describe the workflow you want to enable I figured that I might use the new tuned thresholder to turn code like this into something that's a bit more like gridsearch with all the parallism benefits. ```python from sklearn.datasets import make_classification fro...
29,061
[ -0.047108523547649384, 0.0029359629843384027, 0.025335347279906273, -0.0015900972066447139, 0.08076611161231995, -0.022704539820551872, -0.02265251614153385, 0.02334561012685299, 0.018280059099197388, -0.021198567003011703, -0.02213774062693119, 0.03342413157224655, -0.01179111935198307, 0...
https://github.com/scikit-learn/scikit-learn/issues/29061
[ "New Feature", "Needs Triage" ]
TunedThresholdClassifierCV: add other metrics ### Describe the workflow you want to enable I figured that I might use the new tuned thresholder to turn code like this into something that's a bit more like gridsearch with all the parallism benefits. ```python from sklearn.datasets import make_classification fro...
29,061
[ -0.047108523547649384, 0.0029359629843384027, 0.025335347279906273, -0.0015900972066447139, 0.08076611161231995, -0.022704539820551872, -0.02265251614153385, 0.02334561012685299, 0.018280059099197388, -0.021198567003011703, -0.02213774062693119, 0.03342413157224655, -0.01179111935198307, 0...
https://github.com/scikit-learn/scikit-learn/issues/29061
[ "New Feature", "Needs Triage" ]
TunedThresholdClassifierCV: add other metrics ### Describe the workflow you want to enable I figured that I might use the new tuned thresholder to turn code like this into something that's a bit more like gridsearch with all the parallism benefits. ```python from sklearn.datasets import make_classification fro...
29,061
[ -0.047108523547649384, 0.0029359629843384027, 0.025335347279906273, -0.0015900972066447139, 0.08076611161231995, -0.022704539820551872, -0.02265251614153385, 0.02334561012685299, 0.018280059099197388, -0.021198567003011703, -0.02213774062693119, 0.03342413157224655, -0.01179111935198307, 0...
https://github.com/scikit-learn/scikit-learn/issues/29061
[ "New Feature", "Needs Triage" ]
TunedThresholdClassifierCV: add other metrics ### Describe the workflow you want to enable I figured that I might use the new tuned thresholder to turn code like this into something that's a bit more like gridsearch with all the parallism benefits. ```python from sklearn.datasets import make_classification fro...
29,061
[ -0.047108523547649384, 0.0029359629843384027, 0.025335347279906273, -0.0015900972066447139, 0.08076611161231995, -0.022704539820551872, -0.02265251614153385, 0.02334561012685299, 0.018280059099197388, -0.021198567003011703, -0.02213774062693119, 0.03342413157224655, -0.01179111935198307, 0...
https://github.com/scikit-learn/scikit-learn/issues/29061
[ "New Feature", "Needs Triage" ]
TunedThresholdClassifierCV: add other metrics ### Describe the workflow you want to enable I figured that I might use the new tuned thresholder to turn code like this into something that's a bit more like gridsearch with all the parallism benefits. ```python from sklearn.datasets import make_classification fro...
29,061
[ -0.047108523547649384, 0.0029359629843384027, 0.025335347279906273, -0.0015900972066447139, 0.08076611161231995, -0.022704539820551872, -0.02265251614153385, 0.02334561012685299, 0.018280059099197388, -0.021198567003011703, -0.02213774062693119, 0.03342413157224655, -0.01179111935198307, 0...
https://github.com/scikit-learn/scikit-learn/issues/29055
[ "Documentation", "good first issue", "help wanted", "Meta-issue" ]
`UserWarning`s in the documentation ### Describe the issue linked to the documentation Some `UserWarning` are present in the `dev` documentation and need to be fixed. Here is a list: - [x] [gaussian_process/plot_gpr_prior_posterior.html](https://scikit-learn.org/dev/auto_examples/gaussian_process/plot_gpr_prio...
29,055
[ 0.02375134825706482, 0.0011286648223176599, -0.021790828555822372, 0.004167004022747278, 0.02994394488632679, 0.053154949098825455, 0.06512580066919327, -0.004015106242150068, 0.004384965170174837, -0.01882033981382847, 0.011148576624691486, 0.04163040593266487, 0.019693676382303238, 0.027...
https://github.com/scikit-learn/scikit-learn/issues/29055
[ "Documentation", "good first issue", "help wanted", "Meta-issue" ]
`UserWarning`s in the documentation ### Describe the issue linked to the documentation Some `UserWarning` are present in the `dev` documentation and need to be fixed. Here is a list: - [x] [gaussian_process/plot_gpr_prior_posterior.html](https://scikit-learn.org/dev/auto_examples/gaussian_process/plot_gpr_prio...
29,055
[ 0.02375134825706482, 0.0011286648223176599, -0.021790828555822372, 0.004167004022747278, 0.02994394488632679, 0.053154949098825455, 0.06512580066919327, -0.004015106242150068, 0.004384965170174837, -0.01882033981382847, 0.011148576624691486, 0.04163040593266487, 0.019693676382303238, 0.027...
https://github.com/scikit-learn/scikit-learn/issues/29055
[ "Documentation", "good first issue", "help wanted", "Meta-issue" ]
`UserWarning`s in the documentation ### Describe the issue linked to the documentation Some `UserWarning` are present in the `dev` documentation and need to be fixed. Here is a list: - [x] [gaussian_process/plot_gpr_prior_posterior.html](https://scikit-learn.org/dev/auto_examples/gaussian_process/plot_gpr_prio...
29,055
[ 0.02375134825706482, 0.0011286648223176599, -0.021790828555822372, 0.004167004022747278, 0.02994394488632679, 0.053154949098825455, 0.06512580066919327, -0.004015106242150068, 0.004384965170174837, -0.01882033981382847, 0.011148576624691486, 0.04163040593266487, 0.019693676382303238, 0.027...
https://github.com/scikit-learn/scikit-learn/issues/29055
[ "Documentation", "good first issue", "help wanted", "Meta-issue" ]
`UserWarning`s in the documentation ### Describe the issue linked to the documentation Some `UserWarning` are present in the `dev` documentation and need to be fixed. Here is a list: - [x] [gaussian_process/plot_gpr_prior_posterior.html](https://scikit-learn.org/dev/auto_examples/gaussian_process/plot_gpr_prio...
29,055
[ 0.02375134825706482, 0.0011286648223176599, -0.021790828555822372, 0.004167004022747278, 0.02994394488632679, 0.053154949098825455, 0.06512580066919327, -0.004015106242150068, 0.004384965170174837, -0.01882033981382847, 0.011148576624691486, 0.04163040593266487, 0.019693676382303238, 0.027...
https://github.com/scikit-learn/scikit-learn/issues/29055
[ "Documentation", "good first issue", "help wanted", "Meta-issue" ]
`UserWarning`s in the documentation ### Describe the issue linked to the documentation Some `UserWarning` are present in the `dev` documentation and need to be fixed. Here is a list: - [x] [gaussian_process/plot_gpr_prior_posterior.html](https://scikit-learn.org/dev/auto_examples/gaussian_process/plot_gpr_prio...
29,055
[ 0.02375134825706482, 0.0011286648223176599, -0.021790828555822372, 0.004167004022747278, 0.02994394488632679, 0.053154949098825455, 0.06512580066919327, -0.004015106242150068, 0.004384965170174837, -0.01882033981382847, 0.011148576624691486, 0.04163040593266487, 0.019693676382303238, 0.027...
https://github.com/scikit-learn/scikit-learn/issues/29055
[ "Documentation", "good first issue", "help wanted", "Meta-issue" ]
`UserWarning`s in the documentation ### Describe the issue linked to the documentation Some `UserWarning` are present in the `dev` documentation and need to be fixed. Here is a list: - [x] [gaussian_process/plot_gpr_prior_posterior.html](https://scikit-learn.org/dev/auto_examples/gaussian_process/plot_gpr_prio...
29,055
[ 0.02375134825706482, 0.0011286648223176599, -0.021790828555822372, 0.004167004022747278, 0.02994394488632679, 0.053154949098825455, 0.06512580066919327, -0.004015106242150068, 0.004384965170174837, -0.01882033981382847, 0.011148576624691486, 0.04163040593266487, 0.019693676382303238, 0.027...
https://github.com/scikit-learn/scikit-learn/issues/29055
[ "Documentation", "good first issue", "help wanted", "Meta-issue" ]
`UserWarning`s in the documentation ### Describe the issue linked to the documentation Some `UserWarning` are present in the `dev` documentation and need to be fixed. Here is a list: - [x] [gaussian_process/plot_gpr_prior_posterior.html](https://scikit-learn.org/dev/auto_examples/gaussian_process/plot_gpr_prio...
29,055
[ 0.02375134825706482, 0.0011286648223176599, -0.021790828555822372, 0.004167004022747278, 0.02994394488632679, 0.053154949098825455, 0.06512580066919327, -0.004015106242150068, 0.004384965170174837, -0.01882033981382847, 0.011148576624691486, 0.04163040593266487, 0.019693676382303238, 0.027...
https://github.com/scikit-learn/scikit-learn/issues/29055
[ "Documentation", "good first issue", "help wanted", "Meta-issue" ]
`UserWarning`s in the documentation ### Describe the issue linked to the documentation Some `UserWarning` are present in the `dev` documentation and need to be fixed. Here is a list: - [x] [gaussian_process/plot_gpr_prior_posterior.html](https://scikit-learn.org/dev/auto_examples/gaussian_process/plot_gpr_prio...
29,055
[ 0.02375134825706482, 0.0011286648223176599, -0.021790828555822372, 0.004167004022747278, 0.02994394488632679, 0.053154949098825455, 0.06512580066919327, -0.004015106242150068, 0.004384965170174837, -0.01882033981382847, 0.011148576624691486, 0.04163040593266487, 0.019693676382303238, 0.027...
https://github.com/scikit-learn/scikit-learn/issues/29055
[ "Documentation", "good first issue", "help wanted", "Meta-issue" ]
`UserWarning`s in the documentation ### Describe the issue linked to the documentation Some `UserWarning` are present in the `dev` documentation and need to be fixed. Here is a list: - [x] [gaussian_process/plot_gpr_prior_posterior.html](https://scikit-learn.org/dev/auto_examples/gaussian_process/plot_gpr_prio...
29,055
[ 0.02375134825706482, 0.0011286648223176599, -0.021790828555822372, 0.004167004022747278, 0.02994394488632679, 0.053154949098825455, 0.06512580066919327, -0.004015106242150068, 0.004384965170174837, -0.01882033981382847, 0.011148576624691486, 0.04163040593266487, 0.019693676382303238, 0.027...
https://github.com/scikit-learn/scikit-learn/issues/29055
[ "Documentation", "good first issue", "help wanted", "Meta-issue" ]
`UserWarning`s in the documentation ### Describe the issue linked to the documentation Some `UserWarning` are present in the `dev` documentation and need to be fixed. Here is a list: - [x] [gaussian_process/plot_gpr_prior_posterior.html](https://scikit-learn.org/dev/auto_examples/gaussian_process/plot_gpr_prio...
29,055
[ 0.02375134825706482, 0.0011286648223176599, -0.021790828555822372, 0.004167004022747278, 0.02994394488632679, 0.053154949098825455, 0.06512580066919327, -0.004015106242150068, 0.004384965170174837, -0.01882033981382847, 0.011148576624691486, 0.04163040593266487, 0.019693676382303238, 0.027...
https://github.com/scikit-learn/scikit-learn/issues/29055
[ "Documentation", "good first issue", "help wanted", "Meta-issue" ]
`UserWarning`s in the documentation ### Describe the issue linked to the documentation Some `UserWarning` are present in the `dev` documentation and need to be fixed. Here is a list: - [x] [gaussian_process/plot_gpr_prior_posterior.html](https://scikit-learn.org/dev/auto_examples/gaussian_process/plot_gpr_prio...
29,055
[ 0.02375134825706482, 0.0011286648223176599, -0.021790828555822372, 0.004167004022747278, 0.02994394488632679, 0.053154949098825455, 0.06512580066919327, -0.004015106242150068, 0.004384965170174837, -0.01882033981382847, 0.011148576624691486, 0.04163040593266487, 0.019693676382303238, 0.027...
https://github.com/scikit-learn/scikit-learn/issues/29055
[ "Documentation", "good first issue", "help wanted", "Meta-issue" ]
`UserWarning`s in the documentation ### Describe the issue linked to the documentation Some `UserWarning` are present in the `dev` documentation and need to be fixed. Here is a list: - [x] [gaussian_process/plot_gpr_prior_posterior.html](https://scikit-learn.org/dev/auto_examples/gaussian_process/plot_gpr_prio...
29,055
[ 0.02375134825706482, 0.0011286648223176599, -0.021790828555822372, 0.004167004022747278, 0.02994394488632679, 0.053154949098825455, 0.06512580066919327, -0.004015106242150068, 0.004384965170174837, -0.01882033981382847, 0.011148576624691486, 0.04163040593266487, 0.019693676382303238, 0.027...
https://github.com/scikit-learn/scikit-learn/issues/29055
[ "Documentation", "good first issue", "help wanted", "Meta-issue" ]
`UserWarning`s in the documentation ### Describe the issue linked to the documentation Some `UserWarning` are present in the `dev` documentation and need to be fixed. Here is a list: - [x] [gaussian_process/plot_gpr_prior_posterior.html](https://scikit-learn.org/dev/auto_examples/gaussian_process/plot_gpr_prio...
29,055
[ 0.02375134825706482, 0.0011286648223176599, -0.021790828555822372, 0.004167004022747278, 0.02994394488632679, 0.053154949098825455, 0.06512580066919327, -0.004015106242150068, 0.004384965170174837, -0.01882033981382847, 0.011148576624691486, 0.04163040593266487, 0.019693676382303238, 0.027...
https://github.com/scikit-learn/scikit-learn/issues/29051
[ "Bug", "Needs Triage" ]
It's really amazing!! Why are the calculation results of the AUC (recall, precision) function and the average precision score function significantly different? ### Describe the bug Method 1: Precision, recall, _=Precision-Recall_curve() A=auc (recall, precision) Method 2: B=average precision score () Method 1 an...
29,051
[ 0.016390329226851463, -0.05841469019651413, 0.010467184707522392, 0.04846816137433052, 0.006038830149918795, -0.02724793367087841, 0.014258435927331448, -0.07564324885606766, -0.025085702538490295, 0.016250811517238617, 0.041134901344776154, -0.02898688241839409, 0.07603219896554947, 0.023...
https://github.com/scikit-learn/scikit-learn/issues/29051
[ "Bug", "Needs Triage" ]
It's really amazing!! Why are the calculation results of the AUC (recall, precision) function and the average precision score function significantly different? ### Describe the bug Method 1: Precision, recall, _=Precision-Recall_curve() A=auc (recall, precision) Method 2: B=average precision score () Method 1 an...
29,051
[ 0.010054301470518112, -0.05597763881087303, 0.014067777432501316, 0.047753892838954926, 0.006429859437048435, -0.033492058515548706, 0.004566268529742956, -0.059912312775850296, -0.020455535501241684, 0.01738623157143593, 0.02879389561712742, -0.01573004201054573, 0.08032343536615372, 0.01...
https://github.com/scikit-learn/scikit-learn/issues/29048
[ "Enhancement" ]
Make `zero_division` parameter consistent in the different metric This is an issue to report the step to actually take over the work of @marctorsoc in https://github.com/scikit-learn/scikit-learn/pull/23183 and split the PR into smaller one to facilitate the review process. The intend is to make the `zero_division` p...
29,048
[ -0.01399283017963171, 0.014668786898255348, 0.0533316433429718, -0.032538075000047684, 0.05320441722869873, -0.02024364471435547, 0.046024829149246216, 0.028971439227461815, -0.03679615631699562, -0.02881160005927086, 0.02186780609190464, 0.005561315920203924, 0.03284919261932373, 0.046216...
https://github.com/scikit-learn/scikit-learn/issues/29048
[ "Enhancement" ]
Make `zero_division` parameter consistent in the different metric This is an issue to report the step to actually take over the work of @marctorsoc in https://github.com/scikit-learn/scikit-learn/pull/23183 and split the PR into smaller one to facilitate the review process. The intend is to make the `zero_division` p...
29,048
[ -0.01399283017963171, 0.014668786898255348, 0.0533316433429718, -0.032538075000047684, 0.05320441722869873, -0.02024364471435547, 0.046024829149246216, 0.028971439227461815, -0.03679615631699562, -0.02881160005927086, 0.02186780609190464, 0.005561315920203924, 0.03284919261932373, 0.046216...
https://github.com/scikit-learn/scikit-learn/issues/29048
[ "Enhancement" ]
Make `zero_division` parameter consistent in the different metric This is an issue to report the step to actually take over the work of @marctorsoc in https://github.com/scikit-learn/scikit-learn/pull/23183 and split the PR into smaller one to facilitate the review process. The intend is to make the `zero_division` p...
29,048
[ -0.01399283017963171, 0.014668786898255348, 0.0533316433429718, -0.032538075000047684, 0.05320441722869873, -0.02024364471435547, 0.046024829149246216, 0.028971439227461815, -0.03679615631699562, -0.02881160005927086, 0.02186780609190464, 0.005561315920203924, 0.03284919261932373, 0.046216...
https://github.com/scikit-learn/scikit-learn/issues/29048
[ "Enhancement" ]
Make `zero_division` parameter consistent in the different metric This is an issue to report the step to actually take over the work of @marctorsoc in https://github.com/scikit-learn/scikit-learn/pull/23183 and split the PR into smaller one to facilitate the review process. The intend is to make the `zero_division` p...
29,048
[ -0.01399283017963171, 0.014668786898255348, 0.0533316433429718, -0.032538075000047684, 0.05320441722869873, -0.02024364471435547, 0.046024829149246216, 0.028971439227461815, -0.03679615631699562, -0.02881160005927086, 0.02186780609190464, 0.005561315920203924, 0.03284919261932373, 0.046216...
https://github.com/scikit-learn/scikit-learn/issues/29048
[ "Enhancement" ]
Make `zero_division` parameter consistent in the different metric This is an issue to report the step to actually take over the work of @marctorsoc in https://github.com/scikit-learn/scikit-learn/pull/23183 and split the PR into smaller one to facilitate the review process. The intend is to make the `zero_division` p...
29,048
[ -0.01399283017963171, 0.014668786898255348, 0.0533316433429718, -0.032538075000047684, 0.05320441722869873, -0.02024364471435547, 0.046024829149246216, 0.028971439227461815, -0.03679615631699562, -0.02881160005927086, 0.02186780609190464, 0.005561315920203924, 0.03284919261932373, 0.046216...
https://github.com/scikit-learn/scikit-learn/issues/29048
[ "Enhancement" ]
Make `zero_division` parameter consistent in the different metric This is an issue to report the step to actually take over the work of @marctorsoc in https://github.com/scikit-learn/scikit-learn/pull/23183 and split the PR into smaller one to facilitate the review process. The intend is to make the `zero_division` p...
29,048
[ -0.01399283017963171, 0.014668786898255348, 0.0533316433429718, -0.032538075000047684, 0.05320441722869873, -0.02024364471435547, 0.046024829149246216, 0.028971439227461815, -0.03679615631699562, -0.02881160005927086, 0.02186780609190464, 0.005561315920203924, 0.03284919261932373, 0.046216...