mi: Mutual Information

In mlf: Machine Learning Foundations

Description

Estimates Kullback-Leibler divergence of joint distribution and the product of two respective marginal distributions. Roughly speaking, the amount of information one variable provides about another.

Usage

mi(x, y)

Arguments

x, y	numeric or discrete data vectors

Examples

# Sample data
a <- rnorm(25, 80, 35)
b <- rnorm(25, 100, 50)

mlf::mi(a, b)

mlf documentation built on May 1, 2019, 10:34 p.m.