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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