scorecardModelUtils (version 0.0.1.0)

scoring: Scoring a dataset with class based on a scalling logic to arrive at final score

Description

The function takes the data, with each variable as class. The dataframe of class scalling is used to convert the class into scores and finally arrive at the row level final scores by adding up the score values.

Usage

scoring(base, target, scalling)

Arguments

base

input dataframe with classes same as scalling logic

target

column / field name for the target variable to be passed as string (must be 0/1 type)

scalling

dataframe of class scalling with atleast two columns - Variable, Category, Coefficient, D(i,j)_hat, Score

Value

The function returns a dataframe with classes converted to scores and the final score for each record in the input dataframe.

Examples

# NOT RUN {
data <- iris
suppressWarnings(RNGversion('3.5.0'))
set.seed(11)
data$Y <- sample(0:1,size=nrow(data),replace=TRUE)
x <- c("Sepal.Length","Sepal.Width","Petal.Length","Petal.Width")
iv_table_list <- iv_table(base = data,target = "Y",num_var_name = x,cat_var_name = "Species")
num_cat <- num_to_cat(base = data,num_woe_table = iv_table_list$num_woe_table)
log_model <- glm(Y ~ ., data = num_cat, family = "binomial")
scaling_tab <- scalling(base = num_cat,target = "Y",model = log_model)
score_tab <- scoring(base = num_cat,target = "Y",scalling = scaling_tab)
# }