Weight of evidence and information value. Currently avialable for categorical predictors only.
blr_woe_iv(data, predictor, response, digits = 4, ...)# S3 method for blr_woe_iv
plot(
x,
title = NA,
xaxis_title = "Levels",
yaxis_title = "WoE",
bar_color = "blue",
line_color = "red",
print_plot = TRUE,
...
)
A tibble
or data.frame
.
Predictor variable; column in data
.
Response variable; column in data
.
Number of decimal digits to round off.
Other inputs.
An object of class blr_segment_dist
.
Plot title.
X axis title.
Y axis title.
Color of the bar.
Color of the horizontal line.
logical; if TRUE
, prints the plot else returns a plot object.
A tibble.
Siddiqi N (2006): Credit Risk Scorecards: developing and implementing intelligent credit scoring. New Jersey, Wiley.
Other bivariate analysis procedures:
blr_bivariate_analysis()
,
blr_segment_dist()
,
blr_segment_twoway()
,
blr_segment()
,
blr_woe_iv_stats()
# NOT RUN {
# woe and iv
k <- blr_woe_iv(hsb2, female, honcomp)
k
# plot woe
plot(k)
# }
Run the code above in your browser using DataLab