blr_woe_iv: WoE & IV

In blorr: Tools for Developing Binary Logistic Regression Models

Description

Weight of evidence and information value. Currently avialable for categorical predictors only.

Usage

blr_woe_iv(data, predictor, response, digits = 4, ...)

## S3 method for class 'blr_woe_iv'
plot(
  x,
  title = NA,
  xaxis_title = "Levels",
  yaxis_title = "WoE",
  bar_color = "blue",
  line_color = "red",
  print_plot = TRUE,
  ...
)

Arguments

data	A tibble or data.frame.
predictor	Predictor variable; column in data.
response	Response variable; column in data.
digits	Number of decimal digits to round off.
...	Other inputs.
x	An object of class blr_segment_dist.
title	Plot title.
xaxis_title	X axis title.
yaxis_title	Y axis title.
bar_color	Color of the bar.
line_color	Color of the horizontal line.
print_plot	logical; if TRUE, prints the plot else returns a plot object.

Value

A tibble.

References

Siddiqi N (2006): Credit Risk Scorecards: developing and implementing intelligent credit scoring. New Jersey, Wiley.

See Also

Other bivariate analysis procedures: blr_bivariate_analysis(), blr_segment_dist(), blr_segment_twoway(), blr_segment(), blr_woe_iv_stats()

Examples

# woe and iv
k <- blr_woe_iv(hsb2, female, honcomp)
k

# plot woe
plot(k)

blorr documentation built on July 2, 2020, 2:15 a.m.