Nothing

```
#' Derive WoE, IV, and KS based on the binning outcome
#'
#' The function \code{gen_woe} calculates WoE, IV, and KS statistics based on
#' the binning outcome. It is an utility function and is not supposed to be
#' called directly by the user.
#'
#' @param tbl A input dataframe
#' @param cut A list of numeric values as cut points
#'
#' @return A dataframe
#' @noRd
gen_woe <- function(tbl, cut) {
d1 <- tbl[order(tbl$bin), ]
gdist <- (d1$freq - d1$bads) / (sum(d1$freq) - sum(d1$bads))
bdist <- d1$bads / sum(d1$bads)
d1$rate <- round(d1$bads / d1$freq, 4)
d1$woe <- round(log(bdist / gdist), 4)
d1$iv <- round((bdist - gdist) * d1$woe, 4)
d1$ks <- round(abs(cumsum(bdist) - cumsum(gdist)) * 100, 2)
d1$rule <- NA
for (i in seq(nrow(d1))) {
if (d1[i, ]$bin == 0) {
d1[i, ]$rule <- paste("is.na($X$)", sep = '')
} else if (d1[i, ]$bin == 1) {
d1[i, ]$rule <- ifelse(d1[i, ]$miss == 0,
paste("$X$ <= ", cut[1], sep = ''),
paste("$X$ <= ", cut[1], " | is.na($X$)", sep = ''))
} else if (d1[i, ]$bin == max(d1$bin)) {
d1[i, ]$rule <- ifelse(d1[i, ]$miss == 0,
paste("$X$ > ", cut[length(cut)], sep = ''),
paste("$X$ > ", cut[length(cut)], " | is.na($X$)", sep = ''))
} else {
d1[i, ]$rule <- paste("$X$ > ", cut[d1[i, ]$bin - 1], " & $X$ <= ", cut[d1[i, ]$bin], sep = '')
}
}
keep <- c("bin", "freq", "miss", "bads", "rate", "woe", "iv", "ks", "rule")
rownames(d1) <- NULL
return(d1[, keep])
}
```

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