linkspotter (version 1.3.0)

BeEFdiscretization.numnum: BeEF: Best Equal-Frequency discretization (for a couple of quantitative variables)

Description

Discretize two quantitative variables by optimizing the obtained the Normalized Mutual Information

Usage

BeEFdiscretization.numnum(
  continuousX,
  continuousY,
  maxNbBins = 100,
  includeNA = T,
  showProgress = F
)

Arguments

continuousX

a vector of numeric.

continuousY

a vector of numeric.

maxNbBins

an integer corresponding to the number of bins limitation (for computation time limitation), maxNbBins=100 by default.

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 list of two factors.

Examples

# NOT RUN {
# calculate a correlation dataframe
data(iris)
disc=BeEFdiscretization.numnum(iris$Sepal.Length,iris$Sepal.Width)
summary(disc$x)
summary(disc$y)

# }