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pytorch-survival
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flchain_pycox

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train · 6.52k rows

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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	event_time float32 0 5.17k	event_indicator float32 0 1
80	1	1,997	1.28	1.77	6	1.1	3,336	1
84	1	1,996	2.94	2.13	10	1.3	3,329	0
82	1	1,996	1.47	1.88	7	1.2	3,096	1
86	1	1,996	3.95	3.27	10	2	2,819	1
83	1	1,995	1.9	2.71	9	1.3	4,964	0
82	1	1,997	1.75	2.12	9	1	1,874	1
80	1	1,995	1.89	1.97	9	1	2,651	1
81	1	1,996	2.05	2.5	9	1.4	921	1
81	1	1,996	1.82	2.33	9	1.1	391	1
84	1	1,997	2.61	2.57	10	1.2	670	1
84	1	1,995	2.15	1.96	9	1.6	2,845	0
82	1	1,997	0.875	1.45	3	0.9	3,795	0
83	1	1,995	1.24	1.56	5	1.1	4,673	1
85	1	1,997	3.6	3.84	10	1.6	681	1
82	1	1,997	2.06	2.75	10	1.5	2,635	1
89	1	1,996	10.4	11.2	10	1.6	392	1
82	1	1,999	2.41	1.99	9	1.4	3,710	1
86	1	1,996	3.23	3.13	10	1.5	2,344	1
81	1	1,996	1.74	1.6	7	1.3	4,751	0
81	1	1,996	1.54	1.66	7	1.3	233	1
81	1	1,998	4.77	4.46	10	1.5	975	1
88	1	1,998	3.1	3.14	10	1.8	1,261	1
85	1	1,997	2.03	2.79	10	1.2	839	1
87	1	1,997	5.11	5.68	10	1.6	124	1
80	1	1,996	2.36	3.74	10	1.6	4,823	0
84	1	1,996	3.51	3.33	10	1.2	797	1
81	1	1,995	1.39	1.79	7	1.2	4,116	1
85	1	1,996	2.45	1.6	9	0.9	340	1
81	1	1,996	1.64	1.69	7	1	718	1
88	1	1,995	2.5	2.32	10	1.4	1,883	1
82	1	1,997	3.97	5.42	10	1.4	271	1
84	1	1,996	1.08	1.95	6	1.4	1,856	1
84	1	1,996	0.73	1.17	2	0.9	4,530	1
86	1	1,995	0.97	0.89	2	1.1	130	1
83	1	1,996	2.61	1.88	9	1.4	1,216	1
85	1	1,996	2.54	3.66	10	1.4	23	1
89	1	1,995	1.4	1.54	6	1.3	1,163	1
81	1	1,995	0.72	0.71	1	1.1	4,992	0
81	1	1,995	0.68	1.23	2	1	1,330	1
86	1	1,996	2.15	1.76	9	1	2,380	1
80	1	1,995	0.69	1.63	3	1.1	114	1
84	1	1,997	2.1	2.67	10	1.2	4,531	0
87	1	1,996	2.95	9.23	10	1.3	398	1
83	1	1,997	2.11	1.97	9	1.1	4,541	0
83	1	1,995	1.4	1.44	6	1	2,896	1
82	1	2,001	2.34	2.84	10	2.3	419	1
82	1	1,998	2.38	2.74	10	1.9	2,658	1
83	1	1,997	1.87	2.9	10	1.4	1,271	1
82	1	1,996	1.83	2.02	8	1.5	1,107	1
84	1	1,995	2.78	3.14	10	3.3	2,267	1
88	1	1,995	2.63	2.15	10	1.4	231	1
84	1	1,996	1.74	4.27	10	1.3	3,139	1
82	1	1,995	3.16	2.8	10	1	1,881	1
80	1	1,997	0.259	0.32	1	1	3,399	1
83	1	1,996	2.13	1.77	9	3	2,008	1
83	1	1,996	1.61	1.33	6	1.1	2,336	1
83	1	1,996	2.58	2.99	10	2.9	282	1
82	1	1,996	1.26	1.58	6	0.9	1,928	1
84	1	1,995	2.25	2.64	10	1.1	3,558	1
83	1	1,997	1.54	2.85	9	2.7	1,021	1
80	1	1,997	1.48	2.13	8	1.3	4,400	0
82	1	1,996	1.71	1.2	6	1.3	1,577	1
83	1	1,996	1.36	1.29	5	1.1	3,395	1
85	1	1,995	1.19	1.2	4	1.4	230	1
80	1	1,995	1.99	2.58	9	1.2	3,837	1
81	1	1,995	2.05	4.21	10	1.3	10	1
81	1	1,997	1.34	1.53	6	1.2	4,386	0
83	1	1,996	4.93	5.51	10	0.9	1,338	1
85	1	1,998	1.88	2.19	9	1	1,867	1
83	1	1,996	5.26	3.38	10	2.2	1,673	1
84	1	1,996	1.73	2.06	8	1.5	432	1
81	1	1,996	1.14	1.98	7	1	1,645	1
81	1	1,996	0.78	1.02	2	1.4	3,399	1
84	1	1,996	3.43	5.22	10	1.7	744	1
82	1	1,996	2.2	2.94	10	1	641	1
83	1	1,996	3.5	3.44	10	1.3	1,766	1
88	1	1,996	2.21	2.14	9	0.8	2,035	1
80	1	1,996	2.96	2.68	10	1.4	197	1
88	1	1,995	1.45	1.64	7	1.2	3,146	1
80	1	1,998	1.32	0.976	3	1.1	3,589	1
80	1	1,996	1.52	3.8	10	1.3	2,925	1
80	1	1,995	1.4	2.09	8	1.6	1,058	1
87	1	1,996	1.55	2.71	9	1.5	1,183	1
83	1	1,995	1.42	1.41	6	1.3	666	1
87	1	1,999	2.84	2.14	10	1	520	1
81	1	1,999	2.27	2.06	9	1.2	3,774	0
80	1	1,996	1.25	1.49	5	1.1	1,317	1
83	1	1,996	2.8	5.19	10	2.3	672	1
81	1	1,997	1.68	1.46	7	1	2,434	1
80	1	1,995	1.66	1.53	7	1	5,005	0
88	1	1,996	1.97	1.89	9	1.1	3,068	1
81	1	1,997	2.21	3.45	10	1.4	3,223	1
82	1	1,997	1.56	2.29	8	1.5	3,258	1
85	1	1,996	1.61	1.34	6	1.7	783	1
83	1	1,995	2.79	2.22	10	2	1,897	1
82	1	1,998	1.23	1.94	7	1.1	3,912	0
84	1	2,001	2.7	3.13	10	1	130	1
87	1	1,999	3.6	2.61	10	2.6	97	1
83	1	1,996	1.5	1.88	8	1.7	3,236	1
81	1	1,995	1.2	1.75	6	1	2,591	1

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