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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20
1k
perc
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0
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logrank_test
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CoxMantel_test
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BN_GPH_test
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0
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BN_MCE_test
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143
BN_SCE_test
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Q_test
float64
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MAX_Value_test
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0
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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
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train
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train
H1
H26
300
300
40
40
41
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7,645
train
H0
H26
500
500
40
43.6
39.4
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7,645
train
H1
H26
500
500
40
40.2
39.4
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7,645
train
H0
H26
1,000
1,000
40
42
41.1
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1.147405
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7,645
train
H1
H26
1,000
1,000
40
39.4
40.9
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7,645
train
H0
H26
20
20
50
55
65
1.398261
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7,645
train
H1
H26
20
20
50
50
60
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7,645
train
H0
H26
30
30
50
56.666667
56.666667
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7,645
train
H1
H26
30
30
50
56.666667
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7,645
train
H0
H26
50
50
50
46
52
0.182609
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7,645
train
H1
H26
50
50
50
44
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2.17547
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4.743114
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7,645
train
H0
H26
75
75
50
48
48
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7,645
train
H1
H26
75
75
50
48
44
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7,645
train
H0
H26
100
100
50
48
52
0.589026
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1.375805
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0.589026
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7,645
train
H1
H26
100
100
50
55
54
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0.22232
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7,645
train
H0
H26
150
150
50
50.666667
50
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1.039673
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0.995421
0.15823
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0.025037
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7,645
train
H1
H26
150
150
50
54
51.333333
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0.784302
1.350994
1.353729
1.990691
2.637277
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1.350994
0.356186
1.832583
1.267171
0.617245
2.097152
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7,645
train
H0
H26
200
200
50
49
54.5
2.1271
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4.494549
4.846992
4.56371
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2.162394
0.020978
3.876436
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7,645
train
H1
H26
200
200
50
55
52
-0.238694
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0.977527
0.980293
5.924804
12.63041
6.850407
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0.005508
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7,645
train
H0
H26
300
300
50
49
50.666667
0.549293
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0.755913
1.173682
0.833982
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0.714838
0.441813
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7,645
train
H1
H26
300
300
50
47.333333
47.666667
0.333206
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0.206185
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1.744266
5.620819
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0.901224
0.131588
0.042409
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0.813104
1.06108
1.073604
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7,645
train
H0
H26
500
500
50
50.6
51.8
0.103388
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0.150659
0.150346
0.599019
0.526841
0.64125
0.150346
0.281215
0.725695
0.022604
0.01173
0.079057
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0.300439
7,645
train
H1
H26
500
500
50
52.4
48.4
1.120893
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4.954665
6.299907
5.497386
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1.626558
0.064011
0.180841
1.212701
2.649002
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1.766063
7,645
train
H0
H26
1,000
1,000
50
49
50.9
0.911079
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0.845625
0.982939
0.84673
0.911079
0.903908
0.382602
0.816167
0.827929
0.664094
0.390691
0.367474
0.873111
7,645
train
H1
H26
1,000
1,000
50
49.3
50.7
0.735883
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0.37568
7.125927
0.705651
0.735883
1.258159
0.067991
0.321388
0.482592
1.583453
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1.36517
7,645
train
H0
H27
20
20
0
0
0
0.1082
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3.615917
3.396791
3.870947
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0.928399
0.144356
0.887029
0.247403
0.011752
2.747064
2.66271
0.109579
7,645
train
H1
H27
20
20
0
0
0
-1.541855
1.541855
1.590878
1.611414
2.706277
2.792021
2.661413
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1.590878
0.118406
2.596654
2.713155
2.407558
1.585931
1.79575
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7,645
train
H0
H27
30
30
0
0
0
-2.084604
2.084604
1.701056
1.740866
5.218911
7.046522
4.492794
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2.084604
0.035536
3.030614
4.445003
4.423899
0.430474
0.786562
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7,645
train
H1
H27
30
30
0
0
0
0.413964
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0.010009
0.009866
0.385384
3.3735
0.795107
0.413964
0.413964
0.337543
0.000097
0.031268
0.17063
0.248871
0.36842
0.417457
7,645
train
H0
H27
50
50
0
0
0
-2.750634
2.750634
2.357467
2.405031
7.178067
8.584713
7.713099
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2.750634
0.005701
5.784175
6.995297
7.702125
1.549569
1.532612
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7,645
train
H1
H27
50
50
0
0
0
1.964739
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3.614897
8.36858
3.938126
1.964739
1.964739
0.038978
3.431874
3.595581
3.889062
1.553267
1.432193
1.974637
7,645
train
H0
H27
75
75
0
0
0
-1.351263
1.351263
1.507743
1.512019
2.28831
2.542471
2.288683
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1.507743
0.17807
2.286201
2.026706
1.827008
1.729167
1.690297
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7,645
train
H1
H27
75
75
0
0
0
0.919009
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0.687078
7.357635
1.531712
0.919009
0.919009
0.061331
0.164202
0.388609
0.844768
0.049988
0.09907
0.91592
7,645
train
H0
H27
100
100
0
0
0
0.161264
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0.349442
2.366293
0.14804
0.161264
0.312059
0.49994
0.096635
0.02141
0.025961
0.127518
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7,645
train
H1
H27
100
100
0
0
0
0.620621
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3.149043
13.655884
1.760764
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1.06651
0.003413
1.183588
0.396341
0.385663
1.91105
1.715569
0.622178
7,645
train
H0
H27
150
150
0
0
0
0.606989
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0.817097
1.189525
0.735279
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0.606989
0.543185
0.052745
0.230463
0.368089
0.057776
0.035998
0.608003
7,645
train
H1
H27
150
150
0
0
0
-0.037271
0.037271
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2.449252
3.07957
1.866829
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0.626897
0.379519
0.394984
0.019842
0.001389
1.345377
1.25587
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7,645
train
H0
H27
200
200
0
0
0
0.401334
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0.624189
1.238625
0.332912
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0.401334
0.687804
0.020612
0.144851
0.160925
0.029568
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0.401837
7,645
train
H1
H27
200
200
0
0
0
0.998146
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0.735492
4.178041
1.912138
0.998146
0.998146
0.24287
0.15589
0.39234
0.997636
0.09207
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0.999396
7,645
train
H0
H27
300
300
0
0
0
-0.312281
0.312281
0.544504
0.54312
0.393545
0.40559
0.397946
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0.544504
0.754629
0.29498
0.162833
0.097459
0.42167
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7,645
train
H1
H27
300
300
0
0
0
0.562389
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0.58034
4.621907
0.382336
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0.615622
0.201671
0.379475
0.190003
0.316448
0.265751
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0.562858
7,645
train
H0
H27
500
500
0
0
0
-0.402703
0.402703
0.220153
0.219866
0.181917
0.183925
0.22985
0.219866
0.402703
0.687018
0.048341
0.108612
0.162134
0.000448
0.000054
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7,645
train
H1
H27
500
500
0
0
0
2.572572
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4.956316
18.946024
10.956045
2.572572
2.572572
0.000281
1.471029
3.152173
6.642104
0.146062
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2.573859
7,645
train
H0
H27
1,000
1,000
0
0
0
0.245486
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0.776159
2.545156
0.209092
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0.245486
0.467186
0.00044
0.085901
0.060255
0.04542
0.03645
0.245547
7,645
train
H1
H27
1,000
1,000
0
0
0
1.734353
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2.56838
25.897512
9.850208
1.734353
1.734353
0.00001
0.044457
0.542745
3.015582
1.657495
1.761202
1.734787