scorecard: scorecard2 – R documentation

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scorecard2

Creating a Scorecard

Description

scorecard2 creates a scorecard based on the results from woebin. It has the same function of scorecard, but without model object input and provided adjustment for oversampling.

Usage

scorecard2(bins, dt, y, x = NULL, posprob_pop = NULL, points0 = 600,
  odds0 = 1/19, pdo = 50, basepoints_eq0 = FALSE, digits = 0,
  return_prob = FALSE, positive = "bad|1", ...)

Arguments

`bins`	Binning information generated from `woebin` function.
`dt`	A data frame with both x (predictor/feature) and y (response/label) variables.
`y`	Name of y variable.
`x`	Name of x variables. If it is NULL, then all variables in bins are used. Defaults to NULL.
`posprob_pop`	Positive probability of population. Accepted range: 0-1, default to NULL. If it is not NULL, the model will adjust for oversampling.
`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.
`return_prob`	Logical, defaults to FALSE. If it is TRUE, the predict probability will also return.
`positive`	Value of positive class, default "bad\|1".
`...`	Additional parameters.

Value

A list of scorecard data frames

Examples

# 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)

scorecard

Credit Risk Scorecard

v0.3.2

MIT + file LICENSE

Authors

Shichen Xie [aut, cre]

Initial release