breasttissue: breasttissue
In pmr: Probability Models for Ranking Data
breasttissue R Documentation
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.
adithe rank of category "adipose"
carthe rank of category "carcinoma"
conthe rank of category "connective"
newthe rank of cateogry "fibro-adenoma, mastopathy or glandular"
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.
Source
Frank, A., Asuncion, A. (2010) UCI Machine Learning Repository. http://archive.ics.uci.edu/ml
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) ...
pmr documentation built on June 24, 2022, 5:06 p.m.
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| breasttissue | R Documentation |
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.
adithe rank of category "adipose"
carthe rank of category "carcinoma"
conthe rank of category "connective"
newthe rank of cateogry "fibro-adenoma, mastopathy or glandular"
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.
Source
Frank, A., Asuncion, A. (2010) UCI Machine Learning Repository. http://archive.ics.uci.edu/ml
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) ...
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.
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