10329390
8323
Heinrich Peters
53
Supervised Classification
16345
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(1)
8185010
add_indicator
false
12737
copy
true
12737
fill_value
null
12737
missing_values
NaN
12737
strategy
"most_frequent"
12737
verbose
0
12737
copy
true
13294
with_mean
true
13294
with_std
true
13294
C
0.04763431960619049
13389
cache_size
200
13389
class_weight
null
13389
coef0
-0.21633948699433825
13389
decision_function_shape
"ovr"
13389
degree
1
13389
gamma
2.0076472291150194
13389
kernel
"poly"
13389
max_iter
-1
13389
probability
false
13389
random_state
23357
13389
shrinking
true
13389
tol
0.001
13389
verbose
false
13389
memory
null
16345
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"}}]
16345
verbose
false
16345
openml-python
Sklearn_0.21.2.
54
vehicle
https://www.openml.org/data/download/54/dataset_54_vehicle.arff
-1
21580477
description
https://api.openml.org/data/download/21580477/description.xml
-1
21580478
predictions
https://api.openml.org/data/download/21580478/predictions.arff
area_under_roc_curve
0.8428483258787408 [0.730961,0.729275,0.953179,0.965026]
average_cost
0
f_measure
0.7566043349853079 [0.60199,0.601942,0.912281,0.919431]
kappa
0.6864098647692137
kb_relative_information_score
0.7172844873585639
mean_absolute_error
0.11761229314420804
mean_prior_absolute_error
0.3748407731887084
number_of_instances
846 [212,217,218,199]
precision
0.7525323339740877 [0.636842,0.635897,0.87395,0.869955]
predictive_accuracy
0.764775413711584
prior_entropy
1.9990667866719984
recall
0.764775413711584 [0.570755,0.571429,0.954128,0.974874]
relative_absolute_error
0.31376600828052864
root_mean_prior_squared_error
0.4329203297871725
root_mean_squared_error
0.3429464872895012
root_relative_squared_error
0.7921699760741123
total_cost
0
area_under_roc_curve
0.8274896978021978 [0.667783,0.694444,0.984127,0.969231]
area_under_roc_curve
0.8191811660561661 [0.738839,0.678571,0.945527,0.919231]
area_under_roc_curve
0.8349378052503053 [0.691592,0.724026,0.946609,0.984615]
area_under_roc_curve
0.8663118131868133 [0.762649,0.786436,0.93759,0.984615]
area_under_roc_curve
0.850318605006105 [0.683408,0.761544,0.969336,0.992308]
area_under_roc_curve
0.8903655372405371 [0.834077,0.825036,0.930736,0.976923]
area_under_roc_curve
0.8486470518728585 [0.747067,0.769795,0.952381,0.942915]
area_under_roc_curve
0.8408738159242193 [0.747067,0.714286,0.936508,0.976562]
area_under_roc_curve
0.8416338645673324 [0.785714,0.65873,0.961144,0.960938]
area_under_roc_curve
0.8091357846902202 [0.650794,0.674603,0.967742,0.942187]
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
0.727356428737503 [0.5,0.55,0.956522,0.909091]
f_measure
0.7205802124450434 [0.615385,0.52381,0.893617,0.857143]
f_measure
0.7503650354072429 [0.536585,0.590909,0.930233,0.952381]
f_measure
0.7923249299719888 [0.65,0.7,0.875,0.952381]
f_measure
0.7718515281457407 [0.526316,0.638298,0.954545,0.97561]
f_measure
0.8318963602137337 [0.744186,0.769231,0.888889,0.930233]
f_measure
0.7665681202266568 [0.634146,0.666667,0.909091,0.878049]
f_measure
0.7496980354410158 [0.634146,0.578947,0.869565,0.930233]
f_measure
0.7484379850233508 [0.682927,0.486486,0.933333,0.888889]
f_measure
0.7061876142353498 [0.473684,0.511628,0.916667,0.923077]
kappa
0.6551088159350793
kappa
0.6390991323610854
kappa
0.6706034323675955
kappa
0.733296419342931
kappa
0.7016992981159956
kappa
0.7805642633228841
kappa
0.6986973758731356
kappa
0.6827794561933535
kappa
0.6826596146581034
kappa
0.6185430463576159
kb_relative_information_score
0.6890250942836318
kb_relative_information_score
0.6742539900416367
kb_relative_information_score
0.7032761975891659
kb_relative_information_score
0.7597916751223371
kb_relative_information_score
0.7312610231964918
kb_relative_information_score
0.8024179129626419
kb_relative_information_score
0.7277473705636908
kb_relative_information_score
0.7142165475450584
kb_relative_information_score
0.7144115983499322
kb_relative_information_score
0.6557911338524934
mean_absolute_error
0.12941176470588237
mean_absolute_error
0.13529411764705881
mean_absolute_error
0.12352941176470589
mean_absolute_error
0.1
mean_absolute_error
0.11176470588235295
mean_absolute_error
0.08235294117647059
mean_absolute_error
0.1130952380952381
mean_absolute_error
0.11904761904761904
mean_absolute_error
0.11904761904761904
mean_absolute_error
0.14285714285714285
mean_prior_absolute_error
0.37483044982698976
mean_prior_absolute_error
0.37483044982698976
mean_prior_absolute_error
0.37483044982698976
mean_prior_absolute_error
0.37483044982698976
mean_prior_absolute_error
0.37483044982698976
mean_prior_absolute_error
0.37483044982698976
mean_prior_absolute_error
0.37478291316526624
mean_prior_absolute_error
0.37490896358543435
mean_prior_absolute_error
0.37486694677871163
mean_prior_absolute_error
0.37486694677871163
number_of_instances
85 [21,22,22,20]
number_of_instances
85 [21,22,22,20]
number_of_instances
85 [21,22,22,20]
number_of_instances
85 [21,22,22,20]
number_of_instances
85 [21,22,22,20]
number_of_instances
85 [21,22,22,20]
number_of_instances
84 [22,22,21,19]
number_of_instances
84 [22,21,21,20]
number_of_instances
84 [21,21,22,20]
number_of_instances
84 [21,21,22,20]
precision
0.7215342277261781 [0.526316,0.611111,0.916667,0.833333]
precision
0.7169839572192512 [0.666667,0.55,0.84,0.818182]
precision
0.7492258721670486 [0.55,0.590909,0.952381,0.909091]
precision
0.7933009542916662 [0.684211,0.777778,0.807692,0.909091]
precision
0.7717712967539957 [0.588235,0.6,0.954545,0.952381]
precision
0.8377203659887578 [0.727273,0.882353,0.869565,0.869565]
precision
0.7649875677335632 [0.684211,0.7,0.869565,0.818182]
precision
0.7480020383439417 [0.684211,0.647059,0.8,0.869565]
precision
0.7452316252587992 [0.7,0.5625,0.913043,0.8]
precision
0.7045285725626284 [0.529412,0.5,0.846154,0.947368]
predictive_accuracy
0.7411764705882353
predictive_accuracy
0.7294117647058823
predictive_accuracy
0.7529411764705882
predictive_accuracy
0.8
predictive_accuracy
0.776470588235294
predictive_accuracy
0.8352941176470589
predictive_accuracy
0.7738095238095238
predictive_accuracy
0.7619047619047619
predictive_accuracy
0.7619047619047619
predictive_accuracy
0.7142857142857143
prior_entropy
1.9989496630655892
prior_entropy
1.9989496630655892
prior_entropy
1.9989496630655892
prior_entropy
1.9989496630655892
prior_entropy
1.9989496630655892
prior_entropy
1.9989496630655892
prior_entropy
1.998373047127382
prior_entropy
1.9998531439726461
prior_entropy
1.99937603159913
prior_entropy
1.99937603159913
recall
0.7411764705882353 [0.47619,0.5,1,1]
recall
0.7294117647058823 [0.571429,0.5,0.954545,0.9]
recall
0.7529411764705882 [0.52381,0.590909,0.909091,1]
recall
0.8 [0.619048,0.636364,0.954545,1]
recall
0.7764705882352941 [0.47619,0.681818,0.954545,1]
recall
0.8352941176470589 [0.761905,0.681818,0.909091,1]
recall
0.7738095238095238 [0.590909,0.636364,0.952381,0.947368]
recall
0.7619047619047619 [0.590909,0.52381,0.952381,1]
recall
0.7619047619047619 [0.666667,0.428571,0.954545,1]
recall
0.7142857142857143 [0.428571,0.52381,1,0.9]
relative_absolute_error
0.345254140280265
relative_absolute_error
0.3609475102930043
relative_absolute_error
0.32956077026752567
relative_absolute_error
0.2667872902165684
relative_absolute_error
0.2981740302420471
relative_absolute_error
0.21970718017835045
relative_absolute_error
0.30176199106859236
relative_absolute_error
0.3175374040383284
relative_absolute_error
0.3175729950869588
relative_absolute_error
0.38108759410435056
root_mean_prior_squared_error
0.43290840668819885
root_mean_prior_squared_error
0.43290840668819885
root_mean_prior_squared_error
0.43290840668819885
root_mean_prior_squared_error
0.43290840668819885
root_mean_prior_squared_error
0.43290840668819885
root_mean_prior_squared_error
0.43290840668819885
root_mean_prior_squared_error
0.4328534993731614
root_mean_prior_squared_error
0.43299907891329226
root_mean_prior_squared_error
0.43295055783892555
root_mean_prior_squared_error
0.43295055783892555
root_mean_squared_error
0.3597384670922507
root_mean_squared_error
0.36782348707914075
root_mean_squared_error
0.3514675116774037
root_mean_squared_error
0.31622776601683794
root_mean_squared_error
0.33431228796194873
root_mean_squared_error
0.2869720215917757
root_mean_squared_error
0.33629635456727464
root_mean_squared_error
0.3450327796711771
root_mean_squared_error
0.3450327796711771
root_mean_squared_error
0.3779644730092272
root_relative_squared_error
0.8309805527785729
root_relative_squared_error
0.8496566049456846
root_relative_squared_error
0.811874997684088
root_relative_squared_error
0.7304726845939957
root_relative_squared_error
0.7722471608243364
root_relative_squared_error
0.6628931597497634
root_relative_squared_error
0.77692881091243
root_relative_squared_error
0.7968441423411657
root_relative_squared_error
0.7969334452261931
root_relative_squared_error
0.8729968495613873
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
32.702684999094345
usercpu_time_millis
33.64129699184559
usercpu_time_millis
33.018157992046326
usercpu_time_millis
34.15953001240268
usercpu_time_millis
34.07907500513829
usercpu_time_millis
34.14419099863153
usercpu_time_millis
33.40520399797242
usercpu_time_millis
33.71696999238338
usercpu_time_millis
33.89140800572932
usercpu_time_millis
34.07189798599575
usercpu_time_millis_testing
2.63907499902416
usercpu_time_millis_testing
2.5470409891568124
usercpu_time_millis_testing
2.5475989968981594
usercpu_time_millis_testing
2.6906060084002092
usercpu_time_millis_testing
2.6144810108235106
usercpu_time_millis_testing
2.63721399824135
usercpu_time_millis_testing
2.553247002651915
usercpu_time_millis_testing
2.5990479916799814
usercpu_time_millis_testing
2.6964370044879615
usercpu_time_millis_testing
2.555443992605433
usercpu_time_millis_training
30.063610000070184
usercpu_time_millis_training
31.09425600268878
usercpu_time_millis_training
30.470558995148167
usercpu_time_millis_training
31.468924004002474
usercpu_time_millis_training
31.464593994314782
usercpu_time_millis_training
31.50697700039018
usercpu_time_millis_training
30.851956995320506
usercpu_time_millis_training
31.117922000703402
usercpu_time_millis_training
31.194971001241356
usercpu_time_millis_training
31.516453993390314
wall_clock_time_millis
32.72080421447754
wall_clock_time_millis
33.658742904663086
wall_clock_time_millis
33.03647041320801
wall_clock_time_millis
34.19089317321777
wall_clock_time_millis
34.093379974365234
wall_clock_time_millis
34.23595428466797
wall_clock_time_millis
33.464908599853516
wall_clock_time_millis
33.78582000732422
wall_clock_time_millis
33.9200496673584
wall_clock_time_millis
34.08551216125488
wall_clock_time_millis_testing
2.6497840881347656
wall_clock_time_millis_testing
2.5572776794433594
wall_clock_time_millis_testing
2.557516098022461
wall_clock_time_millis_testing
2.7022361755371094
wall_clock_time_millis_testing
2.621173858642578
wall_clock_time_millis_testing
2.6578903198242188
wall_clock_time_millis_testing
2.5625228881835938
wall_clock_time_millis_testing
2.610445022583008
wall_clock_time_millis_testing
2.703428268432617
wall_clock_time_millis_testing
2.5625228881835938
wall_clock_time_millis_training
30.071020126342773
wall_clock_time_millis_training
31.101465225219727
wall_clock_time_millis_training
30.478954315185547
wall_clock_time_millis_training
31.488656997680664
wall_clock_time_millis_training
31.472206115722656
wall_clock_time_millis_training
31.57806396484375
wall_clock_time_millis_training
30.902385711669922
wall_clock_time_millis_training
31.17537498474121
wall_clock_time_millis_training
31.21662139892578
wall_clock_time_millis_training
31.52298927307129