breastcancerdiagnostic: Breast cancer diagnostic data

In funcml: Functional Machine Learning Framework

Breast cancer diagnostic data

Description

A binary classification dataset for breast cancer diagnosis using tumor morphology measurements.

Usage

breastcancerdiagnostic

Format

A data frame with 569 rows and 31 variables:

radius_mean

Mean radius.

texture_mean

Mean texture.

perimeter_mean

Mean perimeter.

area_mean

Mean area.

smoothness_mean

Mean smoothness.

compactness_mean

Mean compactness.

concavity_mean

Mean concavity.

concave_pts_mean

Mean number of concave points.

symmetry_mean

Mean symmetry.

fractal_dim_mean

Mean fractal dimension.

radius_se

Radius standard error.

texture_se

Texture standard error.

perimeter_se

Perimeter standard error.

area_se

Area standard error.

smoothness_se

Smoothness standard error.

compactness_se

Compactness standard error.

concavity_se

Concavity standard error.

concave_pts_se

Concave points standard error.

symmetry_se

Symmetry standard error.

fractal_dim_se

Fractal dimension standard error.

radius_worst

Worst radius.

texture_worst

Worst texture.

perimeter_worst

Worst perimeter.

area_worst

Worst area.

smoothness_worst

Worst smoothness.

compactness_worst

Worst compactness.

concavity_worst

Worst concavity.

concave_pts_worst

Worst number of concave points.

symmetry_worst

Worst symmetry.

fractal_dim_worst

Worst fractal dimension.

diagnosis

Diagnosis outcome ("B" = benign, "M" = malignant).

Details

Column names were standardized to snake_case when packaging the data.

Source

Breast Cancer Wisconsin Diagnostic Dataset from the UCI Machine Learning Repository, packaged in dslabs::brca.

Examples

str(funcml::breastcancerdiagnostic)
table(funcml::breastcancerdiagnostic$diagnosis)

funcml documentation built on Aug. 22, 2026, 5:08 p.m.