Factor binning

Weight of evidence and information value for categorical data.

rbin_factor(data = NULL, response = NULL, predictor = NULL, include_na = TRUE)

# S3 method for rbin_factor
plot(x, print_plot = TRUE, ...)

Arguments

data	A data.frame or tibble.
response	Response variable.
predictor	Predictor variable.
include_na	logical; if TRUE, a separate bin is created for missing values.
x	An object of class rbin_factor.
print_plot	logical; if TRUE, prints the plot else returns a plot object.
...	further arguments passed to or from other methods.

Examples

bins <- rbin_factor(mbank, y, education)
bins
#> Binning Summary
#> ---------------------------
#> Method               Custom 
#> Response             y 
#> Predictor            education 
#> Levels               4 
#> Count                4521 
#> Goods                517 
#> Bads                 4004 
#> Entropy              0.51 
#> Information Value    0.05 
#> 
#> 
#>       level bin_count good  bad        woe          iv
#> 1  tertiary      1299  195 1104 -0.3133106 0.031785905
#> 2 secondary      2352  231 2121  0.1702190 0.014113157
#> 3   primary       691   66  625  0.2010906 0.005717878
#> 4   unknown       179   25  154 -0.2289295 0.002265111
#>     entropy
#> 1 0.6101292
#> 2 0.4633093
#> 3 0.4546110
#> 4 0.5833603

# plot
plot(bins)