10396177
8323
Heinrich Peters
6
Supervised Classification
16357
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(2)
8235394
memory
null
16357
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "svc", "step_name": "svc"}}]
16357
verbose
false
16357
add_indicator
false
16358
copy
true
16358
fill_value
null
16358
missing_values
NaN
16358
strategy
"median"
16358
verbose
0
16358
copy
true
16359
with_mean
true
16359
with_std
true
16359
C
8829.986986237445
16360
cache_size
200
16360
class_weight
null
16360
coef0
0.0
16360
decision_function_shape
"ovr"
16360
degree
3
16360
gamma
2.305877221785047
16360
kernel
"rbf"
16360
max_iter
-1
16360
probability
false
16360
random_state
1
16360
shrinking
true
16360
tol
0.001
16360
verbose
false
16360
openml-python
Sklearn_0.21.2.
6
letter
https://www.openml.org/data/download/6/dataset_6_letter.arff
-1
21714086
description
https://api.openml.org/data/download/21714086/description.xml
-1
21714087
predictions
https://api.openml.org/data/download/21714087/predictions.arff
area_under_roc_curve
0.912946352937481 [0.920152,0.91478,0.921092,0.929241,0.904037,0.914449,0.922585,0.869975,0.887872,0.913675,0.910797,0.908595,0.944061,0.89964,0.895008,0.911408,0.94558,0.9222,0.935595,0.926953,0.913847,0.898929,0.918805,0.887339,0.929025,0.885429]
average_cost
0
f_measure
0.8736800343376786 [0.913223,0.898305,0.911765,0.911126,0.887777,0.897418,0.905817,0.83628,0.868792,0.890007,0.872493,0.897547,0.917969,0.886058,0.880829,0.342932,0.924603,0.900914,0.925479,0.91706,0.90457,0.880866,0.909747,0.868327,0.915254,0.867433]
kappa
0.8261088726522477
kb_relative_information_score
0.8306333294283371
mean_absolute_error
0.01285769230769161
mean_prior_absolute_error
0.07396191835229461
number_of_instances
20000 [789,766,736,805,768,775,773,734,755,747,739,761,792,783,753,803,783,758,748,796,813,764,752,787,786,734]
precision
0.9480835220423898 [1,0.978462,0.99359,0.969188,0.984152,0.977204,0.974665,0.959436,0.986532,0.96118,0.926941,0.9952,0.947581,0.993651,0.994983,0.207882,0.958848,0.96391,0.986384,0.989811,0.997037,0.982287,0.995261,0.987055,0.979681,0.991243]
predictive_accuracy
0.83285
prior_entropy
4.6998107276322685
recall
0.83285 [0.840304,0.830287,0.842391,0.859627,0.808594,0.829677,0.846054,0.741144,0.776159,0.828648,0.824087,0.817346,0.890152,0.799489,0.790173,0.978829,0.89272,0.845646,0.871658,0.854271,0.827798,0.798429,0.837766,0.775095,0.858779,0.771117]
relative_absolute_error
0.17384206080821202
root_mean_prior_squared_error
0.19230433563020993
root_mean_squared_error
0.11339176472606646
root_relative_squared_error
0.5896474687087254
total_cost
0
area_under_roc_curve
0.9161601730278721 [0.917722,0.921818,0.939189,0.925405,0.88909,0.88961,0.908831,0.855645,0.867382,0.9184,0.951664,0.921053,0.961244,0.903846,0.89974,0.923958,0.928967,0.953687,0.946407,0.917201,0.914634,0.896104,0.933333,0.935897,0.904803,0.891632]
area_under_roc_curve
0.9135608774800584 [0.891026,0.88909,0.93893,0.900974,0.908571,0.901557,0.928311,0.883043,0.875,0.945427,0.896572,0.901056,0.91668,0.949107,0.86,0.898438,0.967428,0.907375,0.966407,0.936709,0.969136,0.902337,0.933074,0.873157,0.949107,0.858108]
area_under_roc_curve
0.9093956946889837 [0.898734,0.948052,0.925416,0.949575,0.881059,0.903586,0.908571,0.861976,0.920793,0.910345,0.931654,0.868421,0.961505,0.911392,0.913333,0.913802,0.928447,0.867382,0.911903,0.968094,0.895062,0.921298,0.886667,0.867089,0.898474,0.885135]
area_under_roc_curve
0.9159042148948714 [0.962025,0.902077,0.884876,0.961719,0.914214,0.928967,0.941298,0.827989,0.868421,0.926407,0.915992,0.927632,0.924219,0.905063,0.89974,0.919271,0.966908,0.907635,0.932173,0.898734,0.969136,0.895844,0.92,0.841772,0.948586,0.911643]
area_under_roc_curve
0.9174588795273028 [0.936709,0.914804,0.885135,0.936979,0.960779,0.909996,0.915324,0.910959,0.888158,0.905887,0.904627,0.934211,0.94375,0.891026,0.906667,0.917969,0.972798,0.920533,0.91974,0.90599,0.91358,0.914214,0.953333,0.867089,0.929227,0.890411]
area_under_roc_curve
0.9106931791627398 [0.917722,0.953687,0.912162,0.886979,0.902337,0.884355,0.910256,0.909662,0.886667,0.879481,0.883837,0.881579,0.936449,0.910256,0.887898,0.91276,0.942257,0.953947,0.9,0.925,0.944444,0.913694,0.906667,0.872377,0.941787,0.917549]
area_under_roc_curve
0.9151186495217865 [0.911392,0.855263,0.90411,0.95599,0.902337,0.993069,0.947938,0.891632,0.879481,0.91974,0.8776,0.940789,0.970779,0.884355,0.921053,0.913802,0.930119,0.906855,0.959221,0.930729,0.858025,0.87474,0.913333,0.929859,0.916667,0.89726]
area_under_roc_curve
0.9155986365544818 [0.955696,0.94027,0.931247,0.93125,0.87013,0.908571,0.922557,0.871622,0.913333,0.912814,0.883837,0.920793,0.979711,0.871535,0.861842,0.893576,0.947805,0.94027,0.946667,0.9375,0.925405,0.901056,0.92,0.898734,0.948198,0.863014]
area_under_roc_curve
0.9049169333514927 [0.911392,0.887898,0.938356,0.924363,0.915584,0.86987,0.927271,0.837578,0.893074,0.918961,0.925156,0.902337,0.942778,0.871795,0.886667,0.907845,0.916407,0.952294,0.933074,0.91849,0.878049,0.861842,0.901316,0.922817,0.92327,0.855905]
area_under_roc_curve
0.9106525997411695 [0.898734,0.934545,0.952055,0.919493,0.896104,0.954285,0.915324,0.850053,0.886667,0.89974,0.937112,0.888158,0.903762,0.897176,0.913333,0.912795,0.954868,0.912294,0.94,0.93125,0.871951,0.907895,0.920533,0.865385,0.93038,0.883562]
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
0.8781878540456122 [0.910345,0.909091,0.935252,0.907895,0.863309,0.875912,0.893617,0.818898,0.823529,0.898551,0.924138,0.914286,0.941935,0.893617,0.882353,0.353982,0.911565,0.945205,0.937063,0.897959,0.906667,0.884058,0.928571,0.931507,0.888889,0.87218]
f_measure
0.8733628693359192 [0.877698,0.863309,0.928571,0.884354,0.887324,0.867133,0.916667,0.854962,0.857143,0.929577,0.836879,0.884058,0.885906,0.940397,0.837209,0.337778,0.954248,0.885714,0.958904,0.932432,0.968153,0.885714,0.921986,0.848921,0.940397,0.834646]
f_measure
0.8672589652301226 [0.887324,0.945205,0.913043,0.924051,0.852941,0.887324,0.887324,0.815385,0.907801,0.859155,0.907801,0.848485,0.948052,0.902778,0.905109,0.339056,0.899329,0.823529,0.897059,0.961039,0.882759,0.896552,0.87218,0.846715,0.881119,0.870229]
f_measure
0.875832286551306 [0.960526,0.879433,0.863636,0.942675,0.9,0.911565,0.931507,0.774194,0.848485,0.914286,0.865248,0.921986,0.900662,0.895105,0.882353,0.355056,0.941935,0.892086,0.920863,0.887324,0.968153,0.877698,0.913043,0.81203,0.928105,0.890511]
f_measure
0.8808973846857393 [0.932432,0.888889,0.870229,0.921053,0.95302,0.895105,0.901408,0.902256,0.874074,0.877698,0.875912,0.929577,0.940397,0.877698,0.897059,0.351111,0.936709,0.901408,0.906475,0.890411,0.905405,0.9,0.951049,0.846715,0.917808,0.876923]
f_measure
0.8711400176493971 [0.910345,0.945205,0.903704,0.861111,0.885714,0.863309,0.901408,0.869565,0.87218,0.850746,0.838235,0.865672,0.926174,0.901408,0.867647,0.33617,0.921053,0.951724,0.888889,0.918919,0.941176,0.887324,0.897059,0.830986,0.926174,0.903704]
f_measure
0.8739851850077711 [0.902778,0.830769,0.893939,0.948052,0.885714,0.980892,0.927152,0.87218,0.850746,0.906475,0.842105,0.937063,0.887574,0.863309,0.914286,0.353741,0.918919,0.873239,0.938776,0.913907,0.834532,0.850746,0.905109,0.912752,0.909091,0.885496]
f_measure
0.8768136551144731 [0.953642,0.924138,0.919708,0.926174,0.850746,0.887324,0.90411,0.852713,0.905109,0.892086,0.838235,0.907801,0.95,0.846715,0.839695,0.340045,0.910256,0.924138,0.943662,0.933333,0.907895,0.884058,0.913043,0.887324,0.933333,0.84127]
f_measure
0.8625866024411472 [0.902778,0.867647,0.934307,0.884615,0.907801,0.844444,0.891892,0.8,0.874074,0.887324,0.906475,0.885714,0.933333,0.852941,0.87218,0.325866,0.902778,0.92517,0.921986,0.905405,0.861111,0.839695,0.890511,0.910345,0.899329,0.825397]
f_measure
0.8707585934279354 [0.887324,0.917808,0.94964,0.906667,0.884058,0.945946,0.901408,0.793893,0.87218,0.882353,0.884354,0.874074,0.864865,0.879433,0.905109,0.338983,0.946667,0.879433,0.93617,0.926174,0.853147,0.898551,0.901408,0.844444,0.92517,0.868217]
kappa
0.8325134554892805
kappa
0.8273108423043704
kappa
0.8189859781753266
kappa
0.8319902523137102
kappa
0.8351132776983686
kappa
0.8215873111647332
kappa
0.8304304076770291
kappa
0.8314563343157244
kappa
0.8101223514343956
kappa
0.8215747356067903
kb_relative_information_score
0.8369148516927218
kb_relative_information_score
0.8317749060789555
kb_relative_information_score
0.8236810202180425
kb_relative_information_score
0.8362048560494295
kb_relative_information_score
0.839412739451907
kb_relative_information_score
0.8262417614460409
kb_relative_information_score
0.8348492466271301
kb_relative_information_score
0.8357666825420267
kb_relative_information_score
0.8151276164054317
kb_relative_information_score
0.8263592919141333
mean_absolute_error
0.01238461538461535
mean_absolute_error
0.012769230769230732
mean_absolute_error
0.013384615384615346
mean_absolute_error
0.012423076923076887
mean_absolute_error
0.012192307692307659
mean_absolute_error
0.013192307692307654
mean_absolute_error
0.012538461538461504
mean_absolute_error
0.012461538461538427
mean_absolute_error
0.014038461538461498
mean_absolute_error
0.013192307692307654
mean_prior_absolute_error
0.07396194754511427
mean_prior_absolute_error
0.07396200900367966
mean_prior_absolute_error
0.07396191681583157
mean_prior_absolute_error
0.07396192641873242
mean_prior_absolute_error
0.07396195714801512
mean_prior_absolute_error
0.07396196483033579
mean_prior_absolute_error
0.07396196867149613
mean_prior_absolute_error
0.07396191489525139
mean_prior_absolute_error
0.07396179389870075
mean_prior_absolute_error
0.0739617842957999
number_of_instances
2000 [79,77,74,81,77,77,77,73,76,74,74,76,79,78,75,80,78,76,75,79,82,77,75,78,79,74]
number_of_instances
2000 [78,77,74,81,77,77,77,73,76,74,74,76,79,79,75,80,78,76,75,79,81,77,75,79,79,74]
number_of_instances
2000 [79,77,74,81,76,78,77,73,76,74,74,76,79,79,75,80,78,76,74,79,81,77,75,79,79,74]
number_of_instances
2000 [79,77,74,80,76,78,77,73,76,75,73,76,80,79,75,80,78,76,74,79,81,77,75,79,79,74]
number_of_instances
2000 [79,77,74,80,77,78,77,73,76,75,74,76,80,78,75,80,78,76,75,80,81,76,75,79,78,73]
number_of_instances
2000 [79,76,74,80,77,78,78,73,75,75,74,76,79,78,76,80,79,76,75,80,81,76,75,79,78,73]
number_of_instances
2000 [79,76,73,80,77,78,78,74,75,75,74,76,79,78,76,80,79,76,75,80,81,76,75,79,78,73]
number_of_instances
2000 [79,76,73,80,77,77,78,74,75,75,74,76,79,78,76,81,79,76,75,80,81,76,75,79,78,73]
number_of_instances
2000 [79,76,73,81,77,77,77,74,75,75,74,77,79,78,75,81,78,75,75,80,82,76,76,78,79,73]
number_of_instances
2000 [79,77,73,81,77,77,77,74,75,75,74,76,79,78,75,81,78,75,75,80,82,76,76,78,79,73]
precision
0.9511132291265488 [1,0.984848,1,0.971831,0.967742,1,0.984375,0.962963,0.933333,0.96875,0.943662,1,0.960526,1,0.983607,0.215054,0.971014,0.985714,0.985294,0.970588,1,1,1,1,0.984615,0.983051]
precision
0.9463821327110663 [1,0.967742,0.984848,0.984848,0.969231,0.939394,0.985075,0.965517,1,0.970588,0.880597,0.983871,0.942857,0.986111,1,0.205405,0.973333,0.96875,0.985915,1,1,0.984127,0.984848,0.983333,0.986111,1]
precision
0.9446092839642836 [1,1,0.984375,0.948052,0.966667,0.984375,0.969231,0.929825,0.984615,0.897059,0.955224,1,0.973333,1,1,0.204663,0.943662,0.933333,0.983871,0.986667,1,0.955882,1,1,0.984375,1]
precision
0.9475943494052202 [1,0.96875,0.982759,0.961039,0.984375,0.971014,0.985507,0.941176,1,0.984615,0.897059,1,0.957746,1,0.983607,0.216438,0.948052,0.984127,0.984615,1,1,0.983871,1,1,0.959459,0.968254]
precision
0.9540230089866393 [1,0.955224,1,0.972222,0.986111,0.984615,0.984615,1,1,0.953125,0.952381,1,1,1,1,0.213514,0.925,0.969697,0.984375,0.984848,1,0.984375,1,1,0.985294,1]
precision
0.9492530846894123 [1,0.985714,1,0.96875,0.984127,0.983607,1,0.923077,1,0.966102,0.919355,1,0.985714,1,0.983333,0.202564,0.958904,1,1,1,1,0.954545,1,0.936508,0.971831,0.983871]
precision
0.9459641515404789 [1,1,1,0.986486,0.984127,0.974684,0.958904,0.983051,0.966102,0.984375,0.949153,1,0.833333,0.983607,1,0.216066,0.985507,0.939394,0.958333,0.971831,1,0.982759,1,0.971429,1,1]
precision
0.9490502971927718 [1,0.971014,0.984375,1,1,0.969231,0.970588,1,1,0.96875,0.919355,0.984615,0.938272,0.983051,1,0.20765,0.922078,0.971014,1,1,0.971831,0.983871,1,1,0.972222,1]
precision
0.9474645526610844 [1,0.983333,1,0.92,1,0.982759,0.929577,0.980392,0.983333,0.940299,0.969231,0.984127,0.985915,1,1,0.195122,0.984848,0.944444,0.984848,0.985294,1,1,1,0.985075,0.957143,0.981132]
precision
0.949586547044096 [1,0.971014,1,0.985507,1,0.985915,0.984615,0.912281,1,0.983607,0.890411,1,0.927536,0.984127,1,0.204604,0.986111,0.939394,1,1,1,1,0.969697,1,1,1]
predictive_accuracy
0.8390000000000001
predictive_accuracy
0.8340000000000001
predictive_accuracy
0.826
predictive_accuracy
0.8384999999999999
predictive_accuracy
0.8415
predictive_accuracy
0.8284999999999999
predictive_accuracy
0.8370000000000001
predictive_accuracy
0.838
predictive_accuracy
0.8175
predictive_accuracy
0.8284999999999999
prior_entropy
4.699825815607033
prior_entropy
4.699854731688913
prior_entropy
4.699809751694497
prior_entropy
4.699813724681224
prior_entropy
4.6998289081692235
prior_entropy
4.699832499136173
prior_entropy
4.69983445932086
prior_entropy
4.699808889896364
prior_entropy
4.69975160696033
prior_entropy
4.699746889170326
recall
0.839 [0.835443,0.844156,0.878378,0.851852,0.779221,0.779221,0.818182,0.712329,0.736842,0.837838,0.905405,0.842105,0.924051,0.807692,0.8,1,0.858974,0.907895,0.893333,0.835443,0.829268,0.792208,0.866667,0.871795,0.810127,0.783784]
recall
0.834 [0.782051,0.779221,0.878378,0.802469,0.818182,0.805195,0.857143,0.767123,0.75,0.891892,0.797297,0.802632,0.835443,0.898734,0.72,0.95,0.935897,0.815789,0.933333,0.873418,0.938272,0.805195,0.866667,0.746835,0.898734,0.716216]
recall
0.826 [0.797468,0.896104,0.851351,0.901235,0.763158,0.807692,0.818182,0.726027,0.842105,0.824324,0.864865,0.736842,0.924051,0.822785,0.826667,0.9875,0.858974,0.736842,0.824324,0.936709,0.790123,0.844156,0.773333,0.734177,0.797468,0.77027]
recall
0.8385 [0.924051,0.805195,0.77027,0.925,0.828947,0.858974,0.883117,0.657534,0.736842,0.853333,0.835616,0.855263,0.85,0.810127,0.8,0.9875,0.935897,0.815789,0.864865,0.797468,0.938272,0.792208,0.84,0.683544,0.898734,0.824324]
recall
0.8415 [0.873418,0.831169,0.77027,0.875,0.922078,0.820513,0.831169,0.821918,0.776316,0.813333,0.810811,0.868421,0.8875,0.782051,0.813333,0.9875,0.948718,0.842105,0.84,0.8125,0.82716,0.828947,0.906667,0.734177,0.858974,0.780822]
recall
0.8285 [0.835443,0.907895,0.824324,0.775,0.805195,0.769231,0.820513,0.821918,0.773333,0.76,0.77027,0.763158,0.873418,0.820513,0.776316,0.9875,0.886076,0.907895,0.8,0.85,0.888889,0.828947,0.813333,0.746835,0.884615,0.835616]
recall
0.837 [0.822785,0.710526,0.808219,0.9125,0.805195,0.987179,0.897436,0.783784,0.76,0.84,0.756757,0.881579,0.949367,0.769231,0.842105,0.975,0.860759,0.815789,0.92,0.8625,0.716049,0.75,0.826667,0.860759,0.833333,0.794521]
recall
0.838 [0.911392,0.881579,0.863014,0.8625,0.74026,0.818182,0.846154,0.743243,0.826667,0.826667,0.77027,0.842105,0.962025,0.74359,0.723684,0.938272,0.898734,0.881579,0.893333,0.875,0.851852,0.802632,0.84,0.797468,0.897436,0.726027]
recall
0.8175 [0.822785,0.776316,0.876712,0.851852,0.831169,0.74026,0.857143,0.675676,0.786667,0.84,0.851351,0.805195,0.886076,0.74359,0.773333,0.987654,0.833333,0.906667,0.866667,0.8375,0.756098,0.723684,0.802632,0.846154,0.848101,0.712329]
recall
0.8285 [0.797468,0.87013,0.90411,0.839506,0.792208,0.909091,0.831169,0.702703,0.773333,0.8,0.878378,0.776316,0.810127,0.794872,0.826667,0.987654,0.910256,0.826667,0.88,0.8625,0.743902,0.815789,0.842105,0.730769,0.860759,0.767123]
relative_absolute_error
0.16744577172012887
relative_absolute_error
0.17264580750633007
relative_absolute_error
0.18096631294648066
relative_absolute_error
0.1679658376222402
relative_absolute_error
0.1648456606942946
relative_absolute_error
0.17836610645174175
relative_absolute_error
0.16952579499541695
relative_absolute_error
0.16848588194595945
relative_absolute_error
0.1898069367772339
relative_absolute_error
0.17836654182850495
root_mean_prior_squared_error
0.1923044115328483
root_mean_prior_squared_error
0.19230457132777806
root_mean_prior_squared_error
0.19230433163533361
root_mean_prior_squared_error
0.19230435660331052
root_mean_prior_squared_error
0.19230443650081483
root_mean_prior_squared_error
0.19230445647518574
root_mean_prior_squared_error
0.1923044664623704
root_mean_prior_squared_error
0.19230432664173788
root_mean_prior_squared_error
0.192304012044943
root_mean_prior_squared_error
0.19230398707692134
root_mean_squared_error
0.11128618685450298
root_mean_squared_error
0.11300102109817739
root_mean_squared_error
0.1156918985262812
root_mean_squared_error
0.1114588575353116
root_mean_squared_error
0.11041878324047796
root_mean_squared_error
0.11485777157993121
root_mean_squared_error
0.111975271995479
root_mean_squared_error
0.11163126113028746
root_mean_squared_error
0.11848401385191801
root_mean_squared_error
0.11485777157993121
root_relative_squared_error
0.5786980442489419
root_relative_squared_error
0.58761484616801
root_relative_squared_error
0.6016083857417605
root_relative_squared_error
0.5795961126623422
root_relative_squared_error
0.5741873939554697
root_relative_squared_error
0.5972704620849598
root_relative_squared_error
0.5822811817914277
root_relative_squared_error
0.5804927173492878
root_relative_squared_error
0.6161286631098853
root_relative_squared_error
0.5972719199731842
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
usercpu_time_millis
55794.22400000112
usercpu_time_millis
59684.9319999983
usercpu_time_millis
56465.48000000075
usercpu_time_millis
56523.09200000127
usercpu_time_millis
57505.58000000092
usercpu_time_millis
58140.142000000196
usercpu_time_millis
56533.66999999889
usercpu_time_millis
53798.179999999775
usercpu_time_millis
45768.809999999576
usercpu_time_millis
45491.735999999946
usercpu_time_millis_testing
3537.4680000004446
usercpu_time_millis_testing
3631.7459999991115
usercpu_time_millis_testing
3718.3960000002116
usercpu_time_millis_testing
3735.316000000239
usercpu_time_millis_testing
3738.119999999981
usercpu_time_millis_testing
3808.8520000001154
usercpu_time_millis_testing
3717.7259999989474
usercpu_time_millis_testing
3032.0339999998396
usercpu_time_millis_testing
3060.1000000006024
usercpu_time_millis_testing
3141.1499999994703
usercpu_time_millis_training
52256.75600000068
usercpu_time_millis_training
56053.18599999919
usercpu_time_millis_training
52747.08400000054
usercpu_time_millis_training
52787.77600000103
usercpu_time_millis_training
53767.46000000094
usercpu_time_millis_training
54331.29000000008
usercpu_time_millis_training
52815.943999999945
usercpu_time_millis_training
50766.145999999935
usercpu_time_millis_training
42708.70999999897
usercpu_time_millis_training
42350.586000000476
wall_clock_time_millis
28424.365758895874
wall_clock_time_millis
32439.06807899475
wall_clock_time_millis
29023.46897125244
wall_clock_time_millis
28813.889026641846
wall_clock_time_millis
29306.387186050415
wall_clock_time_millis
29682.12080001831
wall_clock_time_millis
28943.211793899536
wall_clock_time_millis
27336.10987663269
wall_clock_time_millis
23068.383932113647
wall_clock_time_millis
22899.112939834595
wall_clock_time_millis_testing
1792.8929328918457
wall_clock_time_millis_testing
1863.6598587036133
wall_clock_time_millis_testing
1889.343023300171
wall_clock_time_millis_testing
1905.2081108093262
wall_clock_time_millis_testing
1889.8720741271973
wall_clock_time_millis_testing
1931.1299324035645
wall_clock_time_millis_testing
1905.890941619873
wall_clock_time_millis_testing
1526.2527465820312
wall_clock_time_millis_testing
1543.7440872192383
wall_clock_time_millis_testing
1582.1259021759033
wall_clock_time_millis_training
26631.47282600403
wall_clock_time_millis_training
30575.408220291138
wall_clock_time_millis_training
27134.12594795227
wall_clock_time_millis_training
26908.68091583252
wall_clock_time_millis_training
27416.515111923218
wall_clock_time_millis_training
27750.990867614746
wall_clock_time_millis_training
27037.320852279663
wall_clock_time_millis_training
25809.85713005066
wall_clock_time_millis_training
21524.63984489441
wall_clock_time_millis_training
21316.98703765869