wbca: Wisconsin breast cancer database
In faraway: Functions and Datasets for Books by Julian Faraway
wbca 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
faraway documentation built on Aug. 23, 2022, 5:08 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
| wbca | 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
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.