This is a wrapper for scorecard::woebin, this fixes some problem to replicate the cuts given on windows machines.
Usage
woebin2(
dt,
y,
x = NULL,
var_skip = NULL,
breaks_list = NULL,
special_values = NULL,
stop_limit = 0.1,
count_distr_limit = 0.05,
bin_num_limit = 8,
positive = "bad|1",
no_cores = NULL,
print_step = 0L,
method = "tree",
save_breaks_list = NULL,
ignore_const_cols = TRUE,
ignore_datetime_cols = TRUE,
check_cate_num = TRUE,
replace_blank_inf = TRUE,
control = partykit::ctree_control()
)Arguments
- dt
A data frame with both x (predictor/feature) and y (response/label) variables.
- y
Name of y variable.
- x
Name of x variables. Defaults to NULL. If x is NULL, then all columns except y and var_skip are counted as x variables.
- var_skip
Name of variables that will skip for binning. Defaults to NULL.
- breaks_list
List of break points, Defaults to NULL. If it is not NULL, variable binning will based on the provided breaks.
- special_values
the values specified in special_values will be in separate bins. Defaults to NULL.
- stop_limit
Stop binning segmentation when information value gain ratio less than the 'stop_limit' if using tree method; or stop binning merge when the chi-square of each neighbor bins are larger than the threshold under significance level of 'stop_limit' and freedom degree of 1 if using chimerge method. Accepted range: 0-0.5; Defaults to 0.1. If it is 'N', each x value is a bin.
- count_distr_limit
The minimum count distribution percentage. Accepted range: 0.01-0.2; Defaults to 0.05.
- bin_num_limit
Integer. The maximum number of binning. Defaults to 8.
- positive
Value of positive class, defaults to "bad|1".
- no_cores
Number of CPU cores for parallel computation. Defaults to 90 percent of total cpu cores.
- print_step
A non-negative integer. Defaults to 1. If print_step>0, print variable names by each print_step-th iteration. If print_step=0 or no_cores>1, no message is print.
- method
Four methods are provided, "tree" and "chimerge" for optimal binning that support both numerical and categorical variables, and 'width' and 'freq' for equal binning that support numerical variables only. Defaults to "tree".
- save_breaks_list
A string. The file name to save breaks_list. Defaults to None.
- ignore_const_cols
Logical. Ignore constant columns. Defaults to TRUE.
- ignore_datetime_cols
Logical. Ignore datetime columns. Defaults to TRUE.
- check_cate_num
Logical. Check whether the number of unique values in categorical columns larger than 50. It might make the binning process slow if there are too many unique categories. Defaults to TRUE.
- replace_blank_inf
Logical. Replace blank values with NA and infinite with -1. Defaults to TRUE.
- control
a ctree::ctree_control list element
Examples
if (FALSE) {
data(germancredit, package = "scorecard")
bins <- woebin2(
dt = germancredit,
y = "creditability",
# x = c("credit.amount", "housing", "duration.in.month", "purpose"),
no_cores = 0,
method = "tree"
)
bins
if (require(scorecard)) {
library(scorecard)
options(bin_close_right = TRUE)
}
bins <- woebin2(
dt = germancredit,
y = "creditability",
# x = c("credit.amount", "housing", "duration.in.month", "purpose"),
no_cores = 0,
method = "tree"
)
bins
bins_ctree <- woebin2(
dt = germancredit,
y = "creditability",
method = "ctree",
no_cores = 0,
control = partykit::ctree_control(alpha = 1, maxdepth = 4)
)
woebin_summary(bins)
woebin_summary(bins_ctree)
}