autoBin.binary: Auto Binning for Quantitative Variables - Binary

In CASMI: 'CASMI'-Based Functions

Auto Binning for Quantitative Variables - Binary

Description

Automatically suggest an optimal cutting point for categorizing a quantitative variable before using the CASMI-based functions. This function does binary cutting, that is, to convert the quantitative variable into a categorical variable with two levels/categories.

Usage

autoBin.binary(data, index)

Arguments

data	data frame (features as columns and observations as rows). An outcome variable is required. The outcome variable (Y) MUST be the last column.
index	index or a vector of indices of the quantitative variables that need to be automatically categorized.

Value

'autoBin.binary()' returns the entire data frame after automatic binary categorization for the selected quantitative variable(s).

Examples

## Use the "iris" dataset embedded in R
data("iris")
newData <- autoBin.binary(iris, c(1,2,3,4))
newData

CASMI documentation built on May 29, 2024, 12:12 p.m.