[−][src]Module smartcore::dataset::breast_cancer
Breast Cancer Wisconsin (Diagnostic) Data Set
Diagnostic Wisconsin Breast Cancer database
| Number of Instances | Number of Attributes | Missing Values? | Associated Tasks: |
|---|---|---|---|
| 569 | 30 | No | Classification |
Breast Cancer was collected by Dr. William H. Wolberg, W. Nick Street and Olvi L. Mangasarian. Features are computed from a digitized image of a fine needle aspirate (FNA) of a breast mass and describe characteristics of the cell nuclei present in the image. The dataset has following attributes:
| Predictor | Data Type | Target? |
|---|---|---|
| Radius (mean of distances from center to points on the perimeter) | Numerical | No |
| Texture (standard deviation of gray-scale values) | Numerical | No |
| Perimeter | Numerical | No |
| Area | Numerical | No |
| Smoothness (local variation in radius lengths) | Numerical | No |
| Compactness (perimeter^2 / area - 1.0) | Numerical | No |
| Concavity (severity of concave portions of the contour) | Numerical | No |
| Concave points (number of concave portions of the contour) | Numerical | No |
| Symmetry | Numerical | No |
| Fractal dimension ("coastline approximation" - 1) | Numerical | No |
| Has cancer | Nominal | Yes |
The mean, standard error, and "worst" or largest (mean of the three worst/largest values) of these features were computed for each image, resulting in 30 features. For instance, field 0 is Mean Radius, field 10 is Radius SE, field 20 is Worst Radius.
Functions
| load_dataset | Get dataset |