A dataset containing information on loan applicants and their financial profiles, including demographic characteristics, employment status, income, loan details, credit score, asset values, and loan approval outcome.
data(loan)A data frame with 4269 observations and 13 variables:
Unique identifier for each loan application; not intended as a predictor in modeling.
Number of dependents of the applicant.
Education level of the applicant: "graduate" or "not-graduate".
Whether the applicant is self-employed: "yes" or "no".
Annual income of the applicant.
Requested loan amount.
Loan term.
Applicant's CIBIL credit score.
Value of the applicant's residential assets.
Value of the applicant's commercial assets.
Value of the applicant's luxury assets.
Value of the applicant's bank assets.
Loan application outcome: "approved" or "rejected".
This dataset was obtained from Kaggle and renamed loan for inclusion
in the liver package. It can be used to illustrate methods for
classification, exploratory data analysis, and predictive modeling in R.
Reza Mohammadi (2025). Data Science Foundations and Machine Learning with R: From Data to Decisions. https://book-data-science-r.netlify.app.
mortgage,
bank,
churn_mlc,
churn,
churn_tel,
adult,
cereal,
advertising,
marketing,
drug,
house,
house_price,
red_wines,
white_wines,
insurance,
caravan,
loan
data(loan)
str(loan)
summary(loan)
table(loan$loan_status)
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