scorecard (version 0.1.0)

scorecard: Creating a Scorecard

Description

scorecard creates a scorecard based on the results from woebin and glm.

Usage

scorecard(bins, model, points0 = 600, odds0 = 1/19, pdo = 50)

Arguments

bins

Binning information generated from woebin function.

model

A glm model object.

points0

Target points, default 600.

odds0

Target odds, default 1/19. Odds = p/(1-p).

pdo

Points to Double the Odds, default 50.

Value

scorecard

See Also

scorecard_ply

Examples

# NOT RUN {
library(data.table)
library(scorecard)

# Traditional Credit Scoring Using Logistic Regression
# load germancredit data
data("germancredit")

# random subset 10 x variables
# rename creditability as y
dt <- setDT(germancredit)[, c(sample(20, 10), 21)][, `:=`(
  y = ifelse(creditability == "bad", 1, 0),
  creditability = NULL
)]

# woe binning ------
bins <- woebin(dt, "y")
dt_woe <- woebin_ply(dt, bins)

# glm ------
m <- glm( y ~ ., family = "binomial", data = dt_woe)
# summary(m)

# }
# NOT RUN {
# Select a formula-based model by AIC
m_step <- step(m, direction="both")
m <- eval(m_step$call)
# summary(m)

# performance ------
# predicted proability
# dt_woe$pred <- predict(m, type='response', dt_woe)

# performace
# ks & roc plot
# perf_plot(dt_woe$y, dt_woe$pred)
# }
# NOT RUN {
# card
card <- scorecard(bins, m)

# score
# only total score
score1 <- scorecard_ply(dt, card)

# }
# NOT RUN {
# credit score for both total and each variable
score2 <- scorecard_ply(dt, card, only_total_score = F)
# }