Datasets:
age int8 18 96 | lesion_shape stringclasses 4 values | margin stringclasses 5 values | density stringclasses 4 values | is_severe class label 2 classes |
|---|---|---|---|---|
67 | lobular | spiculated | low | 1yes |
58 | irregular | spiculated | low | 1yes |
28 | round | circumbscribed | low | 0no |
57 | round | spiculated | low | 1yes |
76 | round | ill-defined | low | 1yes |
42 | oval | circumbscribed | low | 1yes |
36 | lobular | circumbscribed | iso | 0no |
60 | oval | circumbscribed | iso | 0no |
54 | round | circumbscribed | low | 0no |
52 | lobular | ill-defined | low | 0no |
59 | oval | circumbscribed | low | 1yes |
54 | round | circumbscribed | low | 1yes |
56 | irregular | obscured | high | 1yes |
42 | irregular | ill-defined | low | 1yes |
59 | oval | ill-defined | low | 1yes |
75 | irregular | spiculated | low | 1yes |
45 | irregular | spiculated | low | 1yes |
55 | irregular | ill-defined | low | 0no |
46 | round | spiculated | iso | 0no |
54 | irregular | ill-defined | low | 1yes |
57 | irregular | ill-defined | low | 1yes |
39 | round | circumbscribed | iso | 0no |
81 | round | circumbscribed | low | 0no |
60 | oval | circumbscribed | low | 0no |
67 | lobular | ill-defined | iso | 1yes |
55 | lobular | ill-defined | iso | 0no |
78 | round | circumbscribed | high | 0no |
50 | round | circumbscribed | low | 0no |
62 | lobular | spiculated | iso | 1yes |
64 | irregular | spiculated | low | 1yes |
67 | irregular | spiculated | low | 1yes |
74 | oval | circumbscribed | iso | 0no |
80 | lobular | spiculated | low | 1yes |
49 | oval | circumbscribed | high | 0no |
52 | irregular | obscured | low | 1yes |
60 | irregular | obscured | low | 1yes |
57 | oval | spiculated | low | 0no |
74 | irregular | ill-defined | low | 1yes |
49 | round | circumbscribed | low | 0no |
45 | oval | circumbscribed | low | 0no |
64 | oval | circumbscribed | low | 0no |
73 | oval | circumbscribed | iso | 0no |
68 | irregular | obscured | low | 1yes |
52 | irregular | spiculated | low | 0no |
66 | irregular | ill-defined | low | 1yes |
25 | round | circumbscribed | low | 0no |
74 | round | circumbscribed | iso | 1yes |
64 | round | circumbscribed | low | 0no |
60 | irregular | obscured | iso | 1yes |
67 | oval | ill-defined | high | 0no |
67 | irregular | spiculated | low | 0no |
44 | irregular | ill-defined | iso | 1yes |
68 | round | circumbscribed | low | 1yes |
58 | irregular | ill-defined | low | 1yes |
62 | round | spiculated | low | 1yes |
73 | lobular | ill-defined | low | 1yes |
80 | irregular | ill-defined | low | 1yes |
59 | oval | circumbscribed | low | 1yes |
54 | irregular | ill-defined | low | 1yes |
62 | irregular | ill-defined | low | 0no |
33 | oval | circumbscribed | low | 0no |
57 | round | circumbscribed | low | 0no |
45 | irregular | ill-defined | low | 0no |
71 | irregular | ill-defined | low | 1yes |
59 | irregular | ill-defined | iso | 0no |
56 | round | circumbscribed | low | 0no |
57 | oval | circumbscribed | iso | 0no |
55 | lobular | ill-defined | low | 1yes |
84 | irregular | spiculated | low | 0no |
51 | irregular | ill-defined | low | 1yes |
24 | oval | circumbscribed | iso | 0no |
66 | round | circumbscribed | low | 0no |
33 | irregular | ill-defined | low | 0no |
59 | irregular | obscured | iso | 0no |
40 | irregular | spiculated | low | 1yes |
67 | irregular | ill-defined | low | 1yes |
75 | irregular | obscured | low | 1yes |
86 | irregular | ill-defined | low | 0no |
66 | irregular | ill-defined | low | 1yes |
46 | irregular | spiculated | low | 1yes |
59 | irregular | ill-defined | low | 1yes |
65 | irregular | ill-defined | low | 1yes |
53 | round | circumbscribed | low | 0no |
67 | lobular | spiculated | low | 1yes |
80 | irregular | spiculated | low | 1yes |
55 | oval | circumbscribed | low | 0no |
47 | round | circumbscribed | iso | 0no |
62 | irregular | spiculated | low | 1yes |
63 | irregular | ill-defined | low | 1yes |
71 | irregular | ill-defined | low | 1yes |
41 | round | circumbscribed | low | 0no |
57 | irregular | ill-defined | fat-containing | 1yes |
71 | irregular | ill-defined | fat-containing | 1yes |
66 | round | circumbscribed | low | 0no |
47 | oval | ill-defined | iso | 0no |
34 | irregular | ill-defined | low | 0no |
59 | lobular | ill-defined | low | 0no |
67 | irregular | ill-defined | low | 1yes |
41 | oval | circumbscribed | low | 0no |
23 | lobular | circumbscribed | low | 0no |
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YAML Metadata Error: "configs[0]" must be of type object
Mammography
The Mammography dataset from the UCI ML repository.
Configurations and tasks
| Configuration | Task | Description |
|---|---|---|
| mammography | Binary classification | Is the lesion benign? |
Usage
from datasets import load_dataset
dataset = load_dataset("mstz/mammography")["train"]
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