linkspotter (version 1.3.0)

NormalizedMI: Maximal Normalized Mutual Information (MaxNMI) function for 2 categorical variables

Description

Calculate the MaxNMI relationship measurement for 2 categorical variables

Usage

NormalizedMI(x, y, includeNA = T)

Arguments

x

a vector of factor.

y

a vector of factor.

includeNA

a boolean. TRUE to include NA value as a factor level.

Value

a double between 0 and 1 corresponding to the MaxNMI.

Examples

# NOT RUN {
# calculate a correlation dataframe
data(iris)
discreteSepalLength=BeEFdiscretization.numfact(continuousY=iris$Sepal.Length,factorX=iris$Species)
NormalizedMI(iris$Species,discreteSepalLength)

# }