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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20
1k
n2
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0
1
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84.2
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99.4
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0
71.9
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0
71.6
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4.587283
9.758755
5.251242
-0.801241
1.680791
0.020732
0.641987
1.628057
2.830376
0.259138
0.28872
1.742846
8
train
H0
H18
500
500
50
49.6
47.2
-0.801658
0.816416
0.699813
0.699701
0.744953
0.902171
0.721996
0.699701
0.816416
0.395138
0.489581
0.646474
0.66638
0.125324
0.12546
-0.850336
8
train
H1
H18
500
500
50
49.4
55.6
3.636531
-3.840526
-3.191745
-3.210108
14.868649
16.892605
15.141977
3.636531
3.840526
0.000055
10.304792
13.106243
14.780765
2.404257
2.403214
4.033863
8
train
H0
H18
1,000
1,000
50
50.1
51.9
0.7533
-0.741341
-0.72538
-0.725037
0.618359
3.488559
0.567492
0.7533
0.741341
0.322249
0.525678
0.703343
0.549527
0.226383
0.233712
0.770455
8
train
H1
H18
1,000
1,000
50
48.6
51
4.469634
-5.02139
-3.342348
-3.356465
33.738129
33.67932
33.992069
4.469634
5.02139
0
11.26586
20.184722
25.299257
0.145792
0.157637
5.218245
8
train
H0
H19
20
20
0
0
0
0.405751
-0.405751
-0.402699
-0.395285
0.248157
2.067459
0.169617
-0.395285
0.405751
0.558524
0.15625
0.217701
0.163221
0.046869
0.113484
0.41092
8
train
H1
H19
20
20
0
0
0
-0.703302
0.703302
0.692247
0.678709
0.495498
0.731808
0.507618
-0.703302
0.703302
0.476303
0.460645
0.497903
0.491636
0.273771
0.261082
-0.712262
8
train
H0
H19
30
30
0
0
0
-0.739221
0.739221
0.657576
0.649372
0.445614
1.497032
0.544624
0.649372
0.739221
0.455994
0.421684
0.440961
0.544544
0.17333
0.130638
-0.74546
8
train
H1
H19
30
30
0
0
0
-1.596718
1.596718
0.598333
0.591508
4.930698
5.18065
5.468359
-1.596718
1.596718
0.064947
0.349881
1.469668
2.572279
0.531098
0.464522
-1.610193
8
train
H0
H19
50
50
0
0
0
2.095721
-2.095721
-1.210894
-1.218836
6.886798
7.436073
6.201551
2.095721
2.095721
0.03518
1.485561
3.479933
4.437104
0.004257
0.033169
2.106279
8
train
H1
H19
50
50
0
0
0
0.248178
-0.248178
-1.054591
-1.07683
2.44584
10.069223
3.655559
-1.07683
1.054591
0.017987
1.159563
0.473752
0.061555
3.122509
3.693962
0.249428
8
train
H0
H19
75
75
0
0
0
0.14847
-0.14847
-0.34563
-0.3446
0.404288
2.938116
0.221515
-0.3446
0.34563
0.401265
0.118749
0.030392
0.021982
0.179373
0.120896
0.147971
8
train
H1
H19
75
75
0
0
0
-1.276088
1.276088
1.630553
1.640836
2.839047
2.885729
2.817588
-1.276088
1.630553
0.203445
2.692342
2.092054
1.62866
2.696316
2.667221
-1.271799
8
train
H0
H19
100
100
0
0
0
-0.15882
0.15882
0.057315
0.05681
0.094782
0.272777
0.052211
0.05681
0.15882
0.873496
0.003227
0.022596
0.025172
0.001098
0.000042
-0.159219
8
train
H1
H19
100
100
0
0
0
-2.304116
2.304116
1.269034
1.266443
6.130794
9.742697
7.622335
-2.304116
2.304116
0.020885
1.603877
3.630107
5.347982
0.069626
0.093327
-2.309898
8
train
H0
H19
150
150
0
0
0
1.505493
-1.505493
-1.070715
-1.067859
2.331278
3.045968
2.508766
1.505493
1.505493
0.131552
1.140323
1.886773
2.268537
0.124598
0.114142
1.508008
8
train
H1
H19
150
150
0
0
0
-1.737107
1.737107
2.02193
2.046928
4.406335
10.414986
4.208413
-1.737107
2.02193
0.015349
4.189915
3.351125
3.022831
3.451615
3.298701
-1.74001
8
train
H0
H19
200
200
0
0
0
-1.127023
1.127023
1.950528
1.98053
6.878085
11.453035
5.677719
-1.127023
1.950528
0.009512
3.922499
1.925518
1.269918
5.791695
5.616784
-1.128435
8
train
H1
H19
200
200
0
0
0
-0.662548
0.662548
-0.522687
-0.523876
5.169156
5.105254
5.560235
-0.662548
0.662548
0.062031
0.274446
0.040497
0.438933
2.619
2.556166
-0.663378
8
train
H0
H19
300
300
0
0
0
1.038582
-1.038582
-0.75176
-0.749783
0.771023
1.791653
1.171851
1.038582
1.038582
0.298596
0.562174
0.748189
1.078705
0.065295
0.054112
1.039448
8
train
H1
H19
300
300
0
0
0
-1.772419
1.772419
0.340789
0.340805
6.473639
8.850115
9.050183
-1.772419
1.772419
0.010834
0.116148
1.337194
3.147082
1.590761
1.599268
-1.773898
8
train
H0
H19
500
500
0
0
0
0.924532
-0.924532
-0.912843
-0.911594
0.852805
1.749774
0.903194
-0.911594
0.924532
0.354969
0.831004
0.85945
0.854641
0.412914
0.382749
0.924994
8
train
H1
H19
500
500
0
0
0
-2.839727
2.839727
1.508642
1.512035
11.852146
11.306828
11.845264
-2.839727
2.839727
0.002678
2.286248
5.813177
8.0824
0.106824
0.079232
-2.841148
8
train
H0
H19
1,000
1,000
0
0
0
0.469598
-0.469598
-1.697794
-1.705284
8.53027
9.520217
7.176252
0.469598
1.697794
0.023117
2.907995
0.725142
0.220499
6.319729
6.229012
0.469715
8
train
H1
H19
1,000
1,000
0
0
0
-3.028768
3.028768
1.689614
1.688863
10.555955
10.462585
12.709821
-3.028768
3.028768
0.001738
2.85226
6.308688
9.185178
0.027227
0.022887
-3.029525
8
train
H0
H19
20
20
10
5
15
2.018732
-2.033802
-1.730302
-1.7236
3.986091
4.875898
4.207885
2.018732
2.033802
0.036277
2.970797
3.795226
4.158079
0.907427
0.932629
2.093811
8
train
H1
H19
20
20
10
0
10
1.582718
-1.546019
-1.389687
-1.402316
2.979608
5.894484
2.509991
-1.402316
1.546019
0.111873
1.966489
2.627876
2.393915
0.707104
1.083445
1.589829
8
train
H0
H19
30
30
10
6.666667
13.333333
0.877726
-0.91538
-0.385436
-0.384306
1.3736
2.779875
1.669096
0.877726
0.91538
0.352713
0.147691
0.478271
0.842315
0.097766
0.112132
0.92934
8
train
H1
H19
30
30
10
20
6.666667
-0.881684
0.853727
0.688262
0.683564
1.301355
6.392908
0.835437
-0.881684
0.853727
0.093983
0.467259
0.849564
0.75278
0.063201
0.198217
-0.913065
8
train
H0
H19
50
50
10
8
18
-0.88431
0.916834
0.106381
0.106311
3.762943
4.245053
3.295929
-0.88431
0.916834
0.192441
0.011302
0.456805
0.845149
0.940985
0.890176
-0.930341
8
train
H1
H19
50
50
10
18
18
-1.984769
2.087246
0.846501
0.846214
9.942581
9.862257
9.755217
-1.984769
2.087246
0.007615
0.716078
2.733751
4.400095
1.228721
1.090162
-2.147405
8
train
H0
H19
75
75
10
13.333333
10.666667
0.159451
-0.167163
-0.064491
-0.063963
0.058487
0.250036
0.055705
0.159451
0.167163
0.866859
0.004091
0.020367
0.027213
0.010174
0.019923
0.167649
8
train
H1
H19
75
75
10
4
10.666667
-0.041762
0.040898
-0.116138
-0.115541
0.015565
4.234193
0.1133
-0.115541
0.116138
0.237261
0.01335
0.019213
0.00167
0.055254
0.109245
-0.038124
8
train
H0
H19
100
100
10
7
10
0.368884
-0.399604
0.234422
0.233373
1.581427
1.513633
1.567193
0.368884
0.399604
0.45676
0.054463
0.0263
0.15837
0.732142
0.658967
0.406609
8
train
H1
H19
100
100
10
16
7
-1.861822
1.788385
2.551002
2.606318
8.690481
9.680786
8.293496
2.606318
2.551002
0.015816
6.792894
4.449301
3.201446
8.415325
8.297213
-1.814691
8
train
H0
H19
150
150
10
8
12
1.093402
-1.055436
-1.604294
-1.615359
3.574954
4.801556
3.275068
-1.615359
1.604294
0.186918
2.609384
1.57087
1.111559
3.156276
3.049086
1.066434
8
train
H1
H19
150
150
10
12.666667
12
0.036485
-0.053074
0.232704
0.231392
0.312324
0.291596
0.341495
0.231392
0.232704
0.843034
0.053542
0.004483
0.002666
0.254951
0.241989
0.052173
8
train
H0
H19
200
200
10
11.5
9.5
0.056455
-0.125823
0.924605
0.925233
4.168858
4.038204
4.652796
0.925233
0.924605
0.097647
0.856057
0.103574
0.015712
3.211746
3.133192
0.126714
8
train
H1
H19
200
200
10
12.5
12
-2.325393
2.343428
1.830941
1.834505
5.102815
8.110938
5.72863
-2.325393
2.343428
0.016541
3.36541
4.650601
5.517507
0.555337
0.507289
-2.39675
8
train
H0
H19
300
300
10
13.666667
12
1.76651
-1.812794
-0.798228
-0.797867
6.568238
6.726654
6.171156
1.76651
1.812794
0.045704
0.636591
2.292461
3.287675
0.210743
0.178783
1.847495
8
train
H1
H19
300
300
10
10.666667
10
-2.370651
2.453306
0.942016
0.939613
10.608593
10.215318
11.787322
-2.370651
2.453306
0.002757
0.882873
3.579913
6.031838
0.957031
0.888538
-2.500982
8
train
H0
H19
500
500
10
12.4
11
-0.290026
0.312009
0.017148
0.017117
0.195597
1.792745
0.360636
-0.290026
0.312009
0.616515
0.000293
0.032611
0.097601
0.080907
0.104401
-0.317367
8
train
H1
H19
500
500
10
12.8
8.6
-2.96068
2.944476
2.842284
2.846199
8.917229
8.780798
8.994119
-2.96068
2.944476
0.002823
8.100848
8.833033
8.685001
3.706293
3.863297
-2.986353
8
train
H0
H19
1,000
1,000
10
9.4
9.5
1.237723
-1.31224
0.360406
0.361138
10.861288
10.310678
11.475263
1.237723
1.31224
0.003222
0.130421
0.482726
1.721594
3.964291
3.883388
1.330371
8
train
H1
H19
1,000
1,000
10
10.9
9.5
-4.02459
4.064618
2.88539
2.889502
17.160991
16.498684
18.454964
-4.02459
4.064618
0.000038
8.349224
13.469536
16.565522
0.569345
0.597561
-4.119694