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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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
float64
0
71.9
WLg_Prentice_test
float64
0
71.6
WKM_test
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7,644
train
H1
H16
300
300
0
0
0
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1.033401
0.781245
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0.801113
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1.124561
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7,644
train
H0
H16
500
500
0
0
0
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0.054457
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7,644
train
H1
H16
500
500
0
0
0
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0.239126
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7.347098
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6.278999
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1.02022
0.025332
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4.106109
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7,644
train
H0
H16
1,000
1,000
0
0
0
0.654293
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0.50197
7.056487
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0.654293
0.654293
0.070119
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0.154625
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0.654457
7,644
train
H1
H16
1,000
1,000
0
0
0
1.872584
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14.926582
14.321807
15.384073
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3.297302
0.000456
11.028349
6.36978
3.509003
15.266373
15.179494
1.873052
7,644
train
H0
H16
20
20
10
10
10
2.28016
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26.106431
28.540713
25.633287
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2.808818
0.000003
11.414711
7.757117
4.995519
24.29964
24.0712
2.273369
7,644
train
H1
H16
20
20
10
15
10
-0.651573
0.642516
0.43541
0.426426
0.638866
0.766358
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0.511159
0.181839
0.342339
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7,644
train
H0
H16
30
30
10
6.666667
6.666667
0.164533
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0.338121
2.069043
0.212781
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0.558201
0.111117
0.031697
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7,644
train
H1
H16
30
30
10
6.666667
20
-0.044477
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0.090493
0.090322
0.014955
0.038969
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0.962544
0.008158
0.004525
0.002043
0.049082
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7,644
train
H0
H16
50
50
10
12
8
-0.275791
0.281462
0.084432
0.083735
0.1212
0.160995
0.217013
0.083735
0.281462
0.774547
0.007012
0.025149
0.079041
0.014475
0.009722
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7,644
train
H1
H16
50
50
10
16
18
-0.525884
0.491259
0.446991
0.449401
0.267578
0.234697
0.285653
0.449401
0.491259
0.616685
0.201961
0.217386
0.24107
0.072656
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7,644
train
H0
H16
75
75
10
6.666667
12
-0.619019
0.605876
0.648066
0.647804
0.509839
2.441346
0.4269
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0.648066
0.485984
0.41965
0.499645
0.366825
0.304012
0.44953
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7,644
train
H1
H16
75
75
10
5.333333
8
-0.598404
0.650175
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7.418034
7.560078
7.047627
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0.650175
0.029487
0.384333
0.036965
0.423018
3.710647
3.52716
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7,644
train
H0
H16
100
100
10
8
8
0.993181
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1.11051
2.943379
1.476699
0.993181
1.024618
0.302533
0.319979
0.68587
1.050211
0.005227
0.014192
1.031017
7,644
train
H1
H16
100
100
10
8
7
-1.530477
1.577268
0.505881
0.504093
5.616459
5.984445
5.941817
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1.577268
0.051257
0.254109
1.449101
2.491226
0.722468
0.671934
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7,644
train
H0
H16
150
150
10
9.333333
9.333333
1.529248
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2.40464
2.456714
2.341211
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1.52137
0.124678
1.885041
2.320697
2.316385
0.671566
0.724341
1.53543
7,644
train
H1
H16
150
150
10
7.333333
10.666667
-0.957734
0.984181
0.389303
0.387812
1.335455
2.800016
1.958862
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0.984181
0.321936
0.150398
0.494693
0.969483
0.126382
0.154445
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7,644
train
H0
H16
200
200
10
13
8
-0.202485
0.144688
0.884288
0.883179
2.042903
3.328056
2.494997
0.883179
0.884288
0.287222
0.780004
0.235275
0.020919
2.110845
2.231572
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7,644
train
H1
H16
200
200
10
10
8
-0.865773
0.891845
0.23717
0.236808
1.506258
2.860088
2.143496
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0.891845
0.342409
0.056078
0.344165
0.795397
0.27633
0.286611
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7,644
train
H0
H16
300
300
10
11
10
0.414582
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0.411124
0.47548
0.634819
0.414582
0.434971
0.661423
0.003935
0.059697
0.189153
0.13507
0.130506
0.43795
7,644
train
H1
H16
300
300
10
10.666667
11.666667
-0.308954
0.36921
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3.054699
3.398361
3.759082
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0.574853
0.15266
0.329817
0.002382
0.136335
2.08507
2.045084
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7,644
train
H0
H16
500
500
10
8.2
7.8
0.751053
-0.745662
-0.886178
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0.826221
1.278975
0.791437
0.751053
0.886178
0.453483
0.785328
0.620147
0.55596
0.613655
0.601847
0.749621
7,644
train
H1
H16
500
500
10
8.6
10.2
-0.247634
0.287647
-0.50799
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2.73731
2.713881
2.667461
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0.50799
0.263492
0.257744
0.000004
0.082723
1.488148
1.427622
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7,644
train
H0
H16
1,000
1,000
10
10.6
9.9
-1.128599
1.142325
0.890495
0.889772
1.149524
1.009584
1.336891
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1.142325
0.249556
0.791695
1.044478
1.305112
0.149939
0.168561
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7,644
train
H1
H16
1,000
1,000
10
11.3
10.6
-1.930462
2.004842
0.756045
0.756011
5.911565
11.093932
8.397716
-1.930462
2.004842
0.011229
0.571553
2.059998
4.021828
0.672553
0.695627
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7,644
train
H0
H16
20
20
20
10
10
1.216584
-1.207986
-1.430119
-1.492148
2.326456
4.40469
2.428886
-1.492148
1.430119
0.220951
2.226506
1.940263
1.470119
1.972814
2.116065
1.2198
7,644
train
H1
H16
20
20
20
15
5
-2.556341
2.521245
2.414334
2.543651
6.6823
11.926973
6.885015
-2.556341
2.521245
0.007638
6.470159
6.452255
6.589334
3.120579
2.935733
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7,644
train
H0
H16
30
30
20
33.333333
13.333333
-0.989527
0.938879
1.190105
1.180153
1.540506
2.02097
1.491312
1.180153
1.190105
0.334969
1.392761
1.056049
0.877127
1.683975
1.646422
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7,644
train
H1
H16
30
30
20
20
20
-0.84604
0.785159
0.861188
0.880893
0.790604
7.384414
0.778636
0.880893
0.861188
0.060604
0.775972
0.602789
0.616859
0.626751
0.5557
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7,644
train
H0
H16
50
50
20
28
20
-0.783929
0.784682
0.73626
0.728208
0.55464
1.549425
0.61457
-0.783929
0.784682
0.420202
0.530287
0.52349
0.614394
0.271832
0.228939
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7,644
train
H1
H16
50
50
20
10
26
0.255977
-0.150382
-0.663609
-0.660098
0.987641
1.986071
1.127526
-0.660098
0.663609
0.569064
0.43573
0.132114
0.022589
0.894875
0.966294
0.158028
7,644
train
H0
H16
75
75
20
13.333333
17.333333
0.027969
-0.030901
-0.167812
-0.167765
0.04673
3.098295
0.128008
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0.167812
0.376717
0.028145
0.025839
0.000953
0.059959
0.08379
0.036081
7,644
train
H1
H16
75
75
20
12
22.666667
1.587205
-1.562734
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2.706133
3.393598
2.531534
-1.487701
1.562734
0.113301
2.213253
2.659719
2.443209
0.97391
1.09106
1.58353
7,644
train
H0
H16
100
100
20
23
14
0.189572
-0.257773
0.260684
0.260859
0.76274
5.986585
1.240619
0.189572
0.260684
0.112265
0.068047
0.001153
0.066403
0.639649
0.707332
0.25945
7,644
train
H1
H16
100
100
20
15
20
-1.363418
1.426446
0.558565
0.557621
3.843966
6.724067
4.744485
-1.363418
1.426446
0.081233
0.310941
1.074028
2.045705
0.424991
0.457407
-1.44498
7,644
train
H0
H16
150
150
20
24
16
-1.720482
1.628718
2.228499
2.241563
6.132303
8.837651
5.791512
2.241563
2.228499
0.031529
5.024607
3.407641
2.656033
5.909014
5.68411
-1.656829
7,644
train
H1
H16
150
150
20
16
17.333333
0.323823
-0.309618
-0.531633
-0.530894
0.409155
0.377172
0.42846
-0.530894
0.531633
0.753923
0.281848
0.181063
0.095756
0.374829
0.379455
0.313471
7,644
train
H0
H16
200
200
20
16
15
0.167963
-0.212852
0.033766
0.033665
0.063826
2.090591
0.219238
0.033665
0.212852
0.553819
0.001133
0.003156
0.045272
0.085583
0.114495
0.215376
7,644
train
H1
H16
200
200
20
21.5
21
-0.746144
0.723843
0.749046
0.748668
0.564827
0.724722
0.582082
0.748668
0.749046
0.463163
0.560504
0.505892
0.523655
0.359315
0.353535
-0.733648
7,644
train
H0
H16
300
300
20
22
19
0.135577
-0.213325
0.250697
0.250323
0.732093
1.526727
0.863556
0.250323
0.250697
0.649354
0.062662
0.000752
0.045509
0.480864
0.514526
0.215088
7,644
train
H1
H16
300
300
20
19
15
-2.496514
2.514542
2.008455
2.015217
6.658984
6.549449
6.658882
-2.496514
2.514542
0.011097
4.061099
5.707762
6.334259
0.718529
0.756256
-2.539614
7,644
train
H0
H16
500
500
20
20.2
20.8
1.240725
-1.172618
-1.399988
-1.402171
2.019455
5.933968
1.977256
-1.402171
1.399988
0.114867
1.966082
2.043917
1.3755
1.615504
1.670952
1.189897
7,644
train
H1
H16
500
500
20
22
20
0.074506
-0.083797
0.089565
0.08945
0.340902
1.708804
0.156399
0.08945
0.089565
0.634978
0.008001
0.008946
0.00702
0.087807
0.065989
0.085271
7,644
train
H0
H16
1,000
1,000
20
20.2
20.7
-1.123266
1.171547
0.693332
0.693068
1.73605
2.076837
1.935785
-1.123266
1.171547
0.234325
0.480343
0.983598
1.372512
0.001215
0.000997
-1.189291
7,644
train
H1
H16
1,000
1,000
20
20.5
19.9
-0.480018
0.533626
0.034925
0.034939
1.295703
1.400651
1.243953
0.034939
0.533626
0.536882
0.001221
0.14306
0.284734
0.298536
0.311924
-0.541086