README.md

metadata

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.