#' About 20,000 fictional credit records.
#'
#' A dataset containing the personal and credit attributes of almost 20,000 fictional
#' customers. The variables are as follows:
#'
#' \itemize{
#' \item gender. gender of customer (F, M)
#' \item marriage. marriage of customer (unmarried, married, divorced)
#' \item education. education of customer (primary, middle, high, polytechnic, junior, bachelor)
#' \item housing. housing of customer (unit, rent, parents, own)
#' \item loanamount. loan amount (500--10800)
#' \item loanperiod. period of loan (3--24)
#' \item queryid. suspect query reuslt by id number (positive, negative)
#' \item queryphone. suspect query reuslt by phone number (positive, negative)
#' \item queryhis15d. suspect query history in the last 15 days (positive, negative)
#' \item queryhis30d. suspect query history in the last 30 days (positive, negative)
#' \item queryhis90d. suspect query history in the last 90 days (positive, negative)
#' \item applyflag. whether applied before (0, 1)
#' \item multiloantimes. times of multiple loan in the last 12 months (1--31)
#' \item purchasingPI. purchasing power index of customer (10--100)
#' \item rationalCI. rational consumption index of customer (0--100)
#' \item equipmentBI. equipment behavior index of customer (302--848)
#' \item transactionRI. transaction risk index of customer (359--818)
#' \item consumptionCI. consumption composite index of customer (350--850)
#' \item gscore. customer's score graded by credit institution G (443--703)
#' \item kscore. customer's score graded by credit institution K (300--850)
#' \item bscore. customer's score graded by credit institution B (365--854)
#' \item pscore. customer's score graded by credit institution P (304--789)
#' \item target. response variable, 1 means bad customer, 0 means good customer (0, 1)
#' }
#'
#' @docType data
#' @keywords datasets
#' @name CreditData
#' @usage data(CreditData)
#' @format A data frame with 19805 rows and 23 variables
NULL
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