Bank customers described by a set of attributes.
A data.frame with 1000 rows on 9 variables.
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).
little (< 100 Deutsch Mark),
moderate (100 <= ... < 500 Deutsch Mark),
quite rich (500 <= ... < 1000 Deutsch Mark)
rich (>= 1000 Deutsch Mark).
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).
Paolo Giordani, Maria Brigida Ferraro, Francesca Martella
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)
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