| german {gamclass} | R Documentation |
German credit scoring data
Description
See website for details of data attributes
Usage
german
Format
A data frame with 1000 observations on the following 21 variables.
V1a factor with levels
A11A12A13A14V2a numeric vector
V3a factor with levels
A30A31A32A33A34V4a factor with levels
A40A41A410A42A43A44A45A46A48A49V5a numeric vector
V6a factor with levels
A61A62A63A64A65V7a factor with levels
A71A72A73A74A75V8a numeric vector
V9a factor with levels
A91A92A93A94V10a factor with levels
A101A102A103V11a numeric vector
V12a factor with levels
A121A122A123A124V13a numeric vector
V14a factor with levels
A141A142A143V15a factor with levels
A151A152A153V16a numeric vector
V17a factor with levels
A171A172A173A174V18a factor with levels
goodbadV19a factor with levels
A191A192V20a factor with levels
A201A202V21a numeric vector
Details
700 good and 300 bad credits with 20 predictor variables. Data from 1973 to 1975. Stratified sample from actual credits with bad credits heavily oversampled. A cost matrix can be used.
Source
http://archive.ics.uci.edu/datasets
References
Grömping, U. (2019). South German Credit Data: Correcting a Widely Used Data Set. Report 4/2019, Reports in Mathematics, Physics and Chemistry, Department II, Beuth University of Applied Sciences Berlin.
Examples
data(german)