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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1k
perc
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0
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logrank_test
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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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0
99.4
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0
106
WLg_PetoPrentice_test
float64
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71.9
WLg_Prentice_test
float64
0
71.6
WKM_test
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train
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1.502661
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7,647
train
H1
H23
300
300
30
33.666667
26.666667
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2.20926
1.21334
1.217187
8.282846
8.727833
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1.481544
3.658425
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7,647
train
H0
H23
500
500
30
28.8
32.2
1.052481
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2.036483
2.82333
1.665409
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0.254054
0.454243
1.049318
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1.140557
7,647
train
H1
H23
500
500
30
28.4
31.2
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0.429615
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15.204911
15.679018
15.737019
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1.442505
0.000383
2.098913
0.082569
0.187195
10.562974
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7,647
train
H0
H23
1,000
1,000
30
29.8
28.9
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0.159562
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0.383437
1.261156
0.583843
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0.250216
0.738377
0.062577
0.002316
0.026155
0.337413
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7,647
train
H1
H23
1,000
1,000
30
27.3
28.9
0.444417
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13.390446
16.693021
11.460268
0.444417
1.718896
0.000817
2.989292
0.469953
0.056843
9.197228
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7,647
train
H0
H23
20
20
40
25
30
1.157878
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1.436886
2.050084
1.545008
1.157878
1.260457
0.176144
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1.236549
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1.352724
7,647
train
H1
H23
20
20
40
50
55
0.301814
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0.249112
0.657815
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0.382906
0.856941
0.143524
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7,647
train
H0
H23
30
30
40
33.333333
33.333333
0.06666
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0.638151
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3.751195
8.431611
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0.06666
0.638151
0.037885
0.405703
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2.630073
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7,647
train
H1
H23
30
30
40
46.666667
26.666667
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1.65599
1.798375
1.772462
3.181692
3.222343
3.181812
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1.798375
0.069191
3.141622
3.113942
2.799232
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7,647
train
H0
H23
50
50
40
34
40
-0.294342
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0.051347
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0.380017
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0.050907
0.339042
0.712349
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0.046848
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7,647
train
H1
H23
50
50
40
38
40
0.052534
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1.110703
1.432764
1.205791
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0.423483
0.547225
0.177252
0.023327
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0.647437
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7,647
train
H0
H23
75
75
40
42.666667
36
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1.344889
0.796362
0.796006
2.574928
2.629235
2.644899
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1.344889
0.139274
0.633625
1.391363
1.83783
0.0127
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7,647
train
H1
H23
75
75
40
37.333333
46.666667
0.431217
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1.219914
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0.431217
0.600635
0.527963
0.004039
0.153844
0.33922
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0.297033
0.631118
7,647
train
H0
H23
100
100
40
43
39
-0.048813
0.024084
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0.300401
1.962194
0.192608
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0.106622
0.58029
0.011255
0.001627
0.001136
0.072044
0.044973
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7,647
train
H1
H23
100
100
40
30
42
-0.086248
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0.043864
0.043932
0.034339
0.357867
0.017499
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0.066264
0.941821
0.00193
0.005647
0.005248
0.000012
0.001591
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7,647
train
H0
H23
150
150
40
41.333333
40.666667
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0.046614
1.063398
1.074194
5.918273
7.062082
5.466217
1.074194
1.063398
0.065017
1.153892
0.158331
0.003005
4.060082
3.960871
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7,647
train
H1
H23
150
150
40
46
38.666667
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0.819079
0.27455
0.274074
1.966153
2.390007
1.803455
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0.819079
0.374711
0.075116
0.449061
0.686147
0.225836
0.185734
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7,647
train
H0
H23
200
200
40
36
39.5
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0.278434
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0.071807
4.706881
0.258571
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0.278434
0.194563
0.001235
0.005118
0.080031
0.074143
0.121393
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7,647
train
H1
H23
200
200
40
43
42
-1.814399
2.095182
0.895097
0.896774
9.190573
8.953643
9.12486
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2.095182
0.010437
0.804204
2.849496
4.444708
0.906985
0.773281
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7,647
train
H0
H23
300
300
40
40.666667
45.666667
-0.065079
0.215567
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1.138025
1.347204
1.210111
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0.319167
0.546044
0.101483
0.000131
0.048731
0.683781
0.716259
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7,647
train
H1
H23
300
300
40
39.333333
39
0.481924
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0.382229
3.72977
0.312823
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0.551195
0.292161
0.304551
0.205178
0.265604
0.252403
0.202065
0.559534
7,647
train
H0
H23
500
500
40
36.2
40.8
0.410005
-0.380916
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0.280175
0.360547
0.287531
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0.509918
0.68169
0.259464
0.18845
0.14212
0.244814
0.254265
0.410158
7,647
train
H1
H23
500
500
40
34.6
38.8
-0.480434
0.820167
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16.082142
16.925149
15.050793
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0.963206
0.000539
0.931894
0.050246
0.678907
8.473404
8.215134
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7,647
train
H0
H23
1,000
1,000
40
41.1
40.6
-1.085813
1.22518
0.632817
0.632255
2.048977
2.276355
2.206296
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1.22518
0.181544
0.399746
1.032609
1.509322
0.044056
0.045529
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7,647
train
H1
H23
1,000
1,000
40
42.6
41.4
-0.740863
0.895839
0.387827
0.387475
0.924683
3.711582
1.312628
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0.895839
0.29434
0.150137
0.420027
0.80879
0.070559
0.079388
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7,647
train
H0
H23
20
20
50
50
55
0.189536
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0.293303
0.62717
0.311098
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0.314016
0.855945
0.098536
0.048369
0.017163
0.090591
0.117192
0.143681
7,647
train
H1
H23
20
20
50
75
65
-0.52274
0.634287
0.267303
0.264304
2.167906
3.369034
2.095363
0.264304
0.634287
0.338149
0.069857
0.375615
0.590806
0.242625
0.122886
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7,647
train
H0
H23
30
30
50
43.333333
40
0.694594
-0.686942
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0.573236
0.57297
0.573876
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0.743158
0.482679
0.567123
0.531078
0.447214
0.293607
0.307736
0.702
7,647
train
H1
H23
30
30
50
56.666667
63.333333
-0.261605
0.588548
-0.203483
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4.649144
5.230605
4.736033
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0.588548
0.093666
0.041371
0.055824
0.374933
1.96957
1.991272
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7,647
train
H0
H23
50
50
50
44
50
0.500409
-0.441804
-0.493268
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0.303935
2.142692
0.250297
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0.493268
0.543324
0.235863
0.283128
0.171659
0.063099
0.11018
0.472023
7,647
train
H1
H23
50
50
50
58
56
-0.126535
0.427142
-0.361583
-0.359906
3.83182
3.881432
3.771036
-0.359906
0.427142
0.15175
0.129532
0.025042
0.21085
1.918954
1.763459
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7,647
train
H0
H23
75
75
50
60
45.333333
-1.827232
1.824352
1.680658
1.679755
3.340306
3.658492
3.391628
1.679755
1.824352
0.037475
2.821577
3.266778
3.432989
1.058166
1.075072
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7,647
train
H1
H23
75
75
50
50.666667
53.333333
-0.707877
1.025209
0.136808
0.136467
3.776937
4.217944
3.902799
0.136467
1.025209
0.142075
0.018623
0.463217
1.079621
0.975604
0.98298
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7,647
train
H0
H23
100
100
50
58
59
0.257254
-0.313312
-0.145734
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0.201976
0.291919
0.21983
0.257254
0.313312
0.740071
0.021103
0.050104
0.089725
0.051887
0.049984
0.33176
7,647
train
H1
H23
100
100
50
43
55
1.393044
-1.402554
-1.370521
-1.360316
1.907705
3.084963
1.956514
1.393044
1.402554
0.113422
1.850458
1.894793
1.896398
0.852984
0.770142
1.582997
7,647
train
H0
H23
150
150
50
40
48.666667
-0.841393
1.104229
0.017047
0.017098
5.111795
5.112012
4.956205
-0.841393
1.104229
0.083902
0.000292
0.53277
1.253458
1.566475
1.401816
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7,647
train
H1
H23
150
150
50
50
56
0.026054
0.178864
-0.379865
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1.373144
1.381235
1.345901
-0.37827
0.379865
0.510201
0.143088
0.000011
0.037996
0.802924
0.750627
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7,647
train
H0
H23
200
200
50
58
48
-0.633041
0.522992
0.836427
0.834161
1.070503
1.473445
0.998746
-0.633041
0.836427
0.541319
0.695825
0.380139
0.291111
1.090227
1.072424
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7,647
train
H1
H23
200
200
50
44.5
48
0.453479
-0.505758
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0.180892
1.482362
0.205932
0.453479
0.505758
0.585282
0.177268
0.172077
0.241003
0.044315
0.035877
0.545686
7,647
train
H0
H23
300
300
50
49
51.666667
0.369502
-0.441524
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0.899019
3.246455
0.703661
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0.441524
0.355165
0.012133
0.124261
0.184777
0.157173
0.129714
0.485682
7,647
train
H1
H23
300
300
50
50.333333
48.333333
0.111585
-0.167411
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0.074827
0.672142
0.047808
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0.167411
0.859976
0.027756
0.011981
0.024426
0.031041
0.034267
0.176404
7,647
train
H0
H23
500
500
50
52.4
50
-2.014211
1.795211
2.062835
2.067056
4.378183
5.622609
4.309127
-2.014211
2.062835
0.041949
4.272722
4.187155
3.255185
2.509582
2.613386
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7,647
train
H1
H23
500
500
50
48
49
-0.083923
0.308684
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2.866522
3.000657
2.889704
-0.487607
0.488423
0.235781
0.23776
0.001631
0.100768
1.692717
1.743757
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7,647
train
H0
H23
1,000
1,000
50
49.2
51.3
-0.045515
0.089298
-0.239977
-0.239949
0.920912
1.450519
0.768504
-0.239949
0.239977
0.68096
0.057576
0.003087
0.008935
0.442944
0.428819
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7,647
train
H1
H23
1,000
1,000
50
51.2
48.9
-1.189099
1.380805
0.48833
0.488513
5.785362
6.942391
5.208758
-1.189099
1.380805
0.073757
0.238645
1.371635
1.925013
0.769869
0.728176
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