pmr (version 1.2.5)

breasttissue: breasttissue

Description

Ranking of 4 breast cancer categories of 106 observations. The original dataset was a categorical one, and it was converted to the current ranking dataset by sorting the expected probabilities (computed by fitting a stepwise logistic regression) of the 4 categories.

Usage

data(breasttissue)

Format

A data frame with 106 observations on the following 4 variables.

adi

the rank of category "adipose"

car

the rank of category "carcinoma"

con

the rank of category "connective"

new

the rank of cateogry "fibro-adenoma, mastopathy or glandular"

Source

Frank, A., Asuncion, A. (2010) UCI Machine Learning Repository. http://archive.ics.uci.edu/ml

Details

The rankings were generated by first fitting a stepwise logistic regression to the original dataset, and then sorted by the expected probabilities of the 4 categories.

References

Jossinet, J. (1996) Variability of impedivity in normal and pathological breast tissue. Medical and Biological Engineering and Computing 34, 346-350.

da Silva, J. E., de Sa, J. P., Jossinet, J. (2000) Classification of breast tissue by electrical impedance spectroscopy. Medical and Biological Engineering and Computing 38, 26-30.

Examples

data(breasttissue)
## maybe str(breasttissue) ; rankagg(breasttissue) ...