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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logrank_test
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0
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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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0
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MIN3_test
float64
0
1
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0
84.2
WLg_TaroneWare_test
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0
99.4
WLg_Breslow_test
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0
106
WLg_PetoPrentice_test
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0
71.9
WLg_Prentice_test
float64
0
71.6
WKM_test
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train
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4.005166
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0.416368
0.08048
0.14382
0.045317
0.173259
1.623541
1.439717
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8
train
H0
H14
500
500
40
36.4
46
2.467605
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6.205573
7.306902
6.24751
2.467605
2.477647
0.012644
6.130171
6.077525
5.918448
3.56788
3.421334
2.493655
8
train
H1
H14
500
500
40
40
40.4
0.590338
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0.604587
2.819377
0.7497
0.590338
0.693589
0.42032
0.13924
0.286773
0.481009
0.016545
0.020114
0.710849
8
train
H0
H14
1,000
1,000
40
39.4
40.7
0.119028
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0.023692
0.141926
0.030471
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0.146958
0.880181
0.005632
0.013092
0.021594
0.002519
0.004214
0.150739
8
train
H1
H14
1,000
1,000
40
40.3
38.5
-0.127765
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0.600412
0.60109
2.600139
2.556303
2.604769
0.60109
0.600412
0.271883
0.361309
0.0385
0.004098
1.76635
1.717743
0.066172
8
train
H0
H14
20
20
50
75
30
-2.646856
2.281438
2.901207
2.929947
9.587544
9.694757
9.571156
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2.901207
0.008349
8.584588
6.622891
5.27875
10.393799
10.53042
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8
train
H1
H14
20
20
50
45
40
-0.414092
0.353142
0.285583
0.278145
0.38892
2.075034
0.294851
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0.353142
0.55698
0.077364
0.16517
0.12388
0.003522
0.074423
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8
train
H0
H14
30
30
50
53.333333
50
0.347894
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0.198132
0.225655
0.193275
0.347894
0.408202
0.670219
0.073928
0.14404
0.166352
0.014859
0.011736
0.425848
8
train
H1
H14
30
30
50
53.333333
43.333333
0.149696
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0.114098
1.510179
0.094612
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0.207331
0.679923
0.043066
0.006742
0.005285
0.026787
0.005852
0.093351
8
train
H0
H14
50
50
50
62
46
-1.325862
1.246819
1.395363
1.384598
1.944571
3.834537
1.928655
1.384598
1.395363
0.188958
1.917113
1.605315
1.551112
1.780892
1.667794
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8
train
H1
H14
50
50
50
60
40
-1.400397
1.200168
1.641645
1.636961
3.345727
3.435141
3.364223
1.636961
1.641645
0.185981
2.679641
2.006566
1.439101
3.953611
3.982822
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8
train
H0
H14
75
75
50
52
54.666667
0.133214
0.224885
-0.543405
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4.266899
4.880817
4.167424
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0.543405
0.124467
0.298085
0.005427
0.050508
2.234932
2.144091
-0.22731
8
train
H1
H14
75
75
50
50.666667
50.666667
-0.069702
0
0.109674
0.109274
0.049117
1.020537
0.036691
0.109274
0.109674
0.796283
0.011941
0.000006
0
0.060261
0.040997
0.000599
8
train
H0
H14
100
100
50
57
52
-0.209028
0.062764
0.449504
0.449001
1.455476
1.491183
1.468712
0.449001
0.449504
0.479814
0.201602
0.054302
0.003934
1.133409
1.118231
-0.065281
8
train
H1
H14
100
100
50
46
49
0.076014
-0.140292
0.034642
0.034645
0.223159
0.268288
0.213526
0.034645
0.140292
0.879877
0.0012
0.005575
0.019663
0.130881
0.119361
0.151125
8
train
H0
H14
150
150
50
42.666667
50.666667
1.99649
-2.160859
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-1.594786
5.685574
5.681186
5.671828
1.99649
2.160859
0.026106
2.543343
3.963404
4.675763
0.171765
0.187053
2.224635
8
train
H1
H14
150
150
50
46.666667
52.666667
0.015135
0.218834
-0.382518
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1.827798
3.376428
2.07921
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0.382518
0.337146
0.145665
0.008329
0.047913
1.110815
1.153591
-0.222554
8
train
H0
H14
200
200
50
47.5
50
0.669643
-0.94122
-0.185642
-0.18558
3.531027
3.567346
3.609548
-0.18558
0.94122
0.164512
0.03444
0.431265
0.886195
0.79891
0.768278
0.975635
8
train
H1
H14
200
200
50
42.5
50
1.348597
-1.088723
-1.774142
-1.777015
5.180974
5.241778
5.226116
-1.777015
1.774142
0.07331
3.157782
1.962374
1.185509
4.877851
4.774656
1.133171
8
train
H0
H14
300
300
50
52
49.666667
0.009026
-0.307836
0.413208
0.412677
3.731438
9.078832
3.386144
0.412677
0.413208
0.028261
0.170302
0.014344
0.094723
1.636984
1.49397
0.314859
8
train
H1
H14
300
300
50
49.666667
54.666667
0.521472
-0.369859
-0.695861
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0.993957
1.983293
0.932085
-0.695695
0.695861
0.575882
0.483991
0.219434
0.136742
0.811532
0.768232
0.38454
8
train
H0
H14
500
500
50
48.2
50.6
1.078328
-0.946055
-1.183385
-1.183692
1.491944
1.715106
1.479152
-1.183692
1.183385
0.327046
1.401126
1.07435
0.895102
1.219816
1.197478
0.98008
8
train
H1
H14
500
500
50
50
50
0.407356
-0.427231
-0.259882
-0.259642
0.341583
1.689407
0.446937
-0.259642
0.427231
0.639291
0.067414
0.091784
0.182519
0.024647
0.026562
0.439826
8
train
H0
H14
1,000
1,000
50
52
48.2
-0.838658
0.515278
1.317808
1.31746
4.990515
5.920964
5.17591
1.31746
1.317808
0.075174
1.735701
0.785009
0.265487
4.564648
4.547083
-0.531581
8
train
H1
H14
1,000
1,000
50
51
50.2
-0.243589
-0.096402
0.733803
0.733641
4.185367
4.184981
4.203753
0.733641
0.733803
0.122227
0.538229
0.047011
0.009293
2.841089
2.844069
0.099009
8
train
H0
H15
20
20
0
0
0
-0.297551
0.297551
-0.191173
-0.187082
0.818117
0.880628
1.006863
-0.297551
0.297551
0.604453
0.035
0.005844
0.088112
0.372691
0.347686
-0.301342
8
train
H1
H15
20
20
0
0
0
1.109054
-1.109054
-1.021157
-1.02657
1.552407
4.580171
1.238119
-1.02657
1.109054
0.20525
1.053845
1.415908
1.231727
0.402135
0.662494
1.123182
8
train
H0
H15
30
30
0
0
0
0.724437
-0.724437
-0.921735
-0.917376
0.89839
1.395892
0.877525
-0.917376
0.921735
0.465054
0.84158
0.667733
0.523807
0.661374
0.595136
0.73055
8
train
H1
H15
30
30
0
0
0
-0.561808
0.561808
0.733594
0.726217
0.604562
1.687733
0.557345
-0.561808
0.733594
0.57102
0.527392
0.388354
0.314528
0.649321
0.562054
-0.566549
8
train
H0
H15
50
50
0
0
0
-1.806181
1.806181
0.544325
0.544295
7.181372
8.307532
8.010965
-1.806181
1.806181
0.018215
0.296257
1.794184
3.297141
1.203994
1.153726
-1.81528
8
train
H1
H15
50
50
0
0
0
0.020681
-0.020681
0.809312
0.810215
2.578455
2.822616
3.068782
0.020681
0.809312
0.215587
0.656449
0.128292
0.000427
2.235059
2.207277
0.020786
8
train
H0
H15
75
75
0
0
0
0.1184
-0.1184
-0.633028
-0.629765
0.932217
0.996887
1.182797
-0.629765
0.633028
0.553553
0.396604
0.137894
0.014011
0.920839
0.916142
0.118002
8
train
H1
H15
75
75
0
0
0
0.644622
-0.644622
0.470766
0.475279
6.01219
6.198917
5.481822
0.644622
0.644622
0.064512
0.22589
0.058596
0.415204
2.39989
2.234985
0.642455
8
train
H0
H15
100
100
0
0
0
-0.153933
0.153933
-0.055286
-0.055126
0.371278
1.657684
0.175407
-0.153933
0.153933
0.646382
0.003039
0.017762
0.023661
0.054941
0.027989
-0.15432
8
train
H1
H15
100
100
0
0
0
-0.59863
0.59863
0.824327
0.820983
0.790049
0.988063
0.732845
-0.59863
0.824327
0.548418
0.674012
0.459451
0.357861
0.773883
0.737756
-0.600132
8
train
H0
H15
150
150
0
0
0
-1.032947
1.032947
1.273103
1.273651
1.623265
2.53855
1.648076
-1.032947
1.273103
0.300822
1.622187
1.401383
1.066529
1.462793
1.621831
-1.034672
8
train
H1
H15
150
150
0
0
0
0.473878
-0.473878
0.702046
0.701739
3.770992
4.646069
5.386006
0.701739
0.702046
0.067677
0.492438
0.007584
0.224864
2.913567
2.935569
0.474669
8
train
H0
H15
200
200
0
0
0
0.883109
-0.883109
0.023846
0.023877
3.183423
5.239539
3.413939
0.023877
0.883109
0.155074
0.00057
0.327028
0.779779
0.859268
0.923908
0.884215
8
train
H1
H15
200
200
0
0
0
-0.642654
0.642654
1.326267
1.327518
2.612956
2.791069
2.863863
1.327518
1.326267
0.238847
1.762304
0.917248
0.412815
2.91822
2.93548
-0.643459
8
train
H0
H15
300
300
0
0
0
1.758288
-1.758288
-1.775532
-1.776443
3.309763
3.327994
3.344762
1.758288
1.775532
0.078449
3.155748
3.266445
3.094356
1.718861
1.71852
1.759756
8
train
H1
H15
300
300
0
0
0
0.115398
-0.115398
0.038506
0.038401
0.005084
0.026906
0.090935
0.038401
0.115398
0.908053
0.001475
0.001619
0.013318
0.035371
0.030077
0.115494
8
train
H0
H15
500
500
0
0
0
0.513069
-0.513069
0.514052
0.514159
3.560094
4.163911
4.018232
0.514159
0.514052
0.134107
0.264359
0.014875
0.263195
2.001637
1.990928
0.513326
8
train
H1
H15
500
500
0
0
0
-0.127665
0.127665
1.881448
1.89186
9.900626
12.909666
13.197763
1.89186
1.881448
0.001362
3.579136
0.933157
0.016314
10.089518
10.201938
-0.127729
8
train
H0
H15
1,000
1,000
0
0
0
-0.226435
0.226435
0.067279
0.067256
0.008124
3.212196
0.118555
-0.226435
0.226435
0.360051
0.004523
0.012708
0.051263
0.009595
0.016142
-0.226492
8
train
H1
H15
1,000
1,000
0
0
0
1.807147
-1.807147
1.468822
1.481327
36.490751
39.691323
42.696411
1.807147
1.807147
0
2.194329
0.226146
3.270502
18.955154
18.990424
1.807599