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clump_thickness
int64 | uniformity_of_cell_size
int64 | uniformity_of_cell_shape
int64 | marginal_adhesion
int64 | single_epithelial_cell_size
int64 | bare_nuclei
int64 | bland_chromatin
int64 | normal_nucleoli
int64 | mitoses
int64 | is_cancer
int64 |
|---|---|---|---|---|---|---|---|---|---|
5 | 1 | 1 | 1 | 2 | 1 | 3 | 1 | 1 | 0 |
5 | 4 | 4 | 5 | 7 | 10 | 3 | 2 | 1 | 0 |
3 | 1 | 1 | 1 | 2 | 2 | 3 | 1 | 1 | 0 |
6 | 8 | 8 | 1 | 3 | 4 | 3 | 7 | 1 | 0 |
4 | 1 | 1 | 3 | 2 | 1 | 3 | 1 | 1 | 0 |
8 | 10 | 10 | 8 | 7 | 10 | 9 | 7 | 1 | 1 |
1 | 1 | 1 | 1 | 2 | 10 | 3 | 1 | 1 | 0 |
2 | 1 | 2 | 1 | 2 | 1 | 3 | 1 | 1 | 0 |
2 | 1 | 1 | 1 | 2 | 1 | 1 | 1 | 5 | 0 |
4 | 2 | 1 | 1 | 2 | 1 | 2 | 1 | 1 | 0 |
1 | 1 | 1 | 1 | 1 | 1 | 3 | 1 | 1 | 0 |
2 | 1 | 1 | 1 | 2 | 1 | 2 | 1 | 1 | 0 |
5 | 3 | 3 | 3 | 2 | 3 | 4 | 4 | 1 | 1 |
1 | 1 | 1 | 1 | 2 | 3 | 3 | 1 | 1 | 0 |
8 | 7 | 5 | 10 | 7 | 9 | 5 | 5 | 4 | 1 |
7 | 4 | 6 | 4 | 6 | 1 | 4 | 3 | 1 | 1 |
4 | 1 | 1 | 1 | 2 | 1 | 2 | 1 | 1 | 0 |
4 | 1 | 1 | 1 | 2 | 1 | 3 | 1 | 1 | 0 |
10 | 7 | 7 | 6 | 4 | 10 | 4 | 1 | 2 | 1 |
6 | 1 | 1 | 1 | 2 | 1 | 3 | 1 | 1 | 0 |
7 | 3 | 2 | 10 | 5 | 10 | 5 | 4 | 4 | 1 |
10 | 5 | 5 | 3 | 6 | 7 | 7 | 10 | 1 | 1 |
3 | 1 | 1 | 1 | 2 | 1 | 2 | 1 | 1 | 0 |
1 | 1 | 1 | 1 | 2 | 1 | 3 | 1 | 1 | 0 |
5 | 2 | 3 | 4 | 2 | 7 | 3 | 6 | 1 | 1 |
3 | 2 | 1 | 1 | 1 | 1 | 2 | 1 | 1 | 0 |
5 | 1 | 1 | 1 | 2 | 1 | 2 | 1 | 1 | 0 |
2 | 1 | 1 | 1 | 2 | 1 | 2 | 1 | 1 | 0 |
1 | 1 | 3 | 1 | 2 | 1 | 1 | 1 | 1 | 0 |
3 | 1 | 1 | 1 | 1 | 1 | 2 | 1 | 1 | 0 |
2 | 1 | 1 | 1 | 2 | 1 | 3 | 1 | 1 | 0 |
10 | 7 | 7 | 3 | 8 | 5 | 7 | 4 | 3 | 1 |
2 | 1 | 1 | 2 | 2 | 1 | 3 | 1 | 1 | 0 |
3 | 1 | 2 | 1 | 2 | 1 | 2 | 1 | 1 | 0 |
2 | 1 | 1 | 1 | 2 | 1 | 2 | 1 | 1 | 0 |
10 | 10 | 10 | 8 | 6 | 1 | 8 | 9 | 1 | 1 |
6 | 2 | 1 | 1 | 1 | 1 | 7 | 1 | 1 | 0 |
5 | 4 | 4 | 9 | 2 | 10 | 5 | 6 | 1 | 1 |
2 | 5 | 3 | 3 | 6 | 7 | 7 | 5 | 1 | 1 |
10 | 4 | 3 | 1 | 3 | 3 | 6 | 5 | 2 | 1 |
6 | 10 | 10 | 2 | 8 | 10 | 7 | 3 | 3 | 1 |
5 | 6 | 5 | 6 | 10 | 1 | 3 | 1 | 1 | 1 |
10 | 10 | 10 | 4 | 8 | 1 | 8 | 10 | 1 | 1 |
1 | 1 | 1 | 1 | 2 | 1 | 2 | 1 | 2 | 0 |
3 | 7 | 7 | 4 | 4 | 9 | 4 | 8 | 1 | 1 |
1 | 1 | 1 | 1 | 2 | 1 | 2 | 1 | 1 | 0 |
4 | 1 | 1 | 3 | 2 | 1 | 3 | 1 | 1 | 0 |
7 | 8 | 7 | 2 | 4 | 8 | 3 | 8 | 2 | 1 |
9 | 5 | 8 | 1 | 2 | 3 | 2 | 1 | 5 | 1 |
5 | 3 | 3 | 4 | 2 | 4 | 3 | 4 | 1 | 1 |
10 | 3 | 6 | 2 | 3 | 5 | 4 | 10 | 2 | 1 |
5 | 5 | 5 | 8 | 10 | 8 | 7 | 3 | 7 | 1 |
10 | 5 | 5 | 6 | 8 | 8 | 7 | 1 | 1 | 1 |
10 | 6 | 6 | 3 | 4 | 5 | 3 | 6 | 1 | 1 |
8 | 10 | 10 | 1 | 3 | 6 | 3 | 9 | 1 | 1 |
8 | 2 | 4 | 1 | 5 | 1 | 5 | 4 | 4 | 1 |
5 | 2 | 3 | 1 | 6 | 10 | 5 | 1 | 1 | 1 |
9 | 5 | 5 | 2 | 2 | 2 | 5 | 1 | 1 | 1 |
5 | 3 | 5 | 5 | 3 | 3 | 4 | 10 | 1 | 1 |
1 | 1 | 1 | 1 | 2 | 2 | 2 | 1 | 1 | 0 |
9 | 10 | 10 | 1 | 10 | 8 | 3 | 3 | 1 | 1 |
6 | 3 | 4 | 1 | 5 | 2 | 3 | 9 | 1 | 1 |
1 | 1 | 1 | 1 | 2 | 1 | 2 | 1 | 1 | 0 |
10 | 4 | 2 | 1 | 3 | 2 | 4 | 3 | 10 | 1 |
4 | 1 | 1 | 1 | 2 | 1 | 3 | 1 | 1 | 0 |
5 | 3 | 4 | 1 | 8 | 10 | 4 | 9 | 1 | 1 |
8 | 3 | 8 | 3 | 4 | 9 | 8 | 9 | 8 | 1 |
1 | 1 | 1 | 1 | 2 | 1 | 3 | 2 | 1 | 0 |
5 | 1 | 3 | 1 | 2 | 1 | 2 | 1 | 1 | 0 |
6 | 10 | 2 | 8 | 10 | 2 | 7 | 8 | 10 | 1 |
1 | 3 | 3 | 2 | 2 | 1 | 7 | 2 | 1 | 0 |
9 | 4 | 5 | 10 | 6 | 10 | 4 | 8 | 1 | 1 |
10 | 6 | 4 | 1 | 3 | 4 | 3 | 2 | 3 | 1 |
1 | 1 | 2 | 1 | 2 | 2 | 4 | 2 | 1 | 0 |
1 | 1 | 4 | 1 | 2 | 1 | 2 | 1 | 1 | 0 |
5 | 3 | 1 | 2 | 2 | 1 | 2 | 1 | 1 | 0 |
3 | 1 | 1 | 1 | 2 | 3 | 3 | 1 | 1 | 0 |
2 | 1 | 1 | 1 | 3 | 1 | 2 | 1 | 1 | 0 |
2 | 2 | 2 | 1 | 1 | 1 | 7 | 1 | 1 | 0 |
4 | 1 | 1 | 2 | 2 | 1 | 2 | 1 | 1 | 0 |
5 | 2 | 1 | 1 | 2 | 1 | 3 | 1 | 1 | 0 |
3 | 1 | 1 | 1 | 2 | 2 | 7 | 1 | 1 | 0 |
3 | 5 | 7 | 8 | 8 | 9 | 7 | 10 | 7 | 1 |
5 | 10 | 6 | 1 | 10 | 4 | 4 | 10 | 10 | 1 |
3 | 3 | 6 | 4 | 5 | 8 | 4 | 4 | 1 | 1 |
3 | 6 | 6 | 6 | 5 | 10 | 6 | 8 | 3 | 1 |
4 | 1 | 1 | 1 | 2 | 1 | 3 | 1 | 1 | 0 |
2 | 1 | 1 | 2 | 3 | 1 | 2 | 1 | 1 | 0 |
1 | 1 | 1 | 1 | 2 | 1 | 3 | 1 | 1 | 0 |
3 | 1 | 1 | 2 | 2 | 1 | 1 | 1 | 1 | 0 |
4 | 1 | 1 | 1 | 2 | 1 | 3 | 1 | 1 | 0 |
1 | 1 | 1 | 1 | 2 | 1 | 2 | 1 | 1 | 0 |
2 | 1 | 1 | 1 | 2 | 1 | 3 | 1 | 1 | 0 |
1 | 1 | 1 | 1 | 2 | 1 | 3 | 1 | 1 | 0 |
2 | 1 | 1 | 2 | 2 | 1 | 1 | 1 | 1 | 0 |
5 | 1 | 1 | 1 | 2 | 1 | 3 | 1 | 1 | 0 |
9 | 6 | 9 | 2 | 10 | 6 | 2 | 9 | 10 | 1 |
7 | 5 | 6 | 10 | 5 | 10 | 7 | 9 | 4 | 1 |
10 | 3 | 5 | 1 | 10 | 5 | 3 | 10 | 2 | 1 |
2 | 3 | 4 | 4 | 2 | 5 | 2 | 5 | 1 | 1 |
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Breast cancer
The Breast cancer dataset from the UCI ML repository. Classify cancerousness of the given cell.
Configurations and tasks
| Configuration | Task | Description |
|---|---|---|
| cancer | Binary classification | Is the cell clump cancerous? |
Usage
from datasets import load_dataset
dataset = load_dataset("mstz/breast", "cancer")["train"]
Features
| Name | Type | Description |
|---|---|---|
clump_thickness |
int8 |
Thickness of the clump |
uniformity_of_cell_size |
int8 |
Uniformity of cell size |
uniformity_of_cell_shape |
int8 |
Uniformity of cell shape |
marginal_adhesion |
int8 |
Marginal adhesion |
single_epithelial_cell_size |
int8 |
single_epithelial_cell_size |
bare_nuclei |
int8 |
bare_nuclei |
bland_chromatin |
int8 |
bland_chromatin |
normal_nucleoli |
int8 |
normal_nucleoli |
mitoses |
int8 |
mitoses |
| is_cancer | int8 |
Is the clump cancer |
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