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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
70	1	1,996	2.08	2.05	9	1.5	4,761	0
74	1	1,997	1.14	1.2	4	1	1	1
73	1	1,996	0.71	0.96	1	1.2	4,640	0
72	1	1,998	2.14	1.93	9	1.5	639	1
71	1	1,995	2.02	1.41	8	1.2	2,817	1
72	1	1,996	3.03	2.94	10	1.2	3,257	1
74	1	1,996	0.741	1.22	2	1	3,211	0
74	1	1,996	1.92	1.68	8	1.1	1,577	1
74	1	1,998	3.35	3.21	10	1.9	893	1
71	1	1,996	1.28	2.5	8	0.9	3,210	1
70	1	1,995	0.96	1.24	3	1.1	4,946	0
73	1	1,995	1.5	1.78	7	1	4,996	0
70	1	1,995	1.91	2.04	9	1.3	374	1
73	1	1,996	2.13	2.32	9	1.5	4,619	0
72	1	1,995	1.97	1.86	8	2	4,995	0
70	1	1,998	2.73	1.94	9	1.5	2,470	1
73	1	1,995	1.43	1.43	6	1.5	5,005	0
71	1	1,996	0.858	1.08	2	1.1	4,691	0
71	1	1,995	1.23	1.74	6	1.2	4,950	0
74	1	1,999	1.41	2.57	9	1.3	3,555	0
72	1	1,996	0.76	1.64	4	1.2	2,506	1
70	1	1,998	1.26	1.61	6	0.9	524	1
73	1	1,995	3.9	4.62	10	1	80	1
70	1	1,999	0.902	1.92	6	1.3	3,703	0
72	1	1,996	1.59	1.64	7	1.1	4,603	0
74	1	1,996	2.06	2.06	9	1.5	3,005	1
72	1	1,996	1.68	2.13	8	1.2	2,348	1
70	1	1,996	1.78	4.41	10	1.1	4,539	0
71	1	1,998	2.16	2.3	9	1.5	1,000	1
72	1	1,996	1.79	2.16	9	1.1	4,778	0
72	1	1,995	1.41	1.64	6	1.2	3,630	1
74	1	1,996	2.79	3.23	10	1.1	620	1
71	1	2,001	3.52	2.46	10	1.4	1,862	1
73	1	1,996	1.14	1.36	4	0.9	3,588	1
74	1	1,995	1.74	2.16	9	1.1	4,960	0
70	1	1,996	0.62	1.72	4	1.2	2,781	1
72	1	1,995	2.13	1.95	9	1.1	2,449	1
72	1	1,996	1.64	1.26	6	1.3	4,661	0
73	1	1,997	2.17	2.19	9	1.3	4,542	0
70	1	1,996	1.04	2.32	7	1.2	268	1
70	1	2,001	1.25	1.25	4	1	2,889	1
73	1	1,996	0.66	1.23	2	1.3	4,765	0
72	1	1,996	1.09	3.56	9	1.2	3,975	0
73	1	1,996	0.99	1.3	3	1.1	4,830	0
70	1	1,996	1.39	2.56	9	1	4,768	0
73	1	1,996	0.65	1.08	1	1.1	4,925	0
70	1	1,998	2.61	1.98	9	1.1	3,934	0
72	1	1,996	1.69	1.89	8	1.4	1,794	1
70	1	1,995	1.61	1.77	8	1.1	4,984	0
74	1	1,997	1.74	2.41	9	1.1	4,326	0
73	1	1,997	1.33	1.49	6	1.6	4,547	0
70	1	1,996	1.33	1.47	5	1.1	4,822	0
74	1	1,996	1.69	2.27	9	1.7	1,045	1
73	1	2,002	1.24	1.68	6	0.9	2,507	0
72	1	1,995	1.89	2.58	9	0.8	1,945	1
72	1	1,996	9.35	8.67	10	8.9	714	1
70	1	1,996	2.78	3.98	10	2.7	2,892	1
74	1	1,996	2.76	2.85	10	1.9	2,906	1
72	1	1,996	2.35	2.78	10	1.2	3,703	1
73	1	2,001	4.86	5.31	10	2.6	159	1
72	1	1,995	2.39	2.55	10	1.2	3,316	1
72	1	1,996	3.28	3.8	10	1.3	2,964	1
70	1	1,995	0.93	1.36	3	1.2	1,606	1
72	1	1,996	1.74	1.81	8	1.4	738	1
72	1	1,996	1.76	2.26	9	0.9	4,767	0
73	1	1,995	1.65	3.74	10	1.3	4,956	0
72	1	1,995	1.38	5.16	10	1.1	4,999	0
73	1	1,996	0.28	0.95	1	1.1	4,915	0
71	1	2,000	1.37	1.72	7	1.1	1,120	1
73	1	1,995	1.77	1.74	8	1.4	2,970	1
74	1	1,996	3.17	3.88	10	1.2	2,397	1
74	1	1,995	1.98	2.12	9	1.1	4,760	0
70	1	1,997	1.84	3.31	10	1	4,488	0
71	1	1,995	1.21	1.53	5	1.2	4,376	1
71	1	1,995	1.64	1.82	8	1.3	4,960	0
70	1	1,996	1.04	1.25	3	1	4,643	0
73	1	1,996	1.39	1.58	6	1.2	4,908	0
74	1	1,999	6.78	5.28	10	5.5	3,760	0
73	1	1,996	1.93	1.86	8	1.3	4,781	1
74	1	1,996	0.879	1.03	2	1.1	4,645	0
70	1	1,996	2.48	1.78	9	1.3	1,843	1
73	1	2,000	1.46	1.37	6	1.2	3,287	0
70	1	1,996	2.38	2.48	10	1.2	2,973	1
73	1	1,998	3.28	2.37	10	1.1	3,323	1
74	1	1,998	1.5	1.83	7	1	1,212	0
71	1	1,996	1.96	2.59	9	1.2	4,639	0
74	1	1,996	3.32	3.01	10	1.1	1,455	1
72	1	1,998	1.14	1.83	6	1.2	2,787	1
70	1	1,995	1.57	1.38	6	1.1	4,957	0
70	1	1,995	1.12	1.26	4	1.3	4,467	1
70	1	1,996	0.848	1.24	3	0.9	1,108	1
72	1	1,996	1.96	2.21	9	1.6	4,661	0
73	1	1,997	0.89	1.15	2	0.9	4,078	1
73	1	1,996	1.55	1.9	8	1.6	2,629	1
72	1	1,996	2.02	2.13	9	1.2	4,631	0
73	1	1,995	2.76	3.12	10	1.8	1,586	1
73	1	1,996	3.25	3.05	10	1.7	4,922	0
72	1	1,996	1.34	1.09	4	1.2	3,389	1
74	1	1,996	1.45	1.5	6	1.5	1,486	1
70	1	1,995	0.95	1.08	2	0.9	3,730	1

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