Description Usage Format Details Source References Examples

See website for details of data attributes

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A data frame with 1000 observations on the following 21 variables.

`V1`

a factor with levels

`A11`

`A12`

`A13`

`A14`

`V2`

a numeric vector

`V3`

a factor with levels

`A30`

`A31`

`A32`

`A33`

`A34`

`V4`

a factor with levels

`A40`

`A41`

`A410`

`A42`

`A43`

`A44`

`A45`

`A46`

`A48`

`A49`

`V5`

a numeric vector

`V6`

a factor with levels

`A61`

`A62`

`A63`

`A64`

`A65`

`V7`

a factor with levels

`A71`

`A72`

`A73`

`A74`

`A75`

`V8`

a numeric vector

`V9`

a factor with levels

`A91`

`A92`

`A93`

`A94`

`V10`

a factor with levels

`A101`

`A102`

`A103`

`V11`

a numeric vector

`V12`

a factor with levels

`A121`

`A122`

`A123`

`A124`

`V13`

a numeric vector

`V14`

a factor with levels

`A141`

`A142`

`A143`

`V15`

a factor with levels

`A151`

`A152`

`A153`

`V16`

a numeric vector

`V17`

a factor with levels

`A171`

`A172`

`A173`

`A174`

`V18`

a factor with levels

`good`

`bad`

`V19`

a factor with levels

`A191`

`A192`

`V20`

a factor with levels

`A201`

`A202`

`V21`

a numeric vector

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.

http://archive.ics.uci.edu/ml/index.php

GrÃ¶mping, 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.

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