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pytorch-survival
/
flchain_pycox

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age
float32
50
101
sex
float32
0
1
sample.yr
int64
2k
2k
kappa
float32
0.01
20.5
lambda
float32
0.04
26.6
flc.grp
int64
1
10
creatinine
float32
0.4
10.8
mgus
float32
0
1
event_time
float32
0
5.17k
event_indicator
float32
0
1
97
0
1,997
5.7
4.86
10
1.7
0
85
1
92
0
2,000
0.87
0.683
1
0.9
0
1,281
1
94
0
1,997
4.36
3.85
10
1.4
0
69
1
92
0
1,996
2.42
2.22
9
1
0
115
1
93
0
1,996
1.32
1.69
6
1.1
0
1,039
1
90
0
1,997
2.01
1.86
9
1
0
1,355
1
90
0
1,996
0.43
0.88
1
0.8
0
2,851
1
90
0
1,999
2.47
2.7
10
1.2
0
372
1
93
0
1,996
1.91
2.18
9
1.2
0
3,309
1
91
0
1,996
0.791
2.22
6
0.8
0
1,326
1
96
0
1,996
2.38
2.17
9
1.3
0
2,776
1
90
0
1,996
3.96
3.95
10
1.1
0
1,046
1
90
0
1,996
0.83
1.4
3
0.9
0
667
1
97
0
1,996
4.53
4.08
10
2
0
51
1
90
0
1,996
2.71
1.81
9
1.1
0
1,286
1
93
0
1,997
1.6
1.75
7
0.9
0
1,914
1
95
0
1,997
1.88
2.43
9
1.9
0
874
1
94
0
1,996
2.6
6.7
10
1.8
0
91
1
94
0
1,996
1.8
2.29
9
1
0
1,903
1
92
0
1,996
0.601
1.44
2
1
0
2,000
1
94
0
1,997
2.31
2.08
9
0.9
0
71
1
90
0
1,996
2.19
2.45
9
1.1
0
2,845
0
90
0
1,997
0.802
1.05
2
1.2
0
2,586
1
94
0
1,996
1.31
1.85
7
1
0
24
1
101
0
1,996
1.54
1.73
7
1
0
4
1
90
0
1,996
1.48
1.53
6
1.2
0
2,718
1
91
0
1,996
1.13
1.32
4
1.5
0
85
1
93
0
1,996
1.57
2.25
8
0.8
0
2,498
0
95
0
1,996
2.92
2.91
10
2
0
0
1
91
0
1,996
0.43
0.94
1
0.9
0
2,905
0
93
0
1,996
4.18
4.28
10
1.1
0
371
1
96
0
1,997
3.35
2.34
10
2.4
0
23
1
90
0
1,998
1.08
1.69
5
0.8
0
1,521
1
96
0
1,997
2.1
2.29
9
1.3
0
691
1
92
0
1,997
1.69
1.91
8
1.1
0
1,584
1
91
0
1,996
3.36
3.16
10
1.2
0
283
1
95
0
1,998
2.41
3.35
10
0.9
0
590
1
90
0
1,997
2.26
2.13
9
0.9
0
702
1
92
0
1,996
2.46
2.03
9
1.4
0
227
1
90
0
1,996
2.12
1.5
8
1.3
0
89
1
93
0
1,997
2.76
2.24
10
1.5
0
2,218
1
90
0
1,996
2.48
1.9
9
1.3
0
997
1
94
0
1,997
4.84
6.31
10
1.3
0
553
1
94
0
1,996
3.94
2.7
10
1.5
0
1,754
1
90
0
1,997
4.53
6.88
10
1
0
225
1
97
0
1,996
3.07
2.85
10
1
0
322
1
91
0
1,997
2.74
3.41
10
0.9
0
704
1
92
0
1,996
1.34
1.49
6
0.9
0
881
1
92
0
1,996
2.24
2.72
10
1.2
0
897
1
91
0
1,996
5.15
5.08
10
2.5
0
500
1
94
0
1,998
6.97
7.97
10
2
0
4
1
100
0
1,999
1.82
3.25
10
1.6
0
0
1
90
0
1,997
1.29
2.23
8
1
0
262
1
99
0
1,996
1.3
1.92
7
1
0
1,960
1
96
0
1,995
1.39
2.13
8
1.3
0
937
1
94
0
1,996
1.01
1
2
0.9
0
1,079
1
94
0
1,996
2.17
2.4
9
1
0
48
1
92
0
1,998
1.56
1.51
7
1.1
0
1,298
1
94
0
1,996
3.17
4.14
10
2
0
77
1
90
0
1,996
0.829
0.614
1
1.1
0
2,047
1
93
0
1,996
2.72
3.11
10
1.5
0
455
1
96
0
1,996
1.28
1.7
6
1.1
0
567
1
92
0
1,996
3.12
2.39
10
1.3
0
687
1
95
0
1,996
1.46
1.38
6
0.8
0
630
1
92
0
1,997
1.24
1.03
3
0.7
0
387
1
91
0
1,996
2.04
2.74
10
1.3
0
663
1
93
0
1,996
1.85
1.51
7
1.1
0
1,817
1
93
0
1,996
2.36
2.5
10
1.1
0
899
1
90
0
1,998
3.09
2.89
10
1.4
0
3,230
1
90
0
1,996
4.04
6.77
10
2.1
0
598
1
90
0
1,998
3.02
2.04
10
1.2
0
266
1
96
0
1,996
4.53
3.95
10
1.8
0
673
1
94
0
1,997
4.54
4.81
10
2
0
18
1
90
0
1,995
1.87
1.87
8
1
0
2,048
1
90
0
1,996
2.1
2.8
10
1.6
0
1,207
1
91
0
1,995
3.14
2.85
10
1.1
0
315
0
90
0
1,997
1.76
2.72
9
0.8
0
335
1
97
0
1,996
2.04
3.06
10
1.1
0
108
1
92
0
1,996
2.61
3.48
10
1
0
166
0
93
1
2,000
2.84
2.2
10
1.5
0
191
1
90
1
1,996
6.04
4
10
2.5
0
28
1
96
1
1,996
5.93
5.06
10
1.2
0
705
1
94
1
1,997
1.54
1.9
8
1.6
0
1,126
1
90
1
1,998
3.39
3.42
10
1.8
0
2,743
1
90
1
1,997
1.49
1.91
8
1.3
0
2,177
1
90
1
1,998
1.77
1.92
8
1.1
0
1,069
1
93
1
1,996
3.53
3.83
10
1
0
28
1
90
1
1,996
2.24
3.62
10
1.4
0
213
1
92
1
1,997
1.66
1.51
7
1.4
0
1,457
1
92
1
1,996
4.18
3.09
10
1.6
0
436
1
96
1
1,996
2.01
6.24
10
2
0
57
1
93
1
1,996
2.44
2.12
9
1.3
0
34
1
91
1
1,996
1.88
1.35
7
1
0
2,887
1
90
1
1,996
2.24
2.07
9
1.8
0
750
1
97
1
1,996
3.53
3.9
10
1.1
0
32
1
92
1
1,996
2.4
2.57
10
1
0
984
1
90
1
1,997
2.99
3.32
10
1.6
0
1,210
1
92
1
1,996
2.86
2.99
10
1.5
0
267
1
91
1
1,999
2.47
2.53
10
1.3
0
2,488
1
92
1
1,996
3.07
3.81
10
1.3
0
877
1