ml-code-generator / datasets /patient_survival_prediction.csv
Surbhi
Feature extraction and model training
cedd211
age,blood_pressure,heart_rate,survival_time
16,46,0.13,86
71,73,0.02,46
28,63,0.16,95
36,9,0.42,37
21,13,0.35,52
57,72,0.15,35
94,16,0.98,30
27,37,0.11,65
97,90,0.28,89
92,77,0.47,73
94,95,0.35,25
93,24,0.5,53
93,53,0.84,18
60,28,0.57,2
70,85,0.37,39
20,77,0.87,11
15,95,0.34,40
95,29,0.06,31
76,81,0.31,33
96,86,0.08,60
75,29,0.0,76
38,45,0.92,41
68,73,0.18,49
55,54,0.6,26
59,87,0.06,5
40,27,0.78,56
61,25,0.72,91
66,24,0.25,16
75,67,0.11,40
84,63,0.22,34
15,48,0.5,74
18,67,0.83,84
35,87,0.24,58
41,65,0.73,99
13,40,0.03,17
15,74,0.39,73
35,82,0.26,44
7,25,0.31,47
67,4,0.56,68
99,86,0.57,13
81,42,0.8,55
72,29,0.99,55
39,72,0.49,38
9,89,0.35,17
58,43,0.47,89
73,39,0.9,58
86,87,0.68,92
14,71,0.9,57
16,12,0.06,11
84,90,0.33,25
99,10,0.94,29
79,47,0.58,87
56,25,0.71,11
74,8,0.15,50
98,41,0.72,87
91,35,0.31,41
8,78,0.72,54
55,38,0.1,27
33,63,0.61,52
89,32,0.55,77
65,38,0.11,97
51,61,0.7,22
30,58,0.61,4
34,13,0.72,25
10,65,0.62,52
90,61,0.48,75
96,19,0.94,52
74,70,0.59,8
74,77,0.61,97
38,29,0.74,54
2,26,0.22,75
61,20,0.34,5
89,17,0.46,56
35,72,0.18,33
33,22,0.04,87
14,68,0.46,22
94,91,0.27,90
35,43,0.65,78
85,26,0.6,16
60,56,0.8,60
35,26,0.49,39
84,52,0.4,98
32,24,0.72,12
9,58,0.01,87
62,7,0.91,54
89,23,0.36,51
15,56,0.97,23
97,32,0.05,56
3,48,1.0,97
40,23,0.65,89
14,40,0.96,87
81,89,0.5,67
37,2,0.15,47
16,13,0.92,99
85,10,0.84,89
13,39,0.96,87
3,91,0.17,31
66,54,0.49,47
42,48,0.0,95
34,6,0.98,72