Breast Cancer Dataset Data Card

Description:
The Breast Cancer dataset consists of features computed from a digitized image of a fine needle aspirate (FNA) of a breast mass. These features describe characteristics of cell nuclei present in the image.

Attributes:

ID: Unique identifier for each sample.
Diagnosis: The diagnosis of the breast mass (Malignant - M, Benign - B).
Radius Mean: Mean of distances from the center to points on the perimeter.
Texture Mean: Standard deviation of gray-scale values.
Perimeter Mean: Mean size of the core tumor.
Area Mean: Mean area of the core tumor.
Smoothness Mean: Mean smoothness of the cell nuclei.
Compactness Mean: Mean compactness of the cell nuclei.
Concavity Mean: Mean concavity of the cell nuclei.
Concave Points Mean: Mean number of concave portions of the contour.
Symmetry Mean: Mean symmetry of the cell nuclei.
Fractal Dimension Mean: Mean "coastline approximation" - 1.
Target Variable:

Diagnosis: Malignant (M) or Benign (B).
Usage:
This dataset can be used to develop predictive models to classify breast masses as either malignant or benign based on the provided features.