scorecard (version 0.2.3)

scorecard_ply: Score Transformation

Description

scorecard_ply calculates credit score using the results from scorecard.

Usage

scorecard_ply(dt, card, only_total_score = TRUE, print_step = 0L,
  replace_blank_na = TRUE, var_kp = NULL)

Arguments

dt

A data frame, which is the rriginal dataset for training model.

card

The scorecard generated from the function scorecard.

only_total_score

Logical, default is TRUE. If it is TRUE, then the output includes only total credit score; Otherwise, if it is FALSE, the output includes both total and each variable's credit score.

print_step

A non-negative integer. Default is 1. If print_step>0, print variable names by each print_step-th iteration. If print_step=0, no message is print.

replace_blank_na

Logical. Replace blank values with NA. Default is TRUE. This argument should be the same with woebin's.

var_kp

Name of force kept variables, such as id column. Default is NULL.

Value

A data frame in score values

See Also

scorecard scorecard2

Examples

# NOT RUN {
# load germancredit data
data("germancredit")

# filter variable via missing rate, iv, identical value rate
dt_sel = var_filter(germancredit, "creditability")

# woe binning ------
bins = woebin(dt_sel, "creditability")
dt_woe = woebin_ply(dt_sel, bins)

# glm ------
m = glm(creditability ~ ., family = binomial(), data = dt_woe)
# summary(m)

# Select a formula-based model by AIC
m_step = step(m, direction="both", trace=FALSE)
m = eval(m_step$call)
# summary(m)

# predicted proability
# dt_pred = predict(m, type='response', dt_woe)

# performace
# ks & roc plot
# perf_eva(dt_woe$creditability, dt_pred)

# scorecard
# Example I # creat a scorecard
card = scorecard(bins, m)
card2 = scorecard2(bins=bins, dt=germancredit, y='creditability',
  x=c("status.of.existing.checking.account", "duration.in.month", "credit.history",
   "purpose", "credit.amount", "savings.account.and.bonds",
   "present.employment.since", "installment.rate.in.percentage.of.disposable.income",
   "personal.status.and.sex", "other.debtors.or.guarantors", "property",
   "age.in.years", "other.installment.plans", "housing"))

# credit score
# Example I # only total score
score1 = scorecard_ply(dt, card)

# Example II # credit score for both total and each variable
score2 = scorecard_ply(dt, card, only_total_score = F)
# }