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, ...)

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.

...

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 #> #> #> # A tibble: 10 x 7 #> cut_point bin_count good bad woe iv entropy #> <chr> <int> <int> <int> <dbl> <dbl> <dbl> #> 1 < 29 410 71 339 -0.484 0.0255 0.665 #> 2 < 31 313 41 272 -0.155 0.00176 0.560 #> 3 < 34 567 55 512 0.184 0.00395 0.459 #> 4 < 36 396 45 351 0.00712 0.00000443 0.511 #> 5 < 39 519 47 472 0.260 0.00701 0.438 #> 6 < 42 431 33 398 0.443 0.0158 0.390 #> 7 < 46 449 47 402 0.0993 0.000942 0.484 #> 8 < 51 521 40 481 0.440 0.0188 0.391 #> 9 < 56 445 49 396 0.0426 0.000176 0.500 #> 10 >= 56 470 89 381 -0.593 0.0456 0.700
# plot plot(bins)