GermanCredit

0th

Percentile

German Credit Data

Data from Dr. Hans Hofmann of the University of Hamburg.

These data have two classes for the credit worthiness: good or bad. There are predictors related to attributes, such as: checking account status, duration, credit history, purpose of the loan, amount of the loan, savings accounts or bonds, employment duration, Installment rate in percentage of disposable income, personal information, other debtors/guarantors, residence duration, property, age, other installment plans, housing, number of existing credits, job information, Number of people being liable to provide maintenance for, telephone, and foreign worker status.

Many of these predictors are discrete and have been expanded into several 0/1 indicator variables

Keywords
datasets
Usage
data(GermanCredit)
source

UCI Machine Learning Repository

Aliases
  • GermanCredit
Documentation reproduced from package caret, version 6.0-52, License: GPL (>= 2)

Community examples

Looks like there are no examples yet.