evtree (version 1.0-2)

GermanCredit: Statlog German Credit

Description

The dataset contains data of past credit applicants. The applicants are rated as good or bad. Models of this data can be used to determine if new applicants present a good or bad credit risk.

Usage

data("GermanCredit")

Format

A data frame containing 1,000 observations on 21 variables.

Source

The original data was provided by: Professor Dr. Hans Hofmann, Institut fuer Statistik und Oekonometrie, Universitaet Hamburg, FB Wirtschaftswissenschaften, Von-Melle-Park 5, 2000 Hamburg 13 The dataset has been taken from the UCI Repository Of Machine Learning Databases at http://archive.ics.uci.edu/ml/.

Details

The use of a cost matrix is suggested for this dataset. It is worse to class a customer as good when they are bad (cost = 5), than it is to class a customer as bad when they are good (cost = 1).

Examples

data("GermanCredit")
summary(GermanCredit)
## Not run: 
# gcw <- array(1, nrow(GermanCredit))
# gcw[GermanCredit$credit_risk == "bad"] <- 5
# set.seed(1090)
# gct <- evtree(credit_risk ~ . , data = GermanCredit, weights = gcw) 
# gct
# table(predict(gct), GermanCredit$credit_risk)
# plot(gct)
# ## End(Not run)