Classification statistics
|
framework
|
AutoGluon
|
FEDOT
|
H2O
|
LAMA
|
Dataset name
|
Metric name
|
|
|
|
|
APSFailure
|
auc
|
0.990
|
0.991
|
0.992
|
0.992
|
Amazon_employee_access
|
auc
|
0.857
|
0.865
|
0.873
|
0.879
|
Australian
|
auc
|
0.940
|
0.939
|
0.938
|
0.945
|
Covertype
|
neg_logloss
|
-0.071
|
-0.117
|
-0.265
|
nan
|
Fashion-MNIST
|
neg_logloss
|
-0.329
|
-0.373
|
-0.380
|
-0.248
|
Jannis
|
neg_logloss
|
-0.728
|
-0.737
|
-0.691
|
-0.664
|
KDDCup09_appetency
|
auc
|
0.804
|
0.822
|
0.829
|
0.850
|
MiniBooNE
|
auc
|
0.982
|
0.981
|
nan
|
0.988
|
Shuttle
|
neg_logloss
|
-0.001
|
-0.001
|
-0.000
|
-0.001
|
Volkert
|
neg_logloss
|
-0.917
|
-1.097
|
-0.976
|
-0.806
|
adult
|
auc
|
0.910
|
0.925
|
0.931
|
0.932
|
bank-marketing
|
auc
|
0.931
|
0.935
|
0.939
|
0.940
|
blood-transfusion
|
auc
|
0.690
|
0.759
|
0.754
|
0.750
|
car
|
neg_logloss
|
-0.117
|
-0.011
|
-0.003
|
-0.002
|
christine
|
auc
|
0.804
|
0.812
|
0.815
|
0.830
|
cnae-9
|
neg_logloss
|
-0.332
|
-0.211
|
-0.262
|
-0.156
|
connect-4
|
neg_logloss
|
-0.502
|
-0.456
|
-0.338
|
-0.337
|
credit-g
|
auc
|
0.795
|
0.778
|
0.798
|
0.796
|
dilbert
|
neg_logloss
|
-0.148
|
-0.159
|
-0.103
|
-0.033
|
fabert
|
neg_logloss
|
-0.788
|
-0.895
|
-0.792
|
-0.766
|
guillermo
|
auc
|
0.900
|
0.891
|
nan
|
0.926
|
jasmine
|
auc
|
0.883
|
0.888
|
0.888
|
0.880
|
jungle chess
|
neg_logloss
|
-0.431
|
-0.193
|
-0.240
|
-0.149
|
kc1
|
auc
|
0.822
|
0.843
|
nan
|
0.831
|
kr-vs-kp
|
auc
|
0.999
|
1.000
|
1.000
|
1.000
|
mfeat-factors
|
neg_logloss
|
-0.161
|
-0.094
|
-0.093
|
-0.082
|
nomao
|
auc
|
0.995
|
0.994
|
0.996
|
0.997
|
numerai28_6
|
auc
|
0.517
|
0.529
|
0.531
|
0.531
|
phoneme
|
auc
|
0.965
|
0.965
|
0.968
|
0.965
|
segment
|
neg_logloss
|
-0.094
|
-0.062
|
-0.060
|
-0.061
|
sylvine
|
auc
|
0.985
|
0.988
|
0.989
|
0.988
|
vehicle
|
neg_logloss
|
-0.515
|
-0.354
|
-0.331
|
-0.404
|