german {datasetsICR}

german dataset

Description

Bank customers described by a set of attributes.

Usage

data(german)

Format

A data.frame with 1000 rows on 9 variables.

Details

The dataset contains 1000 bank consumers with 9 mixed measurements. Each row represents a person who takes a bank credit. Each person is either classified as good or bad customer according to her/his failure to repay. This information is described by the variable Class Risk. The variables are described below.

Age: Age (in years).
Gender: female, male.
Housing: free, own, rent.
Saving accounts: little (< 100 Deutsch Mark), moderate (100 <= ... < 500 Deutsch Mark), quite rich (500 <= ... < 1000 Deutsch Mark) rich (>= 1000 Deutsch Mark).
Checking account: little (< 0 Deutsch Mark), moderate (0 <= ... < 200 Deutsch Mark), rich(>= 200 Deutsch Mark). It represents the status of the existing checking account.
Credit amount: Credit amount (in Deutsch Mark).
Duration: Credit duration (in month).
Purpose: car, furniture/equipment, radio/TV, domestic appliances, repairs, education, business, vacation/others.
Class Risk: 1 (Good), 2 (Bad).

Author(s)

Paolo Giordani, Maria Brigida Ferraro, Francesca Martella

Source

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

References

Dua, D., Graff, C.: UCI Machine Learning Repository. University of California, School of Information and Computer Science, Irvine, CA (2019)
Giordani, P., Ferraro, M.B., Martella, F.: An Introduction to Clustering with R. Springer, Singapore (2020)

Examples

data(german)
X <- german[,1:8]
class <- german[,9]