| wbca {faraway} | R Documentation |
Wisconsin breast cancer database
Description
Data come from a study of breast cancer in Wisconsin. There are 681 cases of potentially cancerous tumors of which 238 are actually malignant. Determining whether a tumor is really malignant is traditionally determined by an invasive surgical procedure. The purpose of this study was to determine whether a new procedure called fine needle aspiration which draws only a small sample of tissue could be effective in determining tumor status.
Format
A data frame with 681 observations on the following 10 variables.
- Class
0 if malignant, 1 if benign
- Adhes
marginal adhesion
- BNucl
bare nuclei
- Chrom
bland chromatin
- Epith
epithelial cell size
- Mitos
mitoses
- NNucl
normal nucleoli
- Thick
clump thickness
- UShap
cell shape uniformity
- USize
cell size uniformity
Details
The predictor values are determined by a doctor observing the cells and rating them on a scale from 1 (normal) to 10 (most abnormal) with respect to the particular characteristic.
Source
Bennett, K.,P., and Mangasarian, O.L., Neural network training via linear programming. In P. M. Pardalos, editor, Advances in Optimization and Parallel Computing, pages 56-57. Elsevier Science, 1992