KmeansQuick {RclusTool} | R 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
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")
[Package RclusTool version 0.91.6 Index]