Creating a Scorecard
scorecard creates a scorecard based on the results from woebin and glm.
scorecard(bins, model, points0 = 600, odds0 = 1/19, pdo = 50, basepoints_eq0 = FALSE, digits = 0)
bins |
Binning information generated from |
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. |
basepoints_eq0 |
Logical, Defaults to FALSE. If it is TRUE, the basepoints will equally distribute to each variable. |
digits |
The number of digits after the decimal point for points calculation. Default 0. |
A list of scorecard data frames
# 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)
# Select a formula-based model by AIC
m_step = step(m, direction="both", trace=FALSE)
m = eval(m_step$call)
# scorecard
# Example I # creat a scorecard
card = scorecard(bins, m)
card2 = scorecard2(bins=bins, dt=germancredit, y='creditability',
x=sub('_woe', '', names(coef(m))[-1]))
# credit score
# Example I # only total score
score1 = scorecard_ply(germancredit, card)
# Example II # credit score for both total and each variable
score2 = scorecard_ply(germancredit, card, only_total_score = FALSE)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.