maxNMI: Maximal Normalized Mutual Information (MaxNMI)

In linkspotter: Bivariate Correlations Calculation and Visualization

Description

Computes the MaxNMI between the two variables whatever their types, by discretizing using Best Equal-Frequency-based discretization (BeEF) if necessary.

Usage

maxNMI(x, y, includeNA = T, maxNbBins = 100, showProgress = F)

Arguments

x	a vector of numeric or factor.
y	a vector of numeric or factor.
includeNA	a boolean. TRUE to include NA value as a factor level.
maxNbBins	an integer corresponding to the number of bins limitation (for computation time limitation), maxNbBins=100 by default.
showProgress	a boolean to decide whether to show the progress bar.

Value

a double between 0 and 1 corresponding to the MaxNMI.

Examples

# calculate a correlation dataframe
data(iris)
maxNMI(iris$Sepal.Length,iris$Species)
maxNMI(iris$Sepal.Length,iris$Sepal.Width)

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