Euclid: Euclidian distance

In MajMinKmeans: k-Means Algorithm with a Majorization-Minimization Method

Euclidian distance

Description

Calculates the Euclidian distance between points. This function can use in kmeans function to do the clustering procedure using the Euclidian distance.

Usage

Euclid(x, mu)

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))
mu	initial seleted centroids (randomly or another method).

Value

Euclidian distance between two points.

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),]
Euclid(X,M)
}

MajMinKmeans documentation built on May 29, 2024, 8:30 a.m.