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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	mgus float32 0 1	event_time float32 0 5.17k	event_indicator float32 0 1
82	0	1,995	1.6	2.41	9	0.9	0	4,957	0
80	0	1,998	1.9	1.41	7	1	0	795	1
88	0	1,996	1.67	1.84	8	1.3	0	1,318	1
84	0	1,996	0.884	1.61	4	1	0	4,435	0
80	0	1,998	3.78	2.93	10	1.2	0	1,868	1
82	0	1,996	0.4	1.2	1	0.9	0	1,567	0
86	0	1,997	1.79	3.47	10	1.2	0	170	1
84	0	1,996	2.36	4.85	10	0.9	0	1,071	1
81	0	1,996	1.68	1.3	6	0.8	0	1,996	1
83	0	1,998	1.8	1.83	8	0.9	0	75	0
84	0	1,995	1.24	1.73	6	1.1	0	2,617	1
80	0	1,996	3.81	2.94	10	1	0	771	1
83	0	1,996	1.54	1.4	6	0.9	0	1,517	1
85	0	1,997	2.03	1.56	8	1.1	0	4,292	1
80	0	1,995	0.63	1.06	1	0.9	0	4,601	1
81	0	2,001	1.03	0.996	2	1	0	1,545	1
89	0	1,996	3.36	3.86	10	1.6	0	522	1
88	0	1,997	1.49	1.75	7	0.9	0	1,813	1
87	0	1,996	1.65	1.39	6	0.8	0	2,713	1
86	0	1,996	1.78	2.03	8	1	0	2,497	1
84	0	1,999	5.96	6.69	10	3.4	0	48	1
81	0	1,997	1.28	2.34	8	1.4	0	1,885	1
81	0	1,996	1.85	1.75	8	0.9	0	4,564	1
86	0	1,996	1.1	1.48	5	0.9	0	816	1
83	0	1,996	1.06	1.09	3	1.5	0	147	1
87	0	1,996	2.04	2.57	9	1	0	2,959	1
82	0	1,995	3.6	3.18	10	0.8	0	2,926	1
82	0	1,998	2.08	1.97	9	0.9	0	440	1
87	0	1,997	1.79	2.05	8	1.1	0	1,306	1
89	0	1,998	2.44	1.69	9	0.9	0	1,744	0
89	0	1,996	0.997	1.99	6	0.8	1	1,220	1
75	1	1,996	1.62	2.49	9	1.2	0	3,934	1
76	1	1,995	1.78	2.43	9	1.1	0	4,736	1
77	1	1,996	1.15	1.29	4	1.1	0	4,605	0
77	1	1,998	1.4	1.24	5	1.2	0	1,552	1
76	1	1,996	11.9	12.3	10	10	0	767	1
78	1	1,995	1.85	1.46	7	1.2	0	1,517	1
75	1	1,996	3.23	3.61	10	1.3	0	4,698	0
77	1	1,996	2.01	2.1	9	1.3	0	2,446	1
77	1	1,996	1.82	1.35	7	1	0	4,634	0
76	1	1,997	2.51	2.25	10	1.3	0	403	1
77	1	1,996	1.13	2.14	7	1.3	0	2,303	1
76	1	1,999	2.26	1.65	9	1.3	0	3,554	0
76	1	1,997	2.04	1.58	8	1.4	0	4,513	0
75	1	1,995	0.86	1.34	3	1.3	0	3,111	1
77	1	1,996	1.29	2.38	8	1.1	0	4,920	0
76	1	2,000	0.912	1.17	3	1.1	0	3,304	0
76	1	1,996	1.88	1.52	8	1.2	0	4,592	0
77	1	1,998	0.916	1.17	3	1.2	0	4,127	0
75	1	1,998	3.51	2.36	10	1.4	0	104	1
76	1	2,000	1.61	1.7	7	0.9	0	1,828	1
75	1	1,996	1.24	1.09	3	1.3	0	4,610	0
79	1	1,996	2.6	2.42	10	1.2	0	2,217	1
78	1	1,995	0.99	1.02	2	1.1	0	4,650	1
78	1	1,996	2.19	1.57	8	1.3	0	3,906	1
76	1	1,995	1.47	2.85	9	1.2	0	706	1
78	1	1,995	1.67	1.68	7	1.2	0	3,365	1
76	1	1,996	1.69	1.24	6	1.3	0	4,017	1
77	1	1,995	1.03	1.69	5	1.2	0	4,969	0
78	1	1,995	3.44	5.18	10	1.4	0	6	1
79	1	1,996	1.2	1.27	4	1.1	0	4,667	0
77	1	1,996	2.12	1.81	9	1.4	0	4,618	0
77	1	1,996	1.1	1.7	5	0.9	0	4,405	1
77	1	1,995	2.25	1.92	9	1.1	0	578	1
79	1	1,996	1.29	0.922481	3	1.3	0	1,860	1
78	1	1,996	4.91	8.89	10	1.7	0	860	1
78	1	1,996	1.17	1.28	4	0.9	0	4,296	1
75	1	1,997	3.1	2.86	10	1.6	0	4,255	0
76	1	1,996	2.56	2.11	9	1.5	0	4,757	0
75	1	2,001	2.25	2.01	9	1.2	0	930	1
77	1	1,996	1.63	1.46	7	1	0	1,601	1
76	1	1,996	1.43	1.31	5	1.4	0	4,655	0
75	1	1,996	1.08	0.96	2	1.1	0	4,920	0
78	1	1,996	1.92	2.4	9	1.3	0	977	1
75	1	1,997	0.915	1.26	3	1.5	0	2,954	1
79	1	1,997	2.07	1.9	9	1.2	0	2,169	1
76	1	1,998	3.62	2.44	10	1.3	0	1,513	1
75	1	1,996	1.12	1.86	6	1.2	0	4,891	0
75	1	1,995	1.26	1.56	6	0.8	0	5,103	0
75	1	1,997	2.93	2.66	10	1.1	0	4,415	0
79	1	1,996	2.83	2.2	10	1.9	0	3,933	1
78	1	1,996	3.36	3.21	10	1.3	0	3,714	1
76	1	1,996	1.36	1.81	7	1.2	0	4,659	0
78	1	1,996	1.88	2.11	9	1.1	0	4,205	1
77	1	1,996	0.9	1.06	2	1.2	0	1,103	1
76	1	1,996	2.43	2.21	9	1.5	0	2,219	1
75	1	1,997	2.16	2.12	9	1.1	0	2,383	1
75	1	1,996	2.17	2.53	9	1.2	0	1,944	1
75	1	1,995	1.37	1.48	6	1.3	0	4,056	1
75	1	1,999	3.42	4.35	10	2.1	0	42	1
79	1	1,996	0.42	0.89	1	1.2	0	4,304	1
75	1	1,996	2.05	1.75	8	1	0	272	1
76	1	1,995	1.23	1.62	6	0.9	0	834	1
77	1	1,996	1.25	1.23	4	1.1	0	1,143	1
77	1	1,996	1.48	1.82	7	1.3	0	2,348	1
79	1	1,997	2.17	2.27	9	1	0	3,728	1
75	1	1,996	2.02	2.1	9	1.2	0	1,033	1
78	1	1,995	1.41	1.46	6	1	0	3,097	1
75	1	1,995	2.06	2.48	9	1.4	0	2,148	1
75	1	1,996	8.84	8.2	10	1.1	0	44	1

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