The breast cancer dataset concerns 569 biopsies of malignant and benign tumors. The dataset provides 30 features extracted from images of fine-needle aspiration biopsies that describe cell nuclei. The images provide information about the shape, size, and texture of each cell nucleus. Furthermore, for each characteristic, three distinct values are provided. The mean, the standard error, and the worst or largest value. This ensures that, for each image, the cell population is adequately described.

The dataset target concerns the diagnosis, that is, whether a tumor is malignant or benign. Thus, this is a classification dataset. The available features are listed as follows:

• Mean radius
• Mean texture
• Mean perimeter
• Mean area
• Mean smoothness
• Mean compactness
• Mean concavity
• Mean concave points
• Mean symmetry
• Mean fractal dimension
• Radius error
• Texture error
• Perimeter error
• Area error
• Smoothness error
• Compactness error
• Concavity error
• Concave points error
• Symmetry error
• Fractal dimension error
• Worst radius
• Worst texture
• Worst perimeter
• Worst area
• Worst smoothness
• Worst compactness
• Worst concavity
• Worst concave points
• Worst symmetry
• Worst fractal dimension