Datasets:
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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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