KmeansQuick: Quick kmeans clustering

View source: R/KmeansAutoElbow.R

KmeansQuickR Documentation

Quick kmeans clustering

Description

Perform quick kmeans algorithm for data clustering.

Usage

KmeansQuick(features, K)

Arguments

features

matrix of raw data (point by line).

K

number of clusters.

Details

KmeansQuick partition and K number of groups according to kmeans clustering

Value

res.kmeans results obtained from kmeans algorithm.

See Also

KmeansAutoElbow

Examples

dat <- rbind(matrix(rnorm(100, mean = 0, sd = 0.3), ncol = 2), 
           matrix(rnorm(100, mean = 2, sd = 0.3), ncol = 2), 
           matrix(rnorm(100, mean = 4, sd = 0.3), ncol = 2))
           
res <- KmeansQuick(dat, K=3)

plot(dat[,1], dat[,2], type = "p", xlab = "x", ylab = "y", 
	col = res$cluster, main = "K-means clustering")


RclusTool documentation built on May 29, 2024, 5:23 a.m.