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
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20
1k
n2
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perc
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143
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Q_test
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0
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84.2
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0
99.4
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0
106
WLg_PetoPrentice_test
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0
71.9
WLg_Prentice_test
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0
71.6
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7,649
train
H1
H16
300
300
0
0
0
0.362679
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7,649
train
H0
H16
500
500
0
0
0
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7,649
train
H1
H16
500
500
0
0
0
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1.406157
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9.124049
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4.794001
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7,649
train
H0
H16
1,000
1,000
0
0
0
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7,649
train
H1
H16
1,000
1,000
0
0
0
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7,649
train
H0
H16
20
20
10
5
10
1.622264
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3.504565
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2.461355
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7,649
train
H1
H16
20
20
10
5
10
0.028898
0
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3.301967
3.546193
3.1396
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0
1.955391
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7,649
train
H0
H16
30
30
10
10
16.666667
0.704218
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7,649
train
H1
H16
30
30
10
10
10
-0.246042
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7,649
train
H0
H16
50
50
10
4
10
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0.313383
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2.803297
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3.108774
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7,649
train
H1
H16
50
50
10
16
12
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1.34936
0.489758
0.487689
5.075629
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7,649
train
H0
H16
75
75
10
10.666667
9.333333
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0.073501
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1.928489
4.882556
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0.665589
0.180602
0.449119
0.068955
0.005402
1.718911
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7,649
train
H1
H16
75
75
10
12
12
-1.180192
1.236363
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0.399527
3.274064
4.614609
3.773931
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1.236363
0.151531
0.159622
0.809005
1.532802
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7,649
train
H0
H16
100
100
10
9
11
0.53341
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0.913005
0.972201
0.942776
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0.839851
0.586711
0.700843
0.483438
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7,649
train
H1
H16
100
100
10
13
7
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1.106515
1.103971
2.28682
3.086524
2.617679
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1.536898
0.120444
1.218751
1.859252
2.36532
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7,649
train
H0
H16
150
150
10
5.333333
7.333333
0.879056
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1.198408
3.035643
1.227033
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1.091707
0.381291
1.190163
1.149221
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7,649
train
H1
H16
150
150
10
9.333333
5.333333
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1.099652
0.367706
0.366369
2.426244
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2.747423
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0.253166
0.134226
0.649585
1.209523
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7,649
train
H0
H16
200
200
10
14
6
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2.460455
3.06496
3.113325
10.713671
13.943085
10.159805
3.113325
3.06496
0.002984
9.692791
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6.067732
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7,649
train
H1
H16
200
200
10
11
6.5
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1.243841
1.645007
1.647287
2.961251
3.031361
2.919066
1.647287
1.645007
0.211095
2.713553
1.998563
1.546969
2.774057
2.868473
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7,649
train
H0
H16
300
300
10
10
8.666667
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0.599119
1.097222
1.098067
1.628777
2.21425
1.837061
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1.097222
0.399105
1.205751
0.728843
0.358879
1.879252
1.906307
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7,649
train
H1
H16
300
300
10
8.333333
13
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1.201186
0.580837
0.58065
1.900246
2.425024
2.453911
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1.201186
0.225408
0.337155
0.850648
1.44385
0.059413
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7,649
train
H0
H16
500
500
10
11.6
11
1.705814
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4.310931
4.376701
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1.705814
1.748939
0.077966
0.937077
2.242266
3.061702
0.012203
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1.762611
7,649
train
H1
H16
500
500
10
10.2
9.8
-0.448914
0.508251
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8.083261
8.334319
7.708115
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0.817276
0.021194
0.673061
0.00033
0.258324
4.266635
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7,649
train
H0
H16
1,000
1,000
10
9.8
8.7
-0.172799
0.126686
0.950856
0.950602
2.776921
3.062513
3.067397
0.950602
0.950856
0.215736
0.903644
0.220223
0.016047
2.491549
2.470435
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7,649
train
H1
H16
1,000
1,000
10
10.1
8.7
-0.549042
0.546773
0.415972
0.415726
0.193819
2.001658
0.327269
0.415726
0.546773
0.572063
0.172828
0.184026
0.298928
0.028273
0.019675
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7,649
train
H0
H16
20
20
20
15
45
1.307689
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4.601654
5.022088
4.493915
1.307689
1.820622
0.10572
3.274643
2.190969
1.462224
4.007696
3.837944
1.31302
7,649
train
H1
H16
20
20
20
20
15
-0.242385
0.227632
0.175421
0.172396
0.06852
0.05699
0.074824
0.172396
0.227632
0.821585
0.02972
0.036544
0.051313
0.024699
0.028942
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7,649
train
H0
H16
30
30
20
26.666667
20
0.734545
-0.801901
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0.832418
2.238423
0.96455
0.734545
0.801901
0.406869
0.188985
0.423561
0.642279
0.013706
0.030709
0.829416
7,649
train
H1
H16
30
30
20
20
16.666667
0.490248
-0.386813
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4.967288
7.031266
4.564836
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1.112641
0.070908
1.348418
0.478145
0.149343
3.467763
3.247763
0.408839
7,649
train
H0
H16
50
50
20
10
14
0.515039
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0.58421
1.413533
0.456705
0.515039
0.53418
0.587497
0.077265
0.229362
0.284364
0.017114
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0.542466
7,649
train
H1
H16
50
50
20
18
18
0.169418
-0.114726
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0.407562
0.881381
0.48812
0.169418
0.433924
0.783441
0.186997
0.079066
0.013117
0.320481
0.338468
0.117272
7,649
train
H0
H16
75
75
20
26.666667
13.333333
-1.971749
2.016693
1.618735
1.619959
3.342043
16.199784
4.15397
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2.016693
0.001032
2.624266
3.099739
4.081809
0.472048
0.346209
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7,649
train
H1
H16
75
75
20
18.666667
24
0.634091
-0.425093
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2.916865
5.070219
3.435533
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1.265581
0.166727
1.611479
0.683842
0.180616
3.198782
3.36846
0.439307
7,649
train
H0
H16
100
100
20
22
21
-0.478315
0.383856
0.729211
0.72694
0.635511
2.933849
0.759355
0.72694
0.729211
0.401937
0.528442
0.326233
0.147167
0.830884
1.037284
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7,649
train
H1
H16
100
100
20
20
21
0.370736
-0.242951
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3.707356
6.502648
4.244449
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1.113598
0.089558
1.258939
0.426447
0.058986
3.415291
3.628874
0.244779
7,649
train
H0
H16
150
150
20
21.333333
20
0.377391
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0.04664
0.046465
0.979905
1.551522
1.125512
0.046465
0.448481
0.569637
0.002159
0.059225
0.201101
0.358879
0.382037
0.452654
7,649
train
H1
H16
150
150
20
19.333333
20
0.729517
-0.708954
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0.67909
0.990053
0.683121
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0.824712
0.473343
0.678971
0.635942
0.502273
0.490374
0.533262
0.71705
7,649
train
H0
H16
200
200
20
17.5
17
1.462187
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2.500192
6.006925
2.172644
1.462187
1.459674
0.111274
1.981565
2.530152
2.133269
0.98191
1.165944
1.473388
7,649
train
H1
H16
200
200
20
18.5
18.5
0.218657
-0.172995
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0.774592
1.608087
0.920574
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0.573948
0.631102
0.329603
0.138717
0.029916
0.724844
0.766867
0.174257
7,649
train
H0
H16
300
300
20
18.666667
16.666667
-0.224593
0.259685
0.036699
0.036635
0.083086
1.503289
0.212969
0.036635
0.259685
0.681512
0.001342
0.015231
0.067396
0.03302
0.042124
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7,649
train
H1
H16
300
300
20
19.666667
20.666667
0.829158
-0.857557
-0.657563
-0.658098
0.678935
1.179557
0.75124
0.829158
0.857557
0.383614
0.433093
0.612216
0.735083
0.061344
0.059748
0.871256
7,649
train
H0
H16
500
500
20
20
22.2
0.34327
-0.286774
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-0.546565
0.398259
1.413786
0.444187
-0.546565
0.547284
0.702307
0.298734
0.154999
0.082214
0.4204
0.454263
0.292257
7,649
train
H1
H16
500
500
20
22.6
19.6
-1.671433
1.77978
0.902263
0.901969
4.51678
7.103332
5.213183
-1.671433
1.77978
0.068676
0.813547
2.128461
3.168021
0.132974
0.153935
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7,649
train
H0
H16
1,000
1,000
20
21.1
18.6
-0.531733
0.538666
0.45307
0.453122
0.359231
0.460083
0.289147
-0.531733
0.538666
0.584572
0.20532
0.328189
0.290122
0.05773
0.053364
-0.546719
7,649
train
H1
H16
1,000
1,000
20
20
19.3
-0.788369
0.897703
-0.154826
-0.15513
5.348511
5.102902
5.30154
-0.15513
0.897703
0.070597
0.024065
0.258284
0.805922
1.787654
1.736135
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