10559664 9186 Prabhant Singh 3573 Supervised Classification 18664 torch.nn.modules.container.Sequential.ee39b87dd683a3ec(1) 8276204 children [{"oml-python:serialized_object": "component_reference", "value": {"key": "0", "step_name": "0"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "1", "step_name": "1"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "2", "step_name": "2"}}] 18664 children [{"oml-python:serialized_object": "component_reference", "value": {"key": "0", "step_name": "0"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "1", "step_name": "1"}}] 18665 args [] 18666 function {"oml-python:serialized_object": "methoddescriptor", "value": "torch._C._TensorBase.reshape"} 18666 kwargs {"shape": [-1, 1, 28, 28]} 18666 affine true 18667 eps 1e-05 18667 momentum 0.1 18667 num_features 1 18667 track_running_stats true 18667 children [{"oml-python:serialized_object": "component_reference", "value": {"key": "0", "step_name": "0"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "1", "step_name": "1"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "2", "step_name": "2"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "3", "step_name": "3"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "4", "step_name": "4"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "5", "step_name": "5"}}] 18668 dilation [1, 1] 18669 groups 1 18669 in_channels 1 18669 kernel_size [5, 5] 18669 out_channels 32 18669 padding [0, 0] 18669 padding_mode "zeros" 18669 stride [1, 1] 18669 inplace false 18670 negative_slope 0.01 18670 ceil_mode false 18671 dilation 1 18671 kernel_size 2 18671 padding 0 18671 return_indices false 18671 stride 2 18671 dilation [1, 1] 18672 groups 1 18672 in_channels 32 18672 kernel_size [5, 5] 18672 out_channels 64 18672 padding [0, 0] 18672 padding_mode "zeros" 18672 stride [1, 1] 18672 inplace false 18673 negative_slope 0.01 18673 ceil_mode false 18674 dilation 1 18674 kernel_size 2 18674 padding 0 18674 return_indices false 18674 stride 2 18674 children [{"oml-python:serialized_object": "component_reference", "value": {"key": "0", "step_name": "0"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "1", "step_name": "1"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "2", "step_name": "2"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "3", "step_name": "3"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "4", "step_name": "4"}}] 18675 args [] 18676 function {"oml-python:serialized_object": "methoddescriptor", "value": "torch._C._TensorBase.reshape"} 18676 kwargs {"shape": [-1, 1024]} 18676 in_features 1024 18677 out_features 256 18677 inplace false 18678 negative_slope 0.01 18678 inplace false 18679 p 0.5 18679 in_features 256 18680 out_features 10 18680 openml-python Torch_1.6.0_cu101. 554 mnist_784 https://www.openml.org/data/download/52667/mnist_784.arff -1 22044326 description https://api.openml.org/data/download/22044326/description.xml -1 22044327 predictions https://api.openml.org/data/download/22044327/predictions.arff area_under_roc_curve 0.9964205061290322 [0.999243,0.998367,0.995222,0.995488,0.997223,0.996791,0.99893,0.995829,0.994932,0.992054] average_cost 0 f_measure 0.9345046890281157 [0.967375,0.966155,0.921276,0.926353,0.937286,0.931881,0.957858,0.927056,0.910013,0.896125] kappa 0.9273398644527078 kb_relative_information_score 0.9139288236006772 mean_absolute_error 0.024879349980604436 mean_prior_absolute_error 0.1799414337543242 weighted_recall 0.9346285714285715 [0.97291,0.974864,0.917454,0.916818,0.940651,0.935055,0.965241,0.928836,0.894212,0.895803] number_of_instances 70000 [6903,7877,6990,7141,6824,6313,6876,7293,6825,6958] precision 0.9344994104036173 [0.961902,0.957601,0.92513,0.936088,0.933944,0.928729,0.950587,0.925283,0.926381,0.896448] predictive_accuracy 0.9346285714285715 prior_entropy 3.319837025446073 relative_absolute_error 0.13826359755792797 root_mean_prior_squared_error 0.2999511838524139 root_mean_squared_error 0.10119635768227139 root_relative_squared_error 0.33737609027762133 total_cost 0 unweighted_recall 0.9341844162703742 [0.97291,0.974864,0.917454,0.916818,0.940651,0.935055,0.965241,0.928836,0.894212,0.895803] area_under_roc_curve 0.9969579055826568 [0.9995,0.998333,0.995955,0.995868,0.9988,0.997576,0.999267,0.995448,0.996369,0.992521] area_under_roc_curve 0.9970540768307073 [0.998889,0.998623,0.995844,0.996691,0.997028,0.995353,0.998852,0.997801,0.995953,0.995135] area_under_roc_curve 0.9967378579972305 [0.99907,0.999032,0.995329,0.997039,0.997933,0.997149,0.999162,0.997159,0.993755,0.991479] area_under_roc_curve 0.9957175365547261 [0.999182,0.998501,0.994148,0.995072,0.994705,0.995988,0.998761,0.995493,0.994668,0.990375] area_under_roc_curve 0.9956155234788575 [0.999113,0.997303,0.994635,0.992625,0.996848,0.995288,0.998931,0.995678,0.994433,0.991198] area_under_roc_curve 0.9956293779906563 [0.999376,0.99794,0.994873,0.994863,0.995465,0.997355,0.998749,0.995248,0.993149,0.989189] area_under_roc_curve 0.9935638622918873 [0.998255,0.997125,0.991788,0.990287,0.995637,0.992985,0.997733,0.990056,0.991238,0.990347] area_under_roc_curve 0.9970681299859527 [0.999417,0.998811,0.996336,0.996399,0.997985,0.997687,0.999258,0.997393,0.995972,0.991292] area_under_roc_curve 0.9978654073050802 [0.999676,0.999142,0.9974,0.996951,0.998447,0.998709,0.999557,0.996757,0.997019,0.995011] area_under_roc_curve 0.997751233458882 [0.999634,0.998777,0.996192,0.997816,0.998795,0.998512,0.99923,0.996967,0.997106,0.994502] average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 f_measure 0.9427130340517225 [0.964029,0.972081,0.93,0.940426,0.954248,0.945626,0.962857,0.926129,0.925484,0.90393] f_measure 0.9422403712683108 [0.962644,0.972292,0.930301,0.929023,0.93946,0.934387,0.964861,0.942623,0.920937,0.921541] f_measure 0.9374198072616826 [0.96259,0.969356,0.928209,0.929972,0.941263,0.940625,0.961511,0.930233,0.910459,0.8967] f_measure 0.9282893558085118 [0.968481,0.968185,0.906228,0.915108,0.926579,0.915094,0.957602,0.925291,0.900888,0.893647] f_measure 0.9296767246907623 [0.976812,0.966306,0.910266,0.916369,0.925899,0.928052,0.952924,0.915007,0.912979,0.888569] f_measure 0.9221360135619346 [0.969343,0.952559,0.906516,0.916369,0.924198,0.92891,0.944444,0.912715,0.887879,0.875714] f_measure 0.9107533590217334 [0.957827,0.94598,0.895225,0.906117,0.918529,0.897764,0.942197,0.896033,0.876877,0.866233] f_measure 0.9395495596736557 [0.964925,0.969163,0.934877,0.931469,0.94898,0.935331,0.958393,0.937673,0.910714,0.9] f_measure 0.9456866995638222 [0.968953,0.977862,0.942019,0.929321,0.944974,0.942097,0.970972,0.94142,0.928144,0.907275] f_measure 0.9465894705807795 [0.978355,0.967985,0.929799,0.948628,0.94883,0.950078,0.963177,0.944099,0.92515,0.907514] kappa 0.9364882939646573 kappa 0.9358508531428228 kappa 0.9306099370653226 kappa 0.9204477356594624 kappa 0.9218750921551795 kappa 0.9136187816723099 kappa 0.9010745782444737 kappa 0.9329935344885273 kappa 0.9396633879388746 kappa 0.9407741881980809 kb_relative_information_score 0.9283864910618107 kb_relative_information_score 0.9229085121697241 kb_relative_information_score 0.9173048014618896 kb_relative_information_score 0.9051482104012816 kb_relative_information_score 0.8949979525915953 kb_relative_information_score 0.904661942462156 kb_relative_information_score 0.8802298604691312 kb_relative_information_score 0.9173193676269848 kb_relative_information_score 0.9357189467605626 kb_relative_information_score 0.9326117722989582 mean_absolute_error 0.020180885537803672 mean_absolute_error 0.022193309000094544 mean_absolute_error 0.024088047196018657 mean_absolute_error 0.027504096587403812 mean_absolute_error 0.031133003759731707 mean_absolute_error 0.027162038106612617 mean_absolute_error 0.03441557009182026 mean_absolute_error 0.024581556453896126 mean_absolute_error 0.018180872430492274 mean_absolute_error 0.01935412064217131 mean_prior_absolute_error 0.17994152998551463 mean_prior_absolute_error 0.17994170016528485 mean_prior_absolute_error 0.17994130267104935 mean_prior_absolute_error 0.17994130267104935 mean_prior_absolute_error 0.17994130267104935 mean_prior_absolute_error 0.1799413030791543 mean_prior_absolute_error 0.1799413030791543 mean_prior_absolute_error 0.1799414581590409 mean_prior_absolute_error 0.17994139612708626 mean_prior_absolute_error 0.17994173893525653 number_of_instances 7000 [691,787,699,714,682,631,687,730,683,696] number_of_instances 7000 [691,787,699,714,682,631,688,729,683,696] number_of_instances 7000 [690,788,699,714,682,631,688,729,683,696] number_of_instances 7000 [690,788,699,714,682,631,688,729,683,696] number_of_instances 7000 [690,788,699,714,682,631,688,729,683,696] number_of_instances 7000 [690,788,699,714,683,631,688,729,682,696] number_of_instances 7000 [690,788,699,714,683,631,688,729,682,696] number_of_instances 7000 [690,788,699,715,683,632,687,729,682,695] number_of_instances 7000 [690,788,699,714,683,632,687,730,682,695] number_of_instances 7000 [691,787,699,714,682,632,687,730,682,696] precision 0.942783196065958 [0.958512,0.970849,0.928673,0.952586,0.945324,0.940439,0.945302,0.924863,0.942337,0.915929] precision 0.9423752693193874 [0.955777,0.963795,0.954819,0.932299,0.934688,0.932177,0.971976,0.938776,0.920937,0.915014] precision 0.9375320416190673 [0.955714,0.95561,0.941176,0.929972,0.942647,0.927581,0.960813,0.927694,0.936533,0.895415] precision 0.9284201023646346 [0.957507,0.952147,0.906877,0.940828,0.927941,0.907956,0.963235,0.924658,0.910314,0.887943] precision 0.9300591499213733 [0.976812,0.968153,0.913545,0.935766,0.926579,0.947195,0.935574,0.886744,0.919762,0.889209] precision 0.922429090605144 [0.976471,0.937346,0.897616,0.935766,0.920174,0.925984,0.925978,0.914601,0.918495,0.870739] precision 0.9107755860228418 [0.944993,0.936567,0.892045,0.92052,0.90483,0.904992,0.936782,0.893588,0.898462,0.871907] precision 0.9395636459613723 [0.953324,0.961298,0.945827,0.931469,0.944848,0.93239,0.944837,0.946853,0.924471,0.906569] precision 0.9457871384450499 [0.965468,0.974779,0.942693,0.928671,0.947059,0.931889,0.968162,0.947295,0.948012,0.899576] precision 0.9466462399909213 [0.97554,0.956576,0.931133,0.953324,0.946064,0.936923,0.955587,0.951321,0.944954,0.912791] predictive_accuracy 0.942857142857143 predictive_accuracy 0.9422857142857143 predictive_accuracy 0.9375714285714285 predictive_accuracy 0.9284285714285714 predictive_accuracy 0.9297142857142857 predictive_accuracy 0.9222857142857143 predictive_accuracy 0.9109999999999999 predictive_accuracy 0.9397142857142857 predictive_accuracy 0.9457142857142857 predictive_accuracy 0.9467142857142857 prior_entropy 3.319842722993559 prior_entropy 3.3198548559727135 prior_entropy 3.3198276564080795 prior_entropy 3.3198276564080795 prior_entropy 3.3198276564080795 prior_entropy 3.319827686603566 prior_entropy 3.319827686603566 prior_entropy 3.3198399404547705 prior_entropy 3.319835600159663 prior_entropy 3.3198587924440996 relative_absolute_error 0.11215246163255496 relative_absolute_error 0.12333610819342572 relative_absolute_error 0.1338661376707604 relative_absolute_error 0.15285038053594646 relative_absolute_error 0.1730175523773213 relative_absolute_error 0.15094943540930303 relative_absolute_error 0.19125998035415587 relative_absolute_error 0.1366086320817172 relative_absolute_error 0.10103774240837703 relative_absolute_error 0.107557705936892 root_mean_prior_squared_error 0.2999513442637286 root_mean_prior_squared_error 0.29995162794255353 root_mean_prior_squared_error 0.29995096534459187 root_mean_prior_squared_error 0.29995096534459187 root_mean_prior_squared_error 0.29995096534459187 root_mean_prior_squared_error 0.29995096602487803 root_mean_prior_squared_error 0.29995096602487803 root_mean_prior_squared_error 0.29995122453349654 root_mean_prior_squared_error 0.2999511211300758 root_mean_prior_squared_error 0.2999516925695864 root_mean_squared_error 0.09480098700567902 root_mean_squared_error 0.09618717409074283 root_mean_squared_error 0.0989260343048172 root_mean_squared_error 0.10607789122558967 root_mean_squared_error 0.10851592184313147 root_mean_squared_error 0.10776740288675142 root_mean_squared_error 0.11861023138649772 root_mean_squared_error 0.09762371180172773 root_mean_squared_error 0.08959100516227761 root_mean_squared_error 0.09007833532381776 root_relative_squared_error 0.31605454957496837 root_relative_squared_error 0.3206756194340926 root_relative_squared_error 0.3298073543159571 root_relative_squared_error 0.3536507745648509 root_relative_squared_error 0.36177887181815005 root_relative_squared_error 0.359283399933485 root_relative_squared_error 0.39543206997593117 root_relative_squared_error 0.32546528841000205 root_relative_squared_error 0.29868534854859186 root_relative_squared_error 0.3003094750096144 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 unweighted_recall 0.9426982093120639 [0.969609,0.973316,0.93133,0.928571,0.963343,0.950872,0.981077,0.927397,0.909224,0.892241] unweighted_recall 0.9417668803505002 [0.969609,0.98094,0.90701,0.92577,0.944282,0.936609,0.957849,0.946502,0.920937,0.928161] unweighted_recall 0.9371337746716446 [0.969565,0.983503,0.915594,0.929972,0.939883,0.954041,0.962209,0.932785,0.885798,0.897989] unweighted_recall 0.9277423407499107 [0.97971,0.984772,0.905579,0.890756,0.92522,0.922345,0.952035,0.925926,0.891654,0.899425] unweighted_recall 0.9291222190072246 [0.976812,0.964467,0.90701,0.897759,0.92522,0.909667,0.97093,0.94513,0.906296,0.887931] unweighted_recall 0.9218541864029003 [0.962319,0.968274,0.915594,0.897759,0.928258,0.931854,0.963663,0.910837,0.859238,0.880747] unweighted_recall 0.9103583942177668 [0.971014,0.955584,0.898426,0.892157,0.93265,0.89065,0.947674,0.898491,0.856305,0.860632] unweighted_recall 0.9392952714992792 [0.976812,0.977157,0.924177,0.931469,0.953148,0.938291,0.972344,0.928669,0.897361,0.893525] unweighted_recall 0.9453790010604308 [0.972464,0.980964,0.941345,0.929972,0.942899,0.952532,0.973799,0.935616,0.909091,0.915108] unweighted_recall 0.9464855076649347 [0.981187,0.97967,0.928469,0.943978,0.951613,0.963608,0.970888,0.936986,0.906158,0.902299] weighted_recall 0.9428571428571428 [0.969609,0.973316,0.93133,0.928571,0.963343,0.950872,0.981077,0.927397,0.909224,0.892241] weighted_recall 0.9422857142857143 [0.969609,0.98094,0.90701,0.92577,0.944282,0.936609,0.957849,0.946502,0.920937,0.928161] weighted_recall 0.9375714285714286 [0.969565,0.983503,0.915594,0.929972,0.939883,0.954041,0.962209,0.932785,0.885798,0.897989] weighted_recall 0.9284285714285714 [0.97971,0.984772,0.905579,0.890756,0.92522,0.922345,0.952035,0.925926,0.891654,0.899425] weighted_recall 0.9297142857142857 [0.976812,0.964467,0.90701,0.897759,0.92522,0.909667,0.97093,0.94513,0.906296,0.887931] weighted_recall 0.9222857142857143 [0.962319,0.968274,0.915594,0.897759,0.928258,0.931854,0.963663,0.910837,0.859238,0.880747] weighted_recall 0.911 [0.971014,0.955584,0.898426,0.892157,0.93265,0.89065,0.947674,0.898491,0.856305,0.860632] weighted_recall 0.9397142857142857 [0.976812,0.977157,0.924177,0.931469,0.953148,0.938291,0.972344,0.928669,0.897361,0.893525] weighted_recall 0.9457142857142857 [0.972464,0.980964,0.941345,0.929972,0.942899,0.952532,0.973799,0.935616,0.909091,0.915108] weighted_recall 0.9467142857142857 [0.981187,0.97967,0.928469,0.943978,0.951613,0.963608,0.970888,0.936986,0.906158,0.902299]