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
int64
20
1k
perc
int64
0
50
real_perc1
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95
real_perc2
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logrank_test
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CoxMantel_test
float64
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BN_GPH_test
float64
0
109
BN_MCE_test
float64
0
143
BN_SCE_test
float64
0
114
Q_test
float64
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MAX_Value_test
float64
0
10.2
MIN3_test
float64
0
1
WLg_logrank_test
float64
0
84.2
WLg_TaroneWare_test
float64
0
99.4
WLg_Breslow_test
float64
0
106
WLg_PetoPrentice_test
float64
0
71.9
WLg_Prentice_test
float64
0
71.6
WKM_test
float64
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10.7
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train
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train
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train
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train
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train
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train
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train
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train
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train
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H1
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train
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train
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7,642
train
H1
H27
300
300
40
40
38.333333
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7,642
train
H0
H27
500
500
40
39.8
40.4
0.981397
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7,642
train
H1
H27
500
500
40
40.8
37.2
1.426001
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9.921682
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3.53707
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7,642
train
H0
H27
1,000
1,000
40
40.3
36.1
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3.405973
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0.900824
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2.850695
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7,642
train
H1
H27
1,000
1,000
40
38.1
40.4
3.575162
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46.324645
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50.517106
3.575162
4.31921
0
2.237007
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7,642
train
H0
H27
20
20
50
60
55
0.548217
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7,642
train
H1
H27
20
20
50
50
70
0.772289
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7,642
train
H0
H27
30
30
50
53.333333
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7,642
train
H1
H27
30
30
50
50
33.333333
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3.655615
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7,642
train
H0
H27
50
50
50
56
54
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1.463867
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7,642
train
H1
H27
50
50
50
48
44
1.047398
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7,642
train
H0
H27
75
75
50
58.666667
45.333333
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1.46425
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3.322478
7.934049
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1.769245
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3.128306
2.323587
2.145272
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7,642
train
H1
H27
75
75
50
38.666667
53.333333
3.242154
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10.562947
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10.895187
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3.347562
0.000113
9.509243
10.436793
11.423828
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3.479712
7,642
train
H0
H27
100
100
50
45
54
0.501316
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0.254056
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7,642
train
H1
H27
100
100
50
56
54
0.759663
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1.312117
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7,642
train
H0
H27
150
150
50
56
48
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1.751001
3.424498
3.573832
3.444473
1.751001
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0.178666
3.066004
2.229981
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7,642
train
H1
H27
150
150
50
46
52
3.643969
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21.716126
24.703438
22.240975
3.643969
4.065389
0.000015
8.237616
13.087252
16.727782
0.441567
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4.245844
7,642
train
H0
H27
200
200
50
52.5
48.5
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0.419795
0.387007
0.386001
0.226633
1.144528
0.200257
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0.419795
0.662017
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0.223366
0.176155
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7,642
train
H1
H27
200
200
50
51
52
1.325738
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5.283628
13.854918
6.047795
1.325738
1.710796
0.003109
0.569378
1.543515
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0.407228
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1.787932
7,642
train
H0
H27
300
300
50
54.333333
49.333333
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0.454671
0.825731
0.825738
1.352667
1.918387
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0.825738
0.825731
0.524321
0.681843
0.340697
0.206639
1.37362
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7,642
train
H1
H27
300
300
50
48.666667
49.333333
2.979981
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20.142827
25.403481
21.427953
2.979981
3.586541
0.000013
3.613909
8.479806
12.955834
0.307283
0.305083
3.767032
7,642
train
H0
H27
500
500
50
49
48.8
1.341951
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4.852854
5.192754
4.931126
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1.644772
0.084961
0.708611
1.878511
2.707601
0.159412
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1.698039
7,642
train
H1
H27
500
500
50
52.2
50.4
2.306707
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21.085099
33.629514
23.095569
2.306707
3.123175
0
1.273801
5.15921
9.787996
2.176606
2.234945
3.286374
7,642
train
H0
H27
1,000
1,000
50
49.5
48.4
-0.448274
0.49896
0.34423
0.344021
0.290424
0.319601
0.3035
0.344021
0.49896
0.605013
0.11835
0.195084
0.248924
0.00497
0.005206
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7,642
train
H1
H27
1,000
1,000
50
48.7
50.5
2.881442
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21.505943
34.257791
23.864081
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3.590772
0
2.923422
7.498974
12.914249
0.979849
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3.762505
7,642
train
H0
H28
20
20
0
0
0
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0.622152
0.559226
0.547878
0.308183
1.490649
0.38548
0.547878
0.622152
0.528644
0.300171
0.292306
0.385358
0.164994
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7,642
train
H1
H28
20
20
0
0
0
0.162301
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1.138542
1.429447
1.040079
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0.605283
0.594497
0.35718
0.111134
0.026082
0.707917
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7,642
train
H0
H28
30
30
0
0
0
-1.493227
1.493227
1.347794
1.347918
2.059749
3.635148
2.243843
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1.493227
0.132111
1.816883
2.04539
2.241362
0.667839
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7,642
train
H1
H28
30
30
0
0
0
0.620946
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0.630751
0.60704
0.648957
0.620946
0.620946
0.531193
0.089301
0.249611
0.384021
0.036201
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0.626186
7,642
train
H0
H28
50
50
0
0
0
-1.034073
1.034073
1.516519
1.533945
2.915182
3.045836
2.86061
1.533945
1.516519
0.239236
2.352989
1.574166
1.069011
3.036628
2.960355
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7,642
train
H1
H28
50
50
0
0
0
-0.585975
0.585975
0.428212
0.423691
0.363831
0.481435
0.376111
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0.585975
0.55591
0.179514
0.274882
0.342385
0.035536
0.063943
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7,642
train
H0
H28
75
75
0
0
0
1.370056
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2.70029
3.863681
1.999234
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1.370056
0.172111
1.06714
1.932968
1.882947
0.205985
0.298675
1.365451
7,642
train
H1
H28
75
75
0
0
0
-1.125739
1.125739
0.310608
0.311567
3.818594
4.260666
3.261711
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1.125739
0.195762
0.097074
0.82335
1.26874
0.492038
0.424018
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7,642
train
H0
H28
100
100
0
0
0
0.15882
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0.007187
0.007131
0.058478
0.617897
0.11223
0.15882
0.15882
0.873496
0.000051
0.006482
0.025174
0.04306
0.062783
0.159219
7,642
train
H1
H28
100
100
0
0
0
1.424496
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3.602331
8.320608
3.244535
1.424496
1.75025
0.03983
3.147322
2.255731
2.030861
2.754368
2.596195
1.42807
7,642
train
H0
H28
150
150
0
0
0
1.349752
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2.400629
4.533188
1.851726
1.349752
1.349752
0.176373
1.588167
2.163759
1.82347
0.728224
0.863711
1.352008
7,642
train
H1
H28
150
150
0
0
0
0.231614
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0.099537
0.0997
0.012395
5.397012
0.435343
0.231614
0.231614
0.14493
0.00994
0.013921
0.053784
0.130134
0.191476
0.232001
7,642
train
H0
H28
200
200
0
0
0
-0.424688
0.424688
0.244612
0.24348
0.162904
0.104301
0.243909
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0.424688
0.670676
0.059282
0.105281
0.180219
0.000348
0.001726
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7,642
train
H1
H28
200
200
0
0
0
0.674657
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0.655408
4.295294
0.548495
0.674657
0.737726
0.231293
0.544516
0.361875
0.454915
0.353162
0.295273
0.675502
7,642
train
H0
H28
300
300
0
0
0
0.305687
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0.216297
0.35601
0.214781
0.305687
0.305687
0.759649
0.008452
0.046594
0.093404
0.02705
0.019144
0.305942
7,642
train
H1
H28
300
300
0
0
0
-0.743257
0.743257
0.510695
0.511203
1.46046
5.011116
0.628622
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0.743257
0.170985
0.261329
0.710885
0.553073
0.01011
0.024899
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7,642
train
H0
H28
500
500
0
0
0
0.550077
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0.402195
0.4034
4.710889
7.575177
3.537104
0.4034
0.550077
0.055658
0.162731
0.074473
0.302505
1.610117
1.520238
0.550352
7,642
train
H1
H28
500
500
0
0
0
2.377023
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4.398361
16.160145
5.6916
2.377023
2.377023
0.001051
3.927847
4.496943
5.658018
1.144765
1.071477
2.378213
7,642
train
H0
H28
1,000
1,000
0
0
0
0.928509
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1.042447
2.23016
1.048738
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1.0206
0.353023
1.04107
0.945211
0.862053
0.689746
0.657257
0.928742
7,642
train
H1
H28
1,000
1,000
0
0
0
-0.577008
0.577008
1.08254
1.085405
1.340055
18.846464
1.7222
1.085405
1.08254
0.000294
1.178104
1.300631
0.333306
1.582101
1.690759
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