cmi: Compute the (conditional) mutual information between two...

In bnclassify: Learning Discrete Bayesian Network Classifiers from Data

Compute the (conditional) mutual information between two variables.

Description

Computes the (conditional) mutual information between two variables. If z is not NULL then returns the conditional mutual information, I(X;Y|Z). Otherwise, returns mutual information, I(X;Y).

Usage

cmi(x, y, dataset, z = NULL, unit = "log")

Arguments

x	A length one character.
y	A length one character.
dataset	A data frame. Must contain x, y and, optionally, z columns.
z	A character vector.
unit	A character. Logarithm base. See entropy package.

Details

I(X;Y|Z) = H(X|Z) + H(Y|Z) - H(X,Y,Z) - H(Z), where H() is Shannon's entropy.

Examples

data(car)
cmi('maint', 'class', car)

bnclassify documentation built on June 22, 2024, 11:08 a.m.