| numericToCategorical {CollapseLevels} | R Documentation |
numericToCategorical
Description
This function categorizes a numerical variable by binning
Usage
numericToCategorical(dset, col = "job", resp = "y", bins = 10, adjFactor = 0.5)
Arguments
dset |
The data frame containing the data set |
col |
A character respresenting the name of the numeric attribute which we want to categorize |
resp |
A character respresenting the name of the binary outcome variable The binary outcome variable may be a factor with two levels or an integer (or numeric ) with two unique values |
bins |
A number denoting the number of bins.Default value is 10 |
adjFactor |
A number or a decimal denoting what is to be added to the number of responses (binary outcome variable is 1 ) or to the number of non responses (binary outcome variable is 0) if either is zero for any level of the attribute |
Value
A list containing the categorized attribute,a table of Information Values for the levels of the categorized attribute,the Information Value for the entire attribute,a table showing the response rates of the levels of the categorized attribute
Examples
# Load the German_Credit data set supplied with this package
data("German_Credit")
# Create an empty list
l<-list()
# Call the function as follows.
#This will categorize the numeric variable Duration in the German_Credit dataset.
l<-numericToCategorical(German_Credit,col="Duration",resp="Good_Bad")
# To view the categorized variable
l$categoricalVariable
# To view the IV table of the levels of the categorized variable
l$IVTable
# To view the total IV value of the categorized variable
l$IV
# To view the response rates of the levels of the categorized variable
l$collapseLevels