EM: EM clustering for data set

In yehanxuan/tamu-689-final: What the package does (short line)

Description

EM clustering for data set

Usage

EM(K, mean, sigma, Y)

Arguments

K	number of clusters
mean	initialization of means of Gaussian clusters
sigma	initialization of variance of Gaussian clusters
Y	the data matrix

Value

The final mean and variance and clustering results

Examples

A = matrix(c(1,1,0,0,0,0,0,0,0,0,0,0,0,0,1,1),4,4)
K = 2
p = 4
prob = runif(K, min=0.1, max = 0.9)
prob = prob/sum(prob)
mean = matrix(rnorm(K*p), K, p)
sigma = array(rep(diag(p), K), dim = c(p, p, K))
ans = EM(prob, mean, sigma, A)
table(ans$class)

yehanxuan/tamu-689-final documentation built on Dec. 8, 2019, 5:25 p.m.