BeEFdiscretization.numfact: BeEF: Best Equal-Frequency discretization

In linkspotter: Bivariate Correlations Calculation and Visualization

Description

Discretize a quantitative variable by optimizing the obtained the Normalized Mutual Information with a target qualitative variable

Usage

BeEFdiscretization.numfact(
  continuousY,
  factorX,
  includeNA = T,
  showProgress = F
)

Arguments

continuousY	a vector of numeric.
factorX	a vector of factor.
includeNA	a boolean. TRUE to include NA value as a factor level.
showProgress	a boolean to decide whether to show the progress bar.

Value

a factor.

Examples

# calculate a correlation dataframe
data(iris)
discreteSepalLength=BeEFdiscretization.numfact(continuousY=iris$Sepal.Length,factorX=iris$Species)
summary(discreteSepalLength)

linkspotter documentation built on July 23, 2020, 5:08 p.m.