configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: diagnosis
dtype: string
- name: radius_mean
dtype: float64
- name: texture_mean
dtype: float64
- name: perimeter_mean
dtype: float64
- name: area_mean
dtype: float64
- name: smoothness_mean
dtype: float64
- name: compactness_mean
dtype: float64
- name: concavity_mean
dtype: float64
- name: concave points_mean
dtype: float64
- name: symmetry_mean
dtype: float64
- name: fractal_dimension_mean
dtype: float64
- name: radius_se
dtype: float64
- name: texture_se
dtype: float64
- name: perimeter_se
dtype: float64
- name: area_se
dtype: float64
- name: smoothness_se
dtype: float64
- name: compactness_se
dtype: float64
- name: concavity_se
dtype: float64
- name: concave points_se
dtype: float64
- name: symmetry_se
dtype: float64
- name: fractal_dimension_se
dtype: float64
- name: radius_worst
dtype: float64
- name: texture_worst
dtype: float64
- name: perimeter_worst
dtype: float64
- name: area_worst
dtype: float64
- name: smoothness_worst
dtype: float64
- name: compactness_worst
dtype: float64
- name: concavity_worst
dtype: float64
- name: concave points_worst
dtype: float64
- name: symmetry_worst
dtype: float64
- name: fractal_dimension_worst
dtype: float64
splits:
- name: train
num_bytes: 139405
num_examples: 569
download_size: 141996
dataset_size: 139405
license: cc
language:
- en
pretty_name: breast-cancer-wisconsin
size_categories:
- n<1K
breast-cancer-wisconsin
Overview
The dataset contains features computed from digitized images of breast cancer biopsies, which are used to predict whether a breast mass is benign (non-cancerous) or malignant (cancerous).
Dataset Details
The original dataset is the Breast Cancer Wisconsin (Diagnostic). This file concerns credit card applications. The dataset is based on features computed from digitized images of breast mass tissue samples. These features are computed from a digitized image of a fine needle aspirate (FNA) of a breast mass. Based on these features, the goal is to predict whether the mass is benign or malignant.
@inproceedings{Street1993NuclearFE,
title={Nuclear feature extraction for breast tumor diagnosis},
author={William Nick Street and William H. Wolberg and Olvi L. Mangasarian},
booktitle={Electronic imaging},
year={1993},
url={https://api.semanticscholar.org/CorpusID:14922543}
}
- Dataset Name: breast-cancer-wisconsin
- Language: English
- Total Size: 569 demonstrations
Contents
The dataset consists of a data frame with 30 columns + diagnosis = M (37,3%) and B (62,7%).
How to use
from datasets import load_dataset
dataset = load_dataset("AiresPucrs/breast-cancer-wisconsin", split='train')
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.