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
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0
50
real_perc1
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logrank_test
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CoxMantel_test
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BN_GPH_test
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0
109
BN_MCE_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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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
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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7,647
train
H1
H28
300
300
30
35
28.333333
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0.402877
1.219182
1.217877
2.813051
13.223178
3.70656
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0.004178
1.483225
0.816062
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3.29674
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7,647
train
H0
H28
500
500
30
32.4
28.8
-0.29435
0.287719
0.149794
0.150011
0.344357
2.557235
0.208958
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0.465036
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7,647
train
H1
H28
500
500
30
31.4
31.2
0.117073
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0.880992
0.882239
6.585662
11.772674
7.959818
0.882239
0.880992
0.008204
0.778345
0.049551
0.160976
4.666953
4.756756
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7,647
train
H0
H28
1,000
1,000
30
29.7
30.2
0.950029
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3.925339
4.646722
4.048708
0.950029
1.132526
0.132079
0.060149
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1.282899
0.709775
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1.159238
7,647
train
H1
H28
1,000
1,000
30
31.4
30.8
0.916966
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0.167143
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7.949108
9.165014
8.984847
0.167259
1.19892
0.011193
0.027976
0.3843
1.437775
2.967285
2.93313
1.23273
7,647
train
H0
H28
20
20
40
30
55
2.454334
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6.270844
6.535674
6.302843
2.454334
2.604782
0.006787
5.311482
6.80628
6.930173
2.13164
2.549012
2.707101
7,647
train
H1
H28
20
20
40
50
20
-1.457103
1.325903
2.016564
2.034187
7.583516
7.796322
7.640742
2.034187
2.016564
0.02192
4.137919
2.817761
1.75944
8.180369
8.170566
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7,647
train
H0
H28
30
30
40
30
46.666667
0.846307
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0.700022
1.671333
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0.407416
0.588401
0.564186
0.632316
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0.82845
7,647
train
H1
H28
30
30
40
43.333333
50
1.084811
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5.885826
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5.974838
1.084811
1.511645
0.050417
0.159362
1.221066
2.28507
0.980321
0.796186
1.586319
7,647
train
H0
H28
50
50
40
34
36
1.14435
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2.160201
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2.180856
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1.385405
0.276286
1.957772
1.460509
1.088462
1.792991
1.848835
1.088701
7,647
train
H1
H28
50
50
40
44
38
-1.09545
0.929058
1.454317
1.481218
3.561133
3.59638
3.521066
1.481218
1.454317
0.171953
2.194007
1.355408
0.86576
4.045327
3.974964
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7,647
train
H0
H28
75
75
40
49.333333
45.333333
0.67705
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0.537771
0.784282
0.573322
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0.72828
0.451399
0.305455
0.436944
0.53146
0.013214
0.012099
0.753085
7,647
train
H1
H28
75
75
40
41.333333
46.666667
0.940356
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1.515596
2.347993
1.647021
0.940356
1.043073
0.283317
0.419284
0.763992
1.086896
0.011656
0.012862
1.072899
7,647
train
H0
H28
100
100
40
44
36
-0.391085
0.345331
0.494608
0.492453
0.363642
2.692176
0.303326
0.492453
0.494608
0.441559
0.24251
0.11754
0.119049
0.360329
0.271234
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7,647
train
H1
H28
100
100
40
45
35
-0.581481
0.472238
0.848518
0.847881
1.141142
8.248239
1.350543
0.847881
0.848518
0.04115
0.718902
0.548768
0.222868
1.290444
1.432153
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7,647
train
H0
H28
150
150
40
34.666667
41.333333
0.418578
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0.705907
1.067983
0.90573
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0.556881
0.563523
0.010481
0.109372
0.309926
0.232134
0.226518
0.577617
7,647
train
H1
H28
150
150
40
37.333333
43.333333
0.358955
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0.309423
0.310458
4.435645
4.391123
4.606728
0.310458
0.628309
0.099922
0.096384
0.060845
0.3952
1.999923
1.952831
0.659237
7,647
train
H0
H28
200
200
40
36
42
0.246631
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0.00965
0.009682
0.735026
0.830274
0.674646
0.009682
0.337086
0.713678
0.000094
0.056669
0.113564
0.248584
0.214577
0.350947
7,647
train
H1
H28
200
200
40
40
43.5
2.010022
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12.598362
13.086865
13.157733
2.010022
2.314151
0.001389
1.126758
3.362886
5.375097
0.698748
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2.379004
7,647
train
H0
H28
300
300
40
38
38.666667
0.400186
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0.741051
0.735682
0.724367
0.400186
0.480712
0.619661
0.017617
0.137399
0.230975
0.142624
0.117498
0.496331
7,647
train
H1
H28
300
300
40
45.666667
38.666667
-0.264522
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1.103821
1.103283
7.719883
11.256784
8.444971
1.103283
1.103821
0.010415
1.217233
0.205141
0.013722
5.739949
5.728837
0.117787
7,647
train
H0
H28
500
500
40
36.6
37.2
0.0969
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0.102439
0.102435
0.190103
1.642076
0.342998
0.0969
0.214359
0.649888
0.010493
0.00022
0.045957
0.168649
0.179087
0.221932
7,647
train
H1
H28
500
500
40
37.6
38.6
1.136048
-1.422712
-0.475105
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3.228195
11.32877
4.425741
1.136048
1.422712
0.010075
0.225334
0.883305
2.025419
0.505369
0.568809
1.471214
7,647
train
H0
H28
1,000
1,000
40
39.3
39.1
-0.473196
0.569535
0.183238
0.183361
1.163225
2.051024
0.924959
0.183361
0.569535
0.557225
0.033621
0.274552
0.324335
0.132889
0.141945
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7,647
train
H1
H28
1,000
1,000
40
37.6
42.5
3.007466
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11.436435
28.947125
13.717102
3.007466
3.362383
0.000002
4.664954
7.577171
11.315819
0.061157
0.055375
3.493283
7,647
train
H0
H28
20
20
50
55
40
0.015815
0.11959
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0.357753
0.488647
0.375773
-0.168252
0.167144
0.828709
0.028309
0.000047
0.014248
0.056809
0.054211
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7,647
train
H1
H28
20
20
50
25
50
2.054044
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4.489529
4.67837
4.481709
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2.063711
0.029889
4.456951
4.362321
3.998889
2.562997
2.695628
2.171555
7,647
train
H0
H28
30
30
50
56.666667
50
-0.004703
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0.255205
0.252396
0.978831
1.012146
0.959796
0.252396
0.255205
0.618847
0.063704
0.002238
0.012113
0.717414
0.692528
0.113017
7,647
train
H1
H28
30
30
50
43.333333
43.333333
1.801718
-2.136878
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6.056428
6.774158
6.282981
1.801718
2.136878
0.022862
1.420862
3.123395
4.641089
0.019391
0.010405
2.275733
7,647
train
H0
H28
50
50
50
58
52
-0.950354
0.903318
0.961775
0.967551
0.937303
2.099941
0.936238
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0.961775
0.345453
0.936155
0.908898
0.815225
0.913372
0.903261
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7,647
train
H1
H28
50
50
50
50
48
0.291469
-0.382126
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0.158073
3.2812
0.208562
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0.382126
0.350268
0.038755
0.072768
0.145818
0.030715
0.036083
0.398149
7,647
train
H0
H28
75
75
50
49.333333
50.666667
-0.305051
0.115423
0.497858
0.498672
0.636245
0.968349
0.670442
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0.497858
0.71518
0.248674
0.078633
0.013308
0.763617
0.796111
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7,647
train
H1
H28
75
75
50
56
46.666667
-0.367917
-0.050934
1.022018
1.024586
6.97727
8.348204
6.657615
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1.022018
0.035836
1.049777
0.114149
0.002592
4.616591
4.362188
0.050715
7,647
train
H0
H28
100
100
50
47
44
-0.316218
0.511826
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2.252327
2.281613
2.24612
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0.511826
0.325283
0.003585
0.084067
0.261828
0.708937
0.681993
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7,647
train
H1
H28
100
100
50
54
41
0.087748
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0.303402
0.303464
1.832134
1.794698
1.858267
0.303464
0.350842
0.394896
0.09209
0.007469
0.123207
1.11291
1.040002
0.369327
7,647
train
H0
H28
150
150
50
41.333333
54.666667
2.016426
-2.110018
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4.662865
5.074986
4.738809
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2.110018
0.02884
2.961027
3.901582
4.449753
0.564248
0.491854
2.185665
7,647
train
H1
H28
150
150
50
50.666667
49.333333
-0.244805
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0.684462
0.683938
2.992612
3.117765
2.909216
0.683938
0.684462
0.233492
0.467771
0.058335
0.000666
2.20133
2.141579
0.022713
7,647
train
H0
H28
200
200
50
49
54
0.407147
-0.17014
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2.641258
2.987607
2.562785
-0.755505
0.755921
0.27765
0.570788
0.14428
0.028936
1.884702
1.848472
0.178268
7,647
train
H1
H28
200
200
50
49
46
-0.220346
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0.701144
0.700895
2.736554
7.142208
3.138692
-0.220346
0.701144
0.067501
0.491254
0.10815
0.009122
2.30435
2.363803
0.098893
7,647
train
H0
H28
300
300
50
48.666667
48.666667
-0.236705
0.187125
0.276702
0.276224
0.083296
0.346251
0.087761
0.276224
0.276702
0.844534
0.0763
0.045397
0.035001
0.103979
0.152087
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7,647
train
H1
H28
300
300
50
53.666667
48.666667
-0.614654
0.075752
1.352484
1.352185
8.68636
10.676097
9.139632
1.352185
1.352484
0.01036
1.828403
0.431154
0.005739
7.049862
7.040047
-0.085426
7,647
train
H0
H28
500
500
50
49.6
48.4
-0.645782
0.6922
0.565876
0.564904
0.423964
0.674328
0.456311
0.564904
0.6922
0.471191
0.319116
0.396204
0.479169
0.080422
0.072418
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7,647
train
H1
H28
500
500
50
52
49
0.007457
-0.320287
0.392605
0.391991
1.912906
4.3389
2.213159
0.391991
0.392605
0.227118
0.153657
0.000038
0.10258
1.288769
1.406072
0.334757
7,647
train
H0
H28
1,000
1,000
50
48.4
50.7
0.923438
-0.761749
-1.069766
-1.069179
1.243691
2.529275
1.301817
-1.069179
1.069766
0.427591
1.143145
0.87166
0.580241
1.169042
1.217735
0.793322
7,647
train
H1
H28
1,000
1,000
50
48.3
51.3
2.155288
-2.569178
-1.451003
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9.033531
14.242831
9.879479
2.155288
2.569178
0.002593
2.104615
4.288559
6.604024
0.080096
0.098519
2.704464