Datasets:

mstz
/

haberman

age int64	year_of_operation int64	number_of_axillary_nodes int64	has_survived_5_years int64
30	1,964	1	1
30	1,962	3	1
30	1,965	0	1
31	1,959	2	1
31	1,965	4	1
33	1,958	10	1
33	1,960	0	1
34	1,959	0	0
34	1,966	9	0
34	1,958	30	1
34	1,960	1	1
34	1,961	10	1
34	1,967	7	1
34	1,960	0	1
35	1,964	13	1
35	1,963	0	1
36	1,960	1	1
36	1,969	0	1
37	1,960	0	1
37	1,963	0	1
37	1,958	0	1
37	1,959	6	1
37	1,960	15	1
37	1,963	0	1
38	1,969	21	0
38	1,959	2	1
38	1,960	0	1
38	1,960	0	1
38	1,962	3	1
38	1,964	1	1
38	1,966	0	1
38	1,966	11	1
38	1,960	1	1
38	1,967	5	1
39	1,966	0	0
39	1,963	0	1
39	1,967	0	1
39	1,958	0	1
39	1,959	2	1
39	1,963	4	1
40	1,958	2	1
40	1,958	0	1
40	1,965	0	1
41	1,960	23	0
41	1,964	0	0
41	1,967	0	0
41	1,958	0	1
41	1,959	8	1
41	1,959	0	1
41	1,964	0	1
41	1,969	8	1
41	1,965	0	1
41	1,965	0	1
42	1,969	1	0
42	1,959	0	0
42	1,958	0	1
42	1,960	1	1
42	1,959	2	1
42	1,961	4	1
42	1,962	20	1
42	1,965	0	1
42	1,963	1	1
43	1,958	52	0
43	1,959	2	0
43	1,964	0	0
43	1,964	0	0
43	1,963	14	1
43	1,964	2	1
43	1,964	3	1
43	1,960	0	1
43	1,963	2	1
43	1,965	0	1
43	1,966	4	1
44	1,964	6	0
44	1,958	9	0
44	1,963	19	0
44	1,961	0	1
44	1,963	1	1
44	1,961	0	1
44	1,967	16	1
45	1,965	6	0
45	1,966	0	0
45	1,967	1	0
45	1,960	0	1
45	1,967	0	1
45	1,959	14	1
45	1,964	0	1
45	1,968	0	1
45	1,967	1	1
46	1,958	2	0
46	1,969	3	0
46	1,962	5	0
46	1,965	20	0
46	1,962	0	1
46	1,958	3	1
46	1,963	0	1
47	1,963	23	0
47	1,962	0	0
47	1,965	0	0
47	1,961	0	1

Haberman

The Haberman dataset from the UCI ML repository. Has the patient survived surgery?

Configuration	Task	Description
sruvival	Binary classification	Has the patient survived surgery?

from datasets import load_dataset

dataset = load_dataset("mstz/haberman", "survival")["train"]