File size: 1,908 Bytes
73025cd 3cc7c6e 73025cd 3cc7c6e d726613 73025cd e28185c 27e1ccf e28185c d0aef76 e28185c 27e1ccf | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 | ---
configs:
- config_name: cancer
data_files:
- path: cancer/train.csv
split: train
default: true
language: en
license: cc
pretty_name: Breast
size_categories: 1M<n<10M
tags:
- tabular_classification
- binary_classification
- multiclass_classification
task_categories:
- tabular-classification
---
# Breast cancer
The [Breast cancer dataset](https://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Wisconsin+%28Original%29) from the [UCI ML repository](https://archive.ics.uci.edu/ml/datasets).
Classify cancerousness of the given cell.
# Configurations and tasks
| **Configuration** | **Task** | Description |
|-------------------|---------------------------|---------------------------------------------------------------|
| cancer | Binary classification | Is the cell clump cancerous? |
# Usage
```python
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 | |