kmeans {MajKMeans}

k-means function

Description

k-means algorithm in clustering. This function export the clustered results based on one replication of the k-means method

Arguments

x

matrix of data (dim 1: samples (must be equal to dim 1 of X), dim 2: attributes (must be equal to dim 2 of X))

centers

initial seleted centroids (randomly or another method)

distFun

function (in this package the distance is Euclidian)

nItter

Number of itteration function

Value

clustered results based on k-means methods.

Examples

{
X=rbind(matrix(rnorm(1000*2 ,4,.1),1000,2),matrix(rnorm(1000*2, 3, 0.2),1000,2))
M <- X[sample(nrow(X), 2),]
kmeans(X,M, Euclid, 4)
}