Datasets:
pfilonenko
/
ML_for_TwoSampleTesting

Dataset card Data Studio Files
xet
Community
1
iter
int64
0
7.65k
sample
stringclasses
1 value
H0_H1
stringclasses
2 values
Hi
stringclasses
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n1
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1k
n2
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143
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Q_test
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0
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MIN3_test
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0
1
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84.2
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0
99.4
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0
106
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0
71.9
WLg_Prentice_test
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0
71.6
WKM_test
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7
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train
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train
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train
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0.109197
0.062591
0.044944
0.136608
0.131995
0.217075
7
train
H0
H04
500
500
50
50.8
51
-0.975622
1.105634
0.704173
0.704717
1.751348
1.894244
1.816687
-0.975622
1.105634
0.250721
0.496627
0.907119
1.223024
0.001279
0.000933
-1.148599
7
train
H1
H04
500
500
50
51.6
49.6
-2.353216
2.324481
2.274767
2.289696
5.624231
6.307298
5.563982
-2.353216
2.324481
0.016177
5.242708
5.695801
5.413759
2.523809
2.672782
-2.404907
7
train
H0
H04
1,000
1,000
50
51.3
49.8
-0.820183
0.966256
0.542364
0.542214
1.618884
1.678784
1.586337
0.542214
0.966256
0.314425
0.293996
0.72447
0.933581
0.030479
0.030646
-1.005981
7
train
H1
H04
1,000
1,000
50
50.5
50.7
-2.105172
2.160095
1.826767
1.832283
5.222806
6.030456
5.073079
-2.105172
2.160095
0.024437
3.357261
4.526292
4.670325
0.60339
0.621055
-2.250194
7
train
H0
H05
20
20
0
0
0
0.297551
-0.297551
-0.534686
-0.522412
0.429134
0.499448
0.399978
-0.522412
0.534686
0.763154
0.272914
0.145987
0.087665
0.260477
0.221068
0.301342
7
train
H1
H05
20
20
0
0
0
0.811503
-0.811503
0.180468
0.181321
5.374553
5.56089
5.104489
0.811503
0.811503
0.077907
0.032877
0.176642
0.657654
1.605686
1.38973
0.821841
7
train
H0
H05
30
30
0
0
0
1.123616
-1.123616
-0.472347
-0.47745
3.699604
8.722696
2.635295
-0.47745
1.123616
0.033214
0.227958
0.961232
1.264448
0.103401
0.033105
1.133098
7
train
H1
H05
30
30
0
0
0
0.975772
-0.975772
-0.929105
-0.926832
1.13606
2.901276
0.969651
-0.926832
0.975772
0.325112
0.859018
1.071666
0.950728
0.339166
0.506774
0.984007
7
train
H0
H05
50
50
0
0
0
1.116799
-1.116799
-1.381217
-1.396603
2.245972
5.594832
2.026172
1.116799
1.381217
0.133075
1.9505
1.40971
1.247694
1.660565
1.510986
1.122425
7
train
H1
H05
50
50
0
0
0
1.206418
-1.206418
-1.41266
-1.415801
2.004806
2.064952
2.011331
1.206418
1.41266
0.225322
2.004492
1.798337
1.456218
1.482903
1.531443
1.212496
7
train
H0
H05
75
75
0
0
0
-0.080813
0.080813
-0.925117
-0.932997
4.656775
4.56269
4.623134
-0.932997
0.925117
0.099106
0.870483
0.10131
0.006522
3.109024
2.993648
-0.080541
7
train
H1
H05
75
75
0
0
0
1.129498
-1.129498
-1.082414
-1.078908
1.263567
2.127012
1.311623
-1.078908
1.129498
0.260292
1.164042
1.288468
1.276153
0.503418
0.457338
1.125701
7
train
H0
H05
100
100
0
0
0
-1.33409
1.33409
1.370152
1.369943
1.891455
2.167337
1.956846
-1.33409
1.370152
0.18108
1.876744
1.796221
1.782007
1.135887
1.116359
-1.337438
7
train
H1
H05
100
100
0
0
0
1.940051
-1.940051
-1.264685
-1.270801
5.667624
7.293823
4.560662
-1.270801
1.940051
0.051785
1.614935
3.368397
3.778992
0.092702
0.159172
1.944919
7
train
H0
H05
150
150
0
0
0
-1.603996
1.603996
1.298576
1.295436
2.672133
2.672708
2.616737
-1.603996
1.603996
0.108126
1.678156
2.374291
2.575399
0.408634
0.48263
-1.606676
7
train
H1
H05
150
150
0
0
0
1.381699
-1.381699
-1.275931
-1.273945
1.736876
2.359861
1.930106
-1.273945
1.381699
0.166356
1.622937
1.732506
1.909768
0.644929
0.615032
1.384008
7
train
H0
H05
200
200
0
0
0
0.373656
-0.373656
0.808752
0.810779
5.07473
4.966205
5.58948
0.373656
0.808752
0.061131
0.657363
0.011359
0.139599
3.328159
3.264262
0.374124
7
train
H1
H05
200
200
0
0
0
1.819844
-1.819844
-0.568179
-0.567326
5.74646
8.420962
7.565874
1.819844
1.819844
0.022756
0.321858
1.683901
3.31977
0.661595
0.713783
1.822123
7
train
H0
H05
300
300
0
0
0
0.377752
-0.377752
-0.315631
-0.314706
0.145826
0.489261
0.143333
0.377752
0.377752
0.705381
0.09904
0.122039
0.142647
0.021984
0.032061
0.378067
7
train
H1
H05
300
300
0
0
0
0.770576
-0.770576
0.158619
0.158399
2.26718
5.553168
3.388237
0.770576
0.770576
0.135493
0.02509
0.13308
0.593817
1.110236
1.20231
0.771219
7
train
H0
H05
500
500
0
0
0
-0.095256
0.095256
-0.331337
-0.330906
0.910299
1.080441
0.701137
-0.095256
0.331337
0.704288
0.109499
0.000174
0.009071
0.434642
0.410851
-0.095304
7
train
H1
H05
500
500
0
0
0
4.980252
-4.980252
-3.931904
-3.962609
23.599001
23.442999
25.582225
4.980252
4.980252
0.000001
15.702268
21.774896
24.977328
3.957454
4.097412
4.982744
7
train
H0
H05
1,000
1,000
0
0
0
-2.687721
2.687721
1.601469
1.602097
9.512679
9.419097
9.373324
-2.687721
2.687721
0.00718
2.566715
5.687301
7.231334
0.000756
0.002029
-2.688393
7
train
H1
H05
1,000
1,000
0
0
0
4.601271
-4.601271
-3.555124
-3.56486
20.940992
20.054991
21.989014
4.601271
4.601271
0.000004
12.708226
18.521326
21.233844
2.725994
2.812137
4.602422
7
train
H0
H05
20
20
10
5
10
-0.637549
0.679407
0.204437
0.199445
1.130873
1.161168
1.080886
-0.637549
0.679407
0.486691
0.039778
0.263121
0.459346
0.090371
0.042887
-0.695582
7
train
H1
H05
20
20
10
5
10
2.874379
-2.863045
-2.739015
-3.02627
9.18426
12.870576
9.251884
-3.02627
2.863045
0.003371
9.158311
8.895373
8.625073
5.50166
5.412755
2.931751
7
train
H0
H05
30
30
10
3.333333
10
-1.214533
1.208537
1.048334
1.046287
1.315805
1.885448
1.492306
-1.214533
1.208537
0.220352
1.094716
1.254103
1.465871
0.389979
0.361305
-1.225592
7
train
H1
H05
30
30
10
16.666667
26.666667
1.299793
-1.21142
-1.471376
-1.510362
2.591977
8.428858
2.436819
-1.510362
1.471376
0.037932
2.281192
1.68606
1.470275
2.182287
2.051138
1.193129
7
train
H0
H05
50
50
10
12
16
-0.392092
0.392137
0.314096
0.313188
0.249828
0.848228
0.165285
-0.392092
0.392137
0.694124
0.098087
0.173578
0.153869
0.020973
0.031764
-0.393264
7
train
H1
H05
50
50
10
10
10
0.757517
-0.772145
-0.551535
-0.551756
0.938655
3.883486
0.673077
-0.551756
0.772145
0.274323
0.304435
0.591773
0.595619
0.014842
0.048544
0.78214
7
train
H0
H05
75
75
10
8
13.333333
1.253392
-1.222966
-1.544554
-1.550633
2.408198
5.235616
2.512177
-1.550633
1.544554
0.155335
2.404464
2.163524
1.495945
2.15141
2.482298
1.230139
7
train
H1
H05
75
75
10
13.333333
6.666667
0.179728
-0.207092
0.302486
0.300682
1.487075
2.70337
1.115899
0.179728
0.302486
0.439655
0.090409
0.005378
0.042799
0.674573
0.553393
0.203891
7
train
H0
H05
100
100
10
11
10
1.635628
-1.574514
-2.133311
-2.190306
5.611244
5.724971
5.538428
-2.190306
2.133311
0.062711
4.79744
3.411787
2.486156
5.166267
5.181456
1.57993
7
train
H1
H05
100
100
10
11
7
1.238835
-1.215049
-1.263634
-1.273923
1.853137
4.011319
1.673702
-1.273923
1.263634
0.217945
1.622879
1.805445
1.478468
0.926823
1.115898
1.23201
7
train
H0
H05
150
150
10
14
8.666667
-0.221178
0.191427
0.497919
0.4964
0.444404
0.38032
0.494294
-0.221178
0.497919
0.781026
0.246413
0.119871
0.036618
0.493431
0.476944
-0.193408
7
train
H1
H05
150
150
10
8.666667
6.666667
2.420821
-2.413954
-2.47347
-2.523722
6.374701
10.898664
6.499106
2.420821
2.47347
0.012287
6.369175
5.975687
5.857362
3.886765
3.762561
2.435961
7
train
H0
H05
200
200
10
11
7.5
0.834853
-0.845013
-0.620681
-0.621116
0.574855
2.667527
0.780371
0.834853
0.845013
0.395552
0.385785
0.517983
0.714054
0.03861
0.034367
0.849592
7
train
H1
H05
200
200
10
7.5
12
0.707713
-0.682001
-1.348132
-1.361116
4.074116
10.00024
3.261036
0.707713
1.348132
0.018564
1.852637
0.782672
0.464752
3.032737
2.897387
0.680118
7
train
H0
H05
300
300
10
8
13
0.899233
-0.88959
-0.878608
-0.876896
0.867472
0.901235
0.836093
0.899233
0.88959
0.368895
0.768947
0.869624
0.791014
0.355737
0.35028
0.898544
7
train
H1
H05
300
300
10
9.666667
12
2.156287
-2.166294
-1.781793
-1.781445
4.613442
4.518058
4.759948
2.156287
2.166294
0.028778
3.173547
4.257749
4.701386
0.792073
0.839332
2.186514
7
train
H0
H05
500
500
10
12.2
7.4
-1.506076
1.50316
1.503757
1.502723
2.504728
2.649726
2.393641
-1.506076
1.503757
0.130199
2.258175
2.594152
2.260264
1.18626
1.198003
-1.513316
7
train
H1
H05
500
500
10
11.4
11.8
1.821796
-1.831334
-1.361019
-1.360166
3.525753
3.724875
3.690187
-1.360166
1.831334
0.064875
1.850051
2.839811
3.355638
0.229388
0.217678
1.846119
7
train
H0
H05
1,000
1,000
10
9.5
9.6
-0.69648
0.686584
0.723534
0.723491
0.60968
1.865475
0.536537
-0.69648
0.723534
0.489676
0.523439
0.599301
0.471347
0.333181
0.353916
-0.690824
7
train
H1
H05
1,000
1,000
10
10.4
9.8
2.572965
-2.578941
-2.110632
-2.112325
6.250969
6.062955
6.790469
2.572965
2.578941
0.009409
4.461918
5.776692
6.657451
1.093548
1.140343
2.596836