Quantile binning

Bin continuous data using quantiles.

rbin_quantiles(
  data = NULL,
  response = NULL,
  predictor = NULL,
  bins = 10,
  include_na = TRUE
)

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

Arguments

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

Value

A tibble.

Examples

bins <- rbin_quantiles(mbank, y, age, 10)
bins
#> Binning Summary
#> -----------------------------
#> Method               Quantile 
#> Response             y 
#> Predictor            age 
#> Bins                 10 
#> Count                4521 
#> Goods                517 
#> Bads                 4004 
#> Entropy              0.5 
#> Information Value    0.12 
#> 
#> 
#>    cut_point bin_count good bad          woe
#> 1       < 29       410   71 339 -0.483686036
#> 2       < 31       313   41 272 -0.154776266
#> 3       < 34       567   55 512  0.183985174
#> 4       < 36       396   45 351  0.007117468
#> 5       < 39       519   47 472  0.259825118
#> 6       < 42       431   33 398  0.442938178
#> 7       < 46       449   47 402  0.099298221
#> 8       < 51       521   40 481  0.439981550
#> 9       < 56       445   49 396  0.042587647
#> 10     >= 56       470   89 381 -0.592843261
#>              iv   entropy
#> 1  2.547353e-02 0.6649069
#> 2  1.760055e-03 0.5601482
#> 3  3.953685e-03 0.4594187
#> 4  4.425063e-06 0.5107878
#> 5  7.008270e-03 0.4383322
#> 6  1.575567e-02 0.3899626
#> 7  9.423907e-04 0.4836486
#> 8  1.881380e-02 0.3907140
#> 9  1.756117e-04 0.5002548
#> 10 4.564428e-02 0.7001343

# plot
plot(bins)