best_vs {autoScorecard}

The Combination of Two Bins Produces the Best Binning Result

Description

The Combination of Two Bins Produces the Best Binning Result

Usage

best_vs(df1, df2, variable = "variable", label_iv = "miv")

Arguments

df1

A binned data.

df2

A binned data.

variable

A name of X variable.

label_iv

A name of target variable.

Value

A data frame of best IV.

Examples

accepts <- read.csv(system.file( "extdata", "accepts.csv", package = "autoScorecard" ))
feature <- stats::na.omit( accepts[,c(1,3,7:23)] )
all2 <- bins_tree(df = feature, key_var= "application_id", y_var= "bad_ind"
, max_depth = 3, p = 0.1 )
f_1 <-bins_unsupervised(  df = feature , id="application_id" , label="bad_ind" ,
methods = c("k_means", "equal_width","equal_freq"  )  ,  bin_nums=10  )
best1 <- best_iv( df=f_1 ,bin=c('bins') ,  method = c('method') ,
variable= c( "variable" )  ,label_iv='miv'  )
vs1 <- best_vs( df1 = all2[,-c(3)], df2 = best1[,-c(1:2)] ,variable="variable" ,label_iv='miv' )