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RSADBE (version 1.0)

GC: German Credit Screening Data

Description

Loans are an assest for the banks! However, not all the loans are promptly returned and it is thus important for a bank to build a classification model which can identify the loan defaulters from those who complete the loan tenure.

Usage

data(GC)

Arguments

Format

A data frame with 1000 observations on the following 21 variables.
checking
Status of existing checking account
duration
Duration in month
history
Credit history
purpose
Purpose of loan
amount
Credit amount
savings
Savings account or bonds
employed
Present employment since
installp
Installment rate in percentage of disposable income
marital
Personal status and sex
coapp
Other debtors or guarantors
resident
Present residence since
property
Property
age
Age in years
other
Other installment plans
housing
Housing
existcr
Number of existing credits at this bank
job
Job
depends
Number of people being liable to provide maintenance for
telephon
Telephone
foreign
foreign worker
good_bad
Loan Defaulter

Source

http://www.stat.auckland.ac.nz/~reilly/credit-g.arff and http://archive.ics.uci.edu/ml/datasets/Statlog+(German+Credit+Data)

References

cran.r-project.org/doc/contrib/Sharma-CreditScoring.pdf

Examples

Run this code
data(GC)

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