CCD: Credit Card Defaults
In sross15/bestclassifier: Identify Best Binary Classification Model

A dataset containing information on default payments, demographic infomration, and payment history for Taiwanese credit card clients from April 2005 to Septembrer 2005

CCD

A dataset with 29728 rows and 25 variables. The variables are as follows:

default.payment.next.month: Factor indicating default
LIMIT: Credit card limit
SEX: Factor indicating gender
Education: Factor depicting highest level of education
Marriage: Factor indicating marital status
AGE: Age
REPAID.SEPT: Factor describing September payment status
REPAID.AUG: Factor describing August payment status
REPAID.JULY: Factor describing July payment status
REPAID.JUNE: Factor describing June payment status
REPAID.MAY: Factor describing May payment status
REPAID.APR: Factor describing April payment status
BILL_SEPT: Total credit card bill in September
BILL_AUG: Total credit card bill in August
BILL_JULY: Total credit card bill in July
BILL_JUNE: Total credit card bill in June
BILL_MAY: Total credit card bill in May
BILL_APR: Total credit card bill in April
PAYMENT_SEPT: Total paid in September
PAYMENT_AUG: Total paid in August
PAYMENT_JULY: Total paid in July
PAYMENT_JUNE: Total paid in June
PAYMENT_MAY: Total paid in May
PAYMENT_APR: Total paid in April

@source Lichman, M. (2013). UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School of Information and Computer Science.

This dataset was retrieved by UCI's Machine Learning Repository and then slightly modified to improve the predictiveness of the variables.

sross15/bestclassifier documentation built on May 23, 2019, 7:19 a.m.