10317668
8323
Heinrich Peters
3481
Supervised Classification
12736
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,histgradientboostingclassifier=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(1)
8155058
l2_regularization
1e-05
12677
learning_rate
0.001
12677
loss
"auto"
12677
max_bins
4
12677
max_depth
8
12677
max_iter
450
12677
max_leaf_nodes
8
12677
min_samples_leaf
15
12677
n_iter_no_change
null
12677
random_state
42186
12677
scoring
null
12677
tol
1e-07
12677
validation_fraction
0.2
12677
verbose
0
12677
memory
null
12736
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "histgradientboostingclassifier", "step_name": "histgradientboostingclassifier"}}]
12736
verbose
false
12736
add_indicator
false
12737
copy
true
12737
fill_value
null
12737
missing_values
NaN
12737
strategy
"most_frequent"
12737
verbose
0
12737
openml-python
Sklearn_0.21.2.
300
isolet
https://www.openml.org/data/download/52405/phpB0xrNj
-1
21557019
description
https://api.openml.org/data/download/21557019/description.xml
-1
21557020
predictions
https://api.openml.org/data/download/21557020/predictions.arff
area_under_roc_curve
0.9925252821115068 [0.989046,0.99348,0.997339,0.989801,0.987102,0.994063,0.993228,0.99491,0.99917,0.996505,0.977284,0.998483,0.991681,0.989822,0.998552,0.986034,0.995644,0.9994,0.996845,0.98725,0.993324,0.980493,0.988493,0.997514,0.999813,0.990388]
average_cost
0
f_measure
0.8874466371274972 [0.862992,0.824645,0.948929,0.796085,0.756014,0.869565,0.883249,0.96633,0.950331,0.878939,0.82087,0.93617,0.857627,0.82069,0.926667,0.821429,0.942529,0.965058,0.898839,0.884746,0.923333,0.778702,0.886165,0.971714,0.981575,0.920204]
kappa
0.883021657685399
kb_relative_information_score
0.608098891308852
mean_absolute_error
0.0517963099158487
mean_prior_absolute_error
0.07396449117237175
number_of_instances
7797 [300,300,300,300,300,298,300,300,300,300,300,300,299,300,300,300,300,300,300,300,300,300,300,300,300,300]
precision
0.8883833100727002 [0.81791,0.783784,0.938111,0.779553,0.780142,0.866667,0.896907,0.97619,0.944079,0.874587,0.858182,0.919614,0.869416,0.85,0.926667,0.800633,0.928803,0.963455,0.894389,0.9,0.923333,0.777409,0.933579,0.9701,0.986532,0.937716]
predictive_accuracy
0.8875208413492369
prior_entropy
4.700438279892712
recall
0.8875208413492369 [0.913333,0.87,0.96,0.813333,0.733333,0.872483,0.87,0.956667,0.956667,0.883333,0.786667,0.953333,0.846154,0.793333,0.926667,0.843333,0.956667,0.966667,0.903333,0.87,0.923333,0.78,0.843333,0.973333,0.976667,0.903333]
relative_absolute_error
0.7002861656296553
root_mean_prior_squared_error
0.19230768465256318
root_mean_squared_error
0.13811904213866527
root_relative_squared_error
0.7182190477109691
total_cost
0
area_under_roc_curve
0.9928564102564102 [0.993556,0.983822,0.997467,0.976044,0.995422,0.998444,0.997956,0.999956,0.999956,0.996533,0.962,0.9984,0.9848,0.993378,0.995378,0.986444,0.994,0.999778,1,0.984844,0.996578,0.996444,0.986044,0.998844,0.999289,0.998889]
area_under_roc_curve
0.9927709401709399 [0.980889,0.994667,0.999778,0.989689,0.992489,0.995511,0.992978,0.999956,0.996578,0.999067,0.984622,0.999511,0.989467,0.994133,0.999467,0.968711,0.999867,0.997378,0.998178,0.992889,0.999022,0.960756,0.999733,0.998133,0.999911,0.988667]
area_under_roc_curve
0.9940529914529915 [0.9932,0.997111,0.992489,0.993333,0.996844,0.998356,0.992622,0.987778,0.998933,0.995378,0.986311,0.997733,0.998267,0.991911,0.999378,0.995244,0.998844,0.998311,0.996756,0.996578,0.9996,0.985867,0.986356,0.984133,0.999778,0.984267]
area_under_roc_curve
0.9929111111111111 [0.9892,0.995467,0.993511,0.991467,0.983022,0.995911,0.9992,0.994622,0.999778,0.994667,0.972667,0.997511,0.994356,0.986089,0.9992,0.987822,0.991556,1,0.993333,0.995867,0.999467,0.975022,0.999867,0.999644,1,0.986444]
area_under_roc_curve
0.9911162393162393 [0.9948,0.994711,0.999111,0.997156,0.976178,0.990044,0.997867,0.983333,0.999689,0.992978,0.980311,0.997689,0.989956,0.977422,0.9992,0.987378,0.999778,1,0.986622,0.975911,0.982133,0.990844,0.978933,0.999733,0.999956,0.997289]
area_under_roc_curve
0.9925606837606837 [0.995067,0.994444,0.999556,0.9716,0.982933,0.987333,0.9976,0.999556,1,0.999022,0.975156,0.998311,0.986444,0.994044,0.999689,0.9784,0.995511,0.999422,0.999333,0.997022,0.999867,0.968444,0.992578,0.998489,0.999822,0.996933]
area_under_roc_curve
0.9927008547008547 [0.983733,0.992933,0.999467,0.997911,0.982444,0.991467,0.998133,0.987378,0.999156,0.997689,0.967822,0.998933,0.992444,0.986578,0.994756,0.977556,0.994,0.999733,0.998978,0.9964,0.991422,0.996178,0.997289,0.999956,1,0.987867]
area_under_roc_curve
0.9950229894316369 [0.996796,0.990743,0.999955,0.992968,0.985937,0.998086,0.989987,0.999288,1,0.998353,0.998264,0.999822,0.997977,0.992746,0.999199,0.998175,0.996262,1,0.998887,0.965198,0.99911,0.984869,0.997997,0.99822,0.999955,0.9919]
area_under_roc_curve
0.9898714737607639 [0.997018,0.99368,0.992701,0.987272,0.99506,0.989701,0.97441,0.997374,0.99773,0.991945,0.971562,0.997775,0.991811,0.992879,0.999599,0.990432,0.987494,0.999377,0.997463,0.971785,0.97401,0.98923,0.970049,0.999911,0.999688,0.986693]
area_under_roc_curve
0.9924453508971884 [0.970449,0.995416,0.999911,0.998487,0.981486,0.997195,0.995639,0.999466,0.999822,0.998932,0.976547,0.998264,0.991055,0.990654,0.999733,0.991188,0.998843,0.999777,0.999021,0.999421,0.992434,0.965376,0.976324,1,0.999644,0.988652]
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
0.8882706811760558 [0.90625,0.754098,0.933333,0.78125,0.806452,0.949153,0.877193,1,0.931034,0.870968,0.8,0.903226,0.814815,0.825397,0.90625,0.827586,0.933333,0.95082,1,0.870968,0.9,0.83871,0.814815,0.95082,0.965517,0.983051]
f_measure
0.8926239957318868 [0.830769,0.8,0.95082,0.733333,0.776119,0.9,0.833333,1,0.949153,0.918033,0.872727,0.967742,0.852459,0.793103,0.949153,0.8,1,0.966667,0.870968,0.912281,0.965517,0.766667,0.933333,0.983051,0.967742,0.915254]
f_measure
0.8956075223130772 [0.857143,0.881356,0.888889,0.8125,0.827586,0.895522,0.862069,0.95082,0.861538,0.881356,0.857143,0.983051,0.888889,0.821429,0.947368,0.931034,0.935484,0.896552,0.912281,0.915254,0.983051,0.761905,0.912281,0.965517,0.983051,0.872727]
f_measure
0.8834263140591916 [0.903226,0.787879,0.95082,0.806452,0.75,0.847458,0.892308,0.983051,1,0.827586,0.745763,0.896552,0.847458,0.785714,0.920635,0.8,0.95082,1,0.915254,0.827586,0.95082,0.727273,0.95082,0.967742,0.983051,0.95082]
f_measure
0.8689949139321398 [0.848485,0.835821,0.966667,0.813559,0.689655,0.774194,0.933333,0.947368,0.966667,0.862069,0.758621,0.931034,0.793651,0.736842,0.920635,0.794118,0.9375,1,0.763636,0.9,0.896552,0.8,0.842105,0.983051,0.983051,0.915254]
f_measure
0.8893088651793205 [0.877193,0.83871,0.966667,0.666667,0.666667,0.833333,0.881356,0.966667,1,0.949153,0.821429,0.920635,0.877193,0.885246,0.949153,0.774194,0.920635,0.966667,0.9,0.903226,0.95082,0.806452,0.9,0.95082,1,0.949153]
f_measure
0.886967651153963 [0.8,0.852941,0.965517,0.847458,0.703704,0.896552,0.95082,0.949153,0.949153,0.852459,0.827586,0.935484,0.821429,0.807018,0.881356,0.8,0.931034,0.966667,0.935484,0.949153,0.857143,0.84375,0.857143,1,0.983607,0.896552]
f_measure
0.90418259729751 [0.903226,0.818182,0.9375,0.779661,0.714286,0.870968,0.881356,0.949153,0.967742,0.918033,0.931034,0.983607,0.966667,0.881356,0.966667,0.865672,0.965517,0.983051,0.885246,0.827586,0.931034,0.754717,0.928571,0.966667,1,0.933333]
f_measure
0.8752318460756388 [0.869565,0.857143,0.949153,0.786885,0.827586,0.892857,0.821429,0.966667,0.933333,0.793651,0.785714,0.935484,0.866667,0.814815,0.947368,0.794118,0.918033,0.95082,0.920635,0.769231,0.866667,0.78125,0.892857,0.966667,0.966667,0.881356]
f_measure
0.8874071552178877 [0.83871,0.819672,0.983607,0.935484,0.779661,0.836364,0.892857,0.949153,0.95082,0.918033,0.807018,0.90625,0.842105,0.847458,0.881356,0.836364,0.935484,0.967742,0.875,0.952381,0.935484,0.698413,0.814815,0.983607,0.983051,0.9]
kappa
0.884
kappa
0.888
kappa
0.8906666666666667
kappa
0.88
kappa
0.864
kappa
0.8853333333333333
kappa
0.8826666666666666
kappa
0.9012068510476399
kappa
0.8704999845757826
kappa
0.8838503025722497
kb_relative_information_score
0.6025413662913292
kb_relative_information_score
0.6173752497392409
kb_relative_information_score
0.6146854433422313
kb_relative_information_score
0.6052192082782204
kb_relative_information_score
0.6011927714146975
kb_relative_information_score
0.604090372472164
kb_relative_information_score
0.6079690706043607
kb_relative_information_score
0.6183319527870285
kb_relative_information_score
0.6000486691333342
kb_relative_information_score
0.6095394499208117
mean_absolute_error
0.052161609737630586
mean_absolute_error
0.051422449524188486
mean_absolute_error
0.05147477690436369
mean_absolute_error
0.0518867490353424
mean_absolute_error
0.05212897439403665
mean_absolute_error
0.05202382072660223
mean_absolute_error
0.05182864960879129
mean_absolute_error
0.051429357288281734
mean_absolute_error
0.05199023067694151
mean_absolute_error
0.05161602829630051
mean_prior_absolute_error
0.07396449704142057
mean_prior_absolute_error
0.07396449704142057
mean_prior_absolute_error
0.07396449704142057
mean_prior_absolute_error
0.07396449704142057
mean_prior_absolute_error
0.07396449704142057
mean_prior_absolute_error
0.07396449704142057
mean_prior_absolute_error
0.07396449704142057
mean_prior_absolute_error
0.07396448587535052
mean_prior_absolute_error
0.07396447325283656
mean_prior_absolute_error
0.07396447325283656
number_of_instances
780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
779 [30,30,30,30,30,30,30,30,30,30,30,30,29,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
779 [30,30,30,30,30,29,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
779 [30,30,30,30,30,29,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
precision
0.8919646239618184 [0.852941,0.741935,0.933333,0.735294,0.78125,0.965517,0.925926,1,0.964286,0.84375,0.88,0.875,0.916667,0.787879,0.852941,0.857143,0.933333,0.935484,1,0.84375,0.9,0.8125,0.916667,0.935484,1,1]
precision
0.8957728639312343 [0.771429,0.8,0.935484,0.733333,0.702703,0.9,0.833333,1,0.965517,0.903226,0.96,0.9375,0.83871,0.821429,0.965517,0.88,1,0.966667,0.84375,0.962963,1,0.766667,0.933333,1,0.9375,0.931034]
precision
0.9005920388142497 [0.818182,0.896552,0.848485,0.764706,0.857143,0.810811,0.892857,0.935484,0.8,0.896552,0.818182,1,0.848485,0.884615,1,0.964286,0.90625,0.928571,0.962963,0.931034,1,0.727273,0.962963,1,1,0.96]
precision
0.8850479724835311 [0.875,0.722222,0.935484,0.78125,0.807692,0.862069,0.828571,1,1,0.857143,0.758621,0.928571,0.862069,0.846154,0.878788,0.8,0.935484,1,0.931034,0.857143,0.935484,0.8,0.935484,0.9375,1,0.935484]
precision
0.8735171437141118 [0.777778,0.756757,0.966667,0.827586,0.714286,0.75,0.933333,1,0.966667,0.892857,0.785714,0.964286,0.757576,0.777778,0.878788,0.710526,0.882353,1,0.84,0.9,0.928571,0.88,0.888889,1,1,0.931034]
precision
0.8910588036879534 [0.925926,0.8125,0.966667,0.636364,0.75,0.833333,0.896552,0.966667,1,0.965517,0.884615,0.878788,0.925926,0.870968,0.965517,0.75,0.878788,0.966667,0.9,0.875,0.935484,0.78125,0.9,0.935484,1,0.965517]
precision
0.891047248646337 [0.742857,0.763158,1,0.862069,0.791667,0.928571,0.935484,0.965517,0.965517,0.83871,0.857143,0.90625,0.884615,0.851852,0.896552,0.742857,0.964286,0.966667,0.90625,0.965517,0.818182,0.794118,0.923077,1,0.967742,0.928571]
precision
0.9073757777034954 [0.875,0.75,0.882353,0.793103,0.769231,0.84375,0.896552,0.965517,0.9375,0.903226,0.964286,0.967742,0.935484,0.896552,0.966667,0.783784,1,1,0.870968,0.857143,0.964286,0.869565,1,0.966667,1,0.933333]
precision
0.8814283197229641 [0.769231,0.818182,0.965517,0.774194,0.857143,0.925926,0.884615,0.966667,0.933333,0.757576,0.846154,0.90625,0.866667,0.916667,1,0.710526,0.903226,0.935484,0.878788,0.909091,0.866667,0.735294,0.961538,0.966667,0.966667,0.896552]
precision
0.8901003380744908 [0.8125,0.806452,0.967742,0.90625,0.793103,0.884615,0.961538,0.965517,0.935484,0.903226,0.851852,0.852941,0.888889,0.862069,0.896552,0.92,0.90625,0.9375,0.823529,0.909091,0.90625,0.666667,0.916667,0.967742,1,0.9]
predictive_accuracy
0.8884615384615384
predictive_accuracy
0.8923076923076922
predictive_accuracy
0.8948717948717949
predictive_accuracy
0.8846153846153847
predictive_accuracy
0.8692307692307693
predictive_accuracy
0.8897435897435898
predictive_accuracy
0.8871794871794871
predictive_accuracy
0.9050064184852374
predictive_accuracy
0.8754813863928114
predictive_accuracy
0.8883183568677793
prior_entropy
4.700441149362989
prior_entropy
4.700441149362989
prior_entropy
4.700441149362989
prior_entropy
4.700441149362989
prior_entropy
4.700441149362989
prior_entropy
4.700441149362989
prior_entropy
4.700441149362989
prior_entropy
4.700435698259304
prior_entropy
4.700429514669705
prior_entropy
4.700429514669705
recall
0.8884615384615384 [0.966667,0.766667,0.933333,0.833333,0.833333,0.933333,0.833333,1,0.9,0.9,0.733333,0.933333,0.733333,0.866667,0.966667,0.8,0.933333,0.966667,1,0.9,0.9,0.866667,0.733333,0.966667,0.933333,0.966667]
recall
0.8923076923076924 [0.9,0.8,0.966667,0.733333,0.866667,0.9,0.833333,1,0.933333,0.933333,0.8,1,0.866667,0.766667,0.933333,0.733333,1,0.966667,0.9,0.866667,0.933333,0.766667,0.933333,0.966667,1,0.9]
recall
0.8948717948717949 [0.9,0.866667,0.933333,0.866667,0.8,1,0.833333,0.966667,0.933333,0.866667,0.9,0.966667,0.933333,0.766667,0.9,0.9,0.966667,0.866667,0.866667,0.9,0.966667,0.8,0.866667,0.933333,0.966667,0.8]
recall
0.8846153846153846 [0.933333,0.866667,0.966667,0.833333,0.7,0.833333,0.966667,0.966667,1,0.8,0.733333,0.866667,0.833333,0.733333,0.966667,0.8,0.966667,1,0.9,0.8,0.966667,0.666667,0.966667,1,0.966667,0.966667]
recall
0.8692307692307693 [0.933333,0.933333,0.966667,0.8,0.666667,0.8,0.933333,0.9,0.966667,0.833333,0.733333,0.9,0.833333,0.7,0.966667,0.9,1,1,0.7,0.9,0.866667,0.733333,0.8,0.966667,0.966667,0.9]
recall
0.8897435897435897 [0.833333,0.866667,0.966667,0.7,0.6,0.833333,0.866667,0.966667,1,0.933333,0.766667,0.966667,0.833333,0.9,0.933333,0.8,0.966667,0.966667,0.9,0.933333,0.966667,0.833333,0.9,0.966667,1,0.933333]
recall
0.8871794871794871 [0.866667,0.966667,0.933333,0.833333,0.633333,0.866667,0.966667,0.933333,0.933333,0.866667,0.8,0.966667,0.766667,0.766667,0.866667,0.866667,0.9,0.966667,0.966667,0.933333,0.9,0.9,0.8,1,1,0.866667]
recall
0.9050064184852374 [0.933333,0.9,1,0.766667,0.666667,0.9,0.866667,0.933333,1,0.933333,0.9,1,1,0.866667,0.966667,0.966667,0.933333,0.966667,0.9,0.8,0.9,0.666667,0.866667,0.966667,1,0.933333]
recall
0.8754813863928113 [1,0.9,0.933333,0.8,0.8,0.862069,0.766667,0.966667,0.933333,0.833333,0.733333,0.966667,0.866667,0.733333,0.9,0.9,0.933333,0.966667,0.966667,0.666667,0.866667,0.833333,0.833333,0.966667,0.966667,0.866667]
recall
0.8883183568677792 [0.866667,0.833333,1,0.966667,0.766667,0.793103,0.833333,0.933333,0.966667,0.933333,0.766667,0.966667,0.8,0.833333,0.866667,0.766667,0.966667,1,0.933333,1,0.966667,0.733333,0.733333,1,0.966667,0.9]
relative_absolute_error
0.7052249636527612
relative_absolute_error
0.6952315175670242
relative_absolute_error
0.6959389837469928
relative_absolute_error
0.7015088469578251
relative_absolute_error
0.7047837338073712
relative_absolute_error
0.7033620562236578
relative_absolute_error
0.7007233427108541
relative_absolute_error
0.6953250155074915
relative_absolute_error
0.7029081448227263
relative_absolute_error
0.6978489270093061
root_mean_prior_squared_error
0.19230769991209876
root_mean_prior_squared_error
0.19230769991209876
root_mean_prior_squared_error
0.19230769991209876
root_mean_prior_squared_error
0.19230769991209876
root_mean_prior_squared_error
0.19230769991209876
root_mean_prior_squared_error
0.19230769991209876
root_mean_prior_squared_error
0.19230769991209876
root_mean_prior_squared_error
0.19230767088031558
root_mean_prior_squared_error
0.19230763806177284
root_mean_prior_squared_error
0.19230763806177284
root_mean_squared_error
0.1390808218182383
root_mean_squared_error
0.13706383636196612
root_mean_squared_error
0.13706015592197812
root_mean_squared_error
0.1384036361561341
root_mean_squared_error
0.13919081507950246
root_mean_squared_error
0.1387599621406699
root_mean_squared_error
0.13822981846351423
root_mean_squared_error
0.1369294575330709
root_mean_squared_error
0.1387887194254379
root_mean_squared_error
0.13765700873352701
root_relative_squared_error
0.7232202448566036
root_relative_squared_error
0.7127319208987271
root_relative_squared_error
0.7127127826115462
root_relative_squared_error
0.7196988795529067
root_relative_squared_error
0.7237922097925601
root_relative_squared_error
0.7215517745992241
root_relative_squared_error
0.7187950275870244
root_relative_squared_error
0.7120332585083939
root_relative_squared_error
0.7217015445889692
root_relative_squared_error
0.715816647331028
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
290418.45424899657
usercpu_time_millis
315855.799629011
usercpu_time_millis
291310.51284800196
usercpu_time_millis
289792.14449399296
usercpu_time_millis
316020.81852000265
usercpu_time_millis
291335.8319510007
usercpu_time_millis
289615.8053370018
usercpu_time_millis
290833.6780979953
usercpu_time_millis
281145.26660800766
usercpu_time_millis
280535.9008499945
usercpu_time_millis_testing
387.7282899993588
usercpu_time_millis_testing
411.86341100546997
usercpu_time_millis_testing
455.0483630009694
usercpu_time_millis_testing
444.715396995889
usercpu_time_millis_testing
445.1299520005705
usercpu_time_millis_testing
443.6608059986611
usercpu_time_millis_testing
850.127641002473
usercpu_time_millis_testing
429.2085449997103
usercpu_time_millis_testing
494.95165700500365
usercpu_time_millis_testing
452.7762189973146
usercpu_time_millis_training
290030.7259589972
usercpu_time_millis_training
315443.93621800555
usercpu_time_millis_training
290855.464485001
usercpu_time_millis_training
289347.4290969971
usercpu_time_millis_training
315575.6885680021
usercpu_time_millis_training
290892.17114500207
usercpu_time_millis_training
288765.67769599933
usercpu_time_millis_training
290404.4695529956
usercpu_time_millis_training
280650.31495100266
usercpu_time_millis_training
280083.1246309972
wall_clock_time_millis
290445.1584815979
wall_clock_time_millis
407067.2061443329
wall_clock_time_millis
291339.84756469727
wall_clock_time_millis
289807.01994895935
wall_clock_time_millis
316046.44441604614
wall_clock_time_millis
291368.99614334106
wall_clock_time_millis
289682.9102039337
wall_clock_time_millis
290901.72481536865
wall_clock_time_millis
281259.96804237366
wall_clock_time_millis
280605.85284233093
wall_clock_time_millis_testing
387.7396583557129
wall_clock_time_millis_testing
411.87596321105957
wall_clock_time_millis_testing
455.0642967224121
wall_clock_time_millis_testing
444.7298049926758
wall_clock_time_millis_testing
445.1425075531006
wall_clock_time_millis_testing
443.71485710144043
wall_clock_time_millis_testing
850.6796360015869
wall_clock_time_millis_testing
429.3854236602783
wall_clock_time_millis_testing
494.9662685394287
wall_clock_time_millis_testing
452.82602310180664
wall_clock_time_millis_training
290057.4188232422
wall_clock_time_millis_training
406655.3301811218
wall_clock_time_millis_training
290884.78326797485
wall_clock_time_millis_training
289362.2901439667
wall_clock_time_millis_training
315601.30190849304
wall_clock_time_millis_training
290925.2812862396
wall_clock_time_millis_training
288832.2305679321
wall_clock_time_millis_training
290472.3393917084
wall_clock_time_millis_training
280765.0017738342
wall_clock_time_millis_training
280153.0268192291