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
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Hi
stringclasses
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1k
n2
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MIN3_test
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84.2
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99.4
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WLg_Prentice_test
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7,645
train
H1
H17
300
300
20
20
20.666667
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7,645
train
H0
H17
500
500
20
18.4
18.2
0.155998
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7,645
train
H1
H17
500
500
20
20.8
22.8
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7,645
train
H0
H17
1,000
1,000
20
20.5
21.6
0.782111
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0.609235
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0.794664
0.395469
0.609171
0.590609
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7,645
train
H1
H17
1,000
1,000
20
19.7
21.1
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18.187478
18.694259
17.825187
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7,645
train
H0
H17
20
20
30
30
35
1.082191
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2.523769
3.880103
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7,645
train
H1
H17
20
20
30
30
40
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7,645
train
H0
H17
30
30
30
16.666667
40
1.202426
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1.440109
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7,645
train
H1
H17
30
30
30
26.666667
40
0.357308
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7,645
train
H0
H17
50
50
30
36
30
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1.044411
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7,645
train
H1
H17
50
50
30
32
26
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1.060423
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7,645
train
H0
H17
75
75
30
26.666667
37.333333
1.75189
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3.186313
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1.75189
1.769698
0.082797
3.109565
3.14681
2.834433
1.61834
1.609185
1.734683
7,645
train
H1
H17
75
75
30
28
37.333333
0.270042
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1.404239
3.171576
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0.680283
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0.456916
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1.196137
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7,645
train
H0
H17
100
100
30
27
40
0.401108
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0.622532
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0.729636
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7,645
train
H1
H17
100
100
30
35
33
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2.113882
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1.927315
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0.210413
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1.26614
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7,645
train
H0
H17
150
150
30
36
30.666667
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0.407528
0.166305
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0.171655
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0.67752
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0.163513
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7,645
train
H1
H17
150
150
30
32
30.666667
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2.029574
1.336004
1.33805
4.858256
6.352636
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2.029574
0.03771
1.790377
3.156656
4.130007
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7,645
train
H0
H17
200
200
30
26
29.5
1.066457
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1.301522
1.47025
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7,645
train
H1
H17
200
200
30
29.5
28
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1.633179
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6.385433
6.753462
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0.01605
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4.433846
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7,645
train
H0
H17
300
300
30
27.666667
26.333333
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1.697411
1.84008
1.848508
3.495207
3.679402
3.451964
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1.84008
0.081571
3.416984
3.430528
2.886248
2.155393
2.174237
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7,645
train
H1
H17
300
300
30
25
29.333333
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0.530017
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3.01887
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3.041873
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0.530017
0.218507
0.069394
0.05716
0.281046
1.26146
1.227495
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7,645
train
H0
H17
500
500
30
29.8
26.6
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1.324049
1.383797
1.382502
2.144327
4.721707
1.994741
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1.383797
0.174269
1.911311
2.139594
1.753254
1.040101
1.151733
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7,645
train
H1
H17
500
500
30
31.8
25
-3.658221
3.650591
3.25902
3.265743
13.353143
12.94881
13.571485
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3.650591
0.000194
10.665076
12.570293
13.36486
3.122992
3.327786
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7,645
train
H0
H17
1,000
1,000
30
32.1
30.3
-0.70973
0.699133
0.701378
0.700899
0.492727
1.232341
0.515635
0.700899
0.701378
0.47306
0.491259
0.442591
0.488734
0.272925
0.253697
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7,645
train
H1
H17
1,000
1,000
30
29.9
31
-2.217718
2.578228
0.522519
0.522342
23.575146
22.949965
23.499855
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2.578228
0.000008
0.272842
3.526748
6.651719
5.0844
5.062204
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7,645
train
H0
H17
20
20
40
45
50
0.364208
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1.742727
3.231936
1.833272
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0.665119
0.357229
0.433552
0.158657
0.018572
1.02428
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0.179567
7,645
train
H1
H17
20
20
40
50
40
-0.879773
0.97956
0.64539
0.635951
1.401918
4.852606
1.548739
0.635951
0.97956
0.182914
0.404433
0.614901
0.961277
0.000821
0.012507
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7,645
train
H0
H17
30
30
40
50
43.333333
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0.471408
0.44078
0.43697
0.24433
0.27958
0.23986
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0.471408
0.622232
0.190943
0.227521
0.221385
0.174587
0.179812
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7,645
train
H1
H17
30
30
40
26.666667
23.333333
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0.569408
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0.94838
5.403858
1.433671
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0.569408
0.144503
0.001895
0.056625
0.324319
0.398644
0.573042
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7,645
train
H0
H17
50
50
40
40
40
0.305931
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1.748516
2.149821
1.866501
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0.708674
0.393273
0.494945
0.118089
0.00542
1.314016
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0.093799
7,645
train
H1
H17
50
50
40
38
38
-0.492479
0.57035
0.250068
0.247614
0.56842
2.607103
0.748701
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0.57035
0.456246
0.061313
0.148476
0.324961
0.019495
0.054086
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7,645
train
H0
H17
75
75
40
36
41.333333
1.059281
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1.07353
2.034843
1.122733
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1.018266
0.297613
1.010313
0.95169
1.036739
0.344158
0.315374
1.041567
7,645
train
H1
H17
75
75
40
50.666667
40
-1.320955
1.406581
1.095737
1.091758
2.051783
2.206525
2.116058
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1.406581
0.143982
1.191935
1.65687
1.977493
0.191268
0.21205
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7,645
train
H0
H17
100
100
40
35
42
1.688328
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2.943341
3.077623
2.92321
1.688328
1.680706
0.082645
2.844968
3.012379
2.758918
1.485388
1.519384
1.735542
7,645
train
H1
H17
100
100
40
45
48
-0.055599
0.504218
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6.606361
6.664221
6.51331
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0.63461
0.038517
0.411323
0.004365
0.254149
3.637441
3.502286
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7,645
train
H0
H17
150
150
40
38.666667
40.666667
-0.890425
0.751588
1.097553
1.104312
1.403076
1.967637
1.470516
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1.097553
0.435025
1.219504
0.898217
0.566065
1.606472
1.626693
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7,645
train
H1
H17
150
150
40
36.666667
38.666667
0.489763
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1.567114
2.037476
1.429959
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0.813987
0.489202
0.663436
0.255779
0.146432
1.306838
1.219522
0.398989
7,645
train
H0
H17
200
200
40
45
32.5
-1.561855
1.429561
1.693039
1.692551
2.864751
4.275832
2.881671
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1.693039
0.13953
2.864727
2.653771
2.04306
2.385749
2.554682
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7,645
train
H1
H17
200
200
40
44
36
-2.582884
2.666082
2.419495
2.421688
6.325983
12.672204
6.717097
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2.666082
0.005402
5.864571
6.387259
7.138772
2.206262
1.994624
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7,645
train
H0
H17
300
300
40
42.333333
45
0.90023
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1.553806
2.610888
1.760422
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1.076036
0.261123
0.309552
0.742151
1.157288
0.052426
0.056737
1.123742
7,645
train
H1
H17
300
300
40
41.666667
40.333333
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2.965584
2.096155
2.106134
11.128763
11.595226
11.519417
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2.965584
0.002334
4.435802
7.108284
8.840279
0.036366
0.045719
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7,645
train
H0
H17
500
500
40
38.6
39
-1.383476
1.314909
1.509424
1.517217
2.349354
2.394736
2.338055
1.517217
1.509424
0.175798
2.301947
1.946845
1.730248
1.963587
1.980989
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7,645
train
H1
H17
500
500
40
44.4
41.8
-2.915143
3.098714
2.401899
2.410161
9.899287
13.122981
10.405029
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3.098714
0.001332
5.808877
7.905068
9.628356
0.637592
0.638787
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7,645
train
H0
H17
1,000
1,000
40
38.9
40.2
-0.021185
0.140084
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0.399442
1.134729
0.525038
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0.207837
0.768698
0.043151
0.003007
0.019621
0.281874
0.276311
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7,645
train
H1
H17
1,000
1,000
40
42.5
38.2
-5.561411
5.840466
4.515341
4.540069
36.402693
40.154995
37.798645
-5.561411
5.840466
0
20.612224
28.891366
34.260012
1.727473
1.77033
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