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
27 values
n1
int64
20
1k
n2
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perc
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143
BN_SCE_test
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Q_test
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MAX_Value_test
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MIN3_test
float64
0
1
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84.2
WLg_TaroneWare_test
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99.4
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WLg_PetoPrentice_test
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71.9
WLg_Prentice_test
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71.6
WKM_test
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7,647
train
H1
H14
300
300
10
11
8.666667
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0.845854
1.275401
1.279149
2.093926
2.132002
2.045586
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1.275401
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1.636223
1.061091
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2.127252
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7,647
train
H0
H14
500
500
10
10
9.4
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0.21684
0.747923
0.747857
1.240093
1.442556
1.428343
0.747857
0.747923
0.489598
0.55929
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1.293742
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7,647
train
H1
H14
500
500
10
9
9.6
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0.352264
0.721447
0.721219
0.623707
3.10079
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0.721219
0.721447
0.376345
0.520157
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0.124091
0.888573
0.939058
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7,647
train
H0
H14
1,000
1,000
10
9.4
11.5
1.2306
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3.383953
3.576595
3.536961
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1.733798
0.170592
3.007168
2.180925
1.436054
3.425239
3.428821
1.205152
7,647
train
H1
H14
1,000
1,000
10
10
8.1
-0.623284
0.561353
1.71636
1.720128
8.012969
9.085424
7.052525
1.720128
1.71636
0.028176
2.958841
0.883989
0.315077
6.351119
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7,647
train
H0
H14
20
20
20
20
25
0.631486
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1.023626
2.227839
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0.51998
0.11962
0.307435
0.401547
0.062501
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7,647
train
H1
H14
20
20
20
15
5
-1.07023
1.003313
1.540862
1.589205
3.475832
4.976521
3.679307
1.589205
1.540862
0.158872
2.525574
1.718792
1.004922
4.183699
4.340199
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7,647
train
H0
H14
30
30
20
20
6.666667
0.87939
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3.159546
3.381978
3.203431
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1.270433
0.20155
1.818341
1.160596
0.684668
2.792348
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0.782175
7,647
train
H1
H14
30
30
20
16.666667
26.666667
0.916579
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2.348622
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2.477919
0.916579
1.004105
0.289685
0.127738
0.573958
1.005638
0.279897
0.213032
1.031531
7,647
train
H0
H14
50
50
20
26
20
-0.597628
0.517283
1.075684
1.088271
2.651003
2.861098
2.737921
1.088271
1.075684
0.254371
1.184335
0.608001
0.266797
2.741744
2.759739
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7,647
train
H1
H14
50
50
20
20
16
-0.252385
0.293553
0.170476
0.168715
0.053345
0.750655
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0.168715
0.293553
0.767435
0.028465
0.057285
0.085876
0.007772
0.00082
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7,647
train
H0
H14
75
75
20
20
21.333333
0.626314
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0.402815
0.685664
0.409333
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0.630948
0.542049
0.39211
0.398061
0.363668
0.174408
0.136471
0.609718
7,647
train
H1
H14
75
75
20
28
14.666667
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1.453011
1.863153
1.879915
4.164674
8.889238
3.870947
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1.863153
0.0308
3.534079
2.487023
2.11159
3.784207
3.5948
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7,647
train
H0
H14
100
100
20
21
22
-0.253992
0.285614
0.260649
0.260327
0.076354
0.144934
0.069026
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0.285614
0.770991
0.06777
0.099527
0.081488
0.064191
0.067203
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7,647
train
H1
H14
100
100
20
17
21
0.343722
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0.195186
0.195044
1.618269
1.707129
1.746452
0.343722
0.41919
0.417602
0.038042
0.031305
0.175539
0.777007
0.750988
0.423563
7,647
train
H0
H14
150
150
20
21.333333
16.666667
-0.124284
0.136812
0.228915
0.228329
0.096728
0.087453
0.098743
0.228329
0.228915
0.890281
0.052134
0.033449
0.018697
0.12235
0.127689
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7,647
train
H1
H14
150
150
20
21.333333
25.333333
1.904321
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5.166141
8.282892
5.845994
1.904321
2.022185
0.039995
1.443463
2.897567
4.099851
0
0.002486
2.053803
7,647
train
H0
H14
200
200
20
20.5
23.5
1.335299
-1.343966
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1.97318
2.802068
1.799525
1.335299
1.343966
0.172384
1.630927
2.070114
1.807804
0.762115
0.852057
1.364582
7,647
train
H1
H14
200
200
20
27.5
18
-0.269835
0.054098
1.444276
1.445501
9.966827
10.438638
10.133498
1.445501
1.444276
0.006303
2.089473
0.367362
0.002926
7.217196
7.219067
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7,647
train
H0
H14
300
300
20
14.666667
21.333333
1.40113
-1.229531
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12.365038
14.580914
11.226766
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2.475932
0.002212
6.226337
2.740024
1.511944
10.745008
10.526968
1.244641
7,647
train
H1
H14
300
300
20
23.666667
18.666667
-1.76007
1.731548
1.746114
1.746935
3.117084
3.95665
3.201601
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1.746114
0.079537
3.051781
2.968234
3.000949
1.708496
1.723135
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7,647
train
H0
H14
500
500
20
17.6
20.6
0.564385
-0.57384
-0.263094
-0.263298
1.009769
3.102101
0.709975
-0.263298
0.57384
0.376149
0.069326
0.276279
0.329192
0.041733
0.032402
0.58284
7,647
train
H1
H14
500
500
20
19.2
20.4
-0.638866
0.639743
0.636633
0.636439
0.408164
1.025397
0.424452
-0.638866
0.639743
0.517349
0.405055
0.391314
0.409259
0.24735
0.233804
-0.647437
7,647
train
H0
H14
1,000
1,000
20
22.1
19.8
-1.215152
1.201343
1.084764
1.084216
1.512855
1.651155
1.482478
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1.201343
0.223675
1.175523
1.411358
1.443096
0.418918
0.434385
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7,647
train
H1
H14
1,000
1,000
20
21.9
19.8
-0.959931
0.857254
1.622455
1.623973
4.413109
4.342232
4.472636
1.623973
1.622455
0.106851
2.637288
1.398415
0.734849
4.458271
4.442957
-0.866937
7,647
train
H0
H14
20
20
30
35
20
-1.24278
1.253149
1.090663
1.0813
1.546379
2.444896
1.638815
1.0813
1.253149
0.199281
1.169211
1.423159
1.571429
0.443931
0.453068
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7,647
train
H1
H14
20
20
30
30
15
-0.522682
0.488748
0.499168
0.490361
0.241339
3.596839
0.273016
0.490361
0.499168
0.308418
0.240454
0.180244
0.23791
0.189327
0.10035
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7,647
train
H0
H14
30
30
30
26.666667
36.666667
0.610896
-0.598785
-0.824926
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0.909028
0.958315
0.945959
0.610896
0.824926
0.541036
0.683011
0.53041
0.360716
0.784737
0.780888
0.611247
7,647
train
H1
H14
30
30
30
23.333333
20
0.497349
-0.607064
0.00911
0.009019
2.131195
2.6464
1.909293
0.497349
0.607064
0.384948
0.000081
0.169825
0.367858
0.547073
0.408307
0.592341
7,647
train
H0
H14
50
50
30
38
32
-0.447321
0.372144
0.626409
0.622888
0.602764
0.630671
0.610599
0.622888
0.626409
0.699578
0.38799
0.234522
0.138066
0.806282
0.820631
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7,647
train
H1
H14
50
50
30
32
28
-1.361163
1.321456
1.437636
1.452466
2.109721
2.582054
2.11082
-1.361163
1.437636
0.174608
2.109657
2.044549
1.753162
1.793555
1.974054
-1.357546
7,647
train
H0
H14
75
75
30
29.333333
30.666667
-0.667462
0.700293
0.380876
0.37943
1.191058
2.852035
1.004959
0.37943
0.700293
0.415005
0.143967
0.412754
0.489757
0.019474
0.003546
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7,647
train
H1
H14
75
75
30
32
26.666667
-0.722155
0.67309
0.765516
0.760773
0.585167
1.539667
0.579689
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0.765516
0.494895
0.578775
0.438591
0.452892
0.478285
0.432374
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7,647
train
H0
H14
100
100
30
30
27
-0.40196
0.345915
0.653064
0.651949
0.83135
0.937907
0.787217
0.651949
0.653064
0.674618
0.425037
0.209953
0.11953
0.845581
0.849538
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7,647
train
H1
H14
100
100
30
27
36
1.465249
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-1.295878
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2.33847
3.128493
2.226916
1.465249
1.49815
0.127071
1.672699
2.216156
2.243788
0.475122
0.558072
1.525753
7,647
train
H0
H14
150
150
30
33.333333
32
0.853129
-0.812132
-0.713775
-0.71523
0.716543
1.886748
0.811143
0.853129
0.812132
0.409538
0.511554
0.530198
0.659649
0.082734
0.061847
0.824706
7,647
train
H1
H14
150
150
30
33.333333
34
-1.024718
1.058818
0.905289
0.906307
1.16505
1.823524
1.099946
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1.058818
0.280795
0.821393
1.101241
1.12266
0.294064
0.321363
-1.078535
7,647
train
H0
H14
200
200
30
28
29.5
0.413738
-0.292629
-0.858752
-0.861139
1.671595
3.641524
2.003735
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0.858752
0.302865
0.741561
0.362111
0.085653
1.662589
1.678981
0.300584
7,647
train
H1
H14
200
200
30
33.5
30.5
-0.615227
0.542363
0.893528
0.893463
1.40909
3.108268
1.262403
-0.615227
0.893528
0.375232
0.798275
0.4032
0.294029
1.356749
1.231603
-0.555459
7,647
train
H0
H14
300
300
30
30.333333
32.333333
0.62501
-0.760492
-0.048456
-0.048619
2.95855
2.897173
2.928991
-0.048619
0.760492
0.231195
0.002364
0.257339
0.578343
0.768485
0.745431
0.777709
7,647
train
H1
H14
300
300
30
30
31.333333
-0.145907
-0.015241
0.674143
0.67563
2.688464
2.827956
2.572626
0.67563
0.674143
0.276288
0.456477
0.055853
0.000232
1.85543
1.80746
0.01643
7,647
train
H0
H14
500
500
30
29.6
28.4
1.213037
-1.277708
-0.80984
-0.810164
2.615106
3.246556
2.3167
1.213037
1.277708
0.193581
0.656366
1.401311
1.632639
0.000128
0.000404
1.300059
7,647
train
H1
H14
500
500
30
29.8
33.6
0.336793
-0.265009
-0.475126
-0.475035
0.390553
0.802702
0.330217
-0.475035
0.475126
0.785752
0.225658
0.092236
0.070225
0.302701
0.301156
0.271831
7,647
train
H0
H14
1,000
1,000
30
30.9
29.4
-0.321837
0.39928
0.050433
0.050448
0.460405
1.434762
0.615272
-0.321837
0.39928
0.682986
0.002545
0.050028
0.159423
0.125838
0.130338
-0.408392
7,647
train
H1
H14
1,000
1,000
30
33.2
29.7
-1.331818
1.152625
1.86449
1.865325
4.570543
7.473685
4.994391
1.865325
1.86449
0.058238
3.479436
2.403077
1.328601
5.049204
5.050353
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