R: kmeans

For example, you want to divide a group of data into two clusters:

> dataset = matrix(c(1,2,+ 1.2,2,+ 8,9,+ 0.9,1.8,+ 7,10,+ 8.8,9.2), nrow=6, byrow=T)> dataset     [,1] [,2][1,]  1.0  2.0[2,]  1.2  2.0[3,]  8.0  9.0[4,]  0.9  1.8[5,]  7.0 10.0[6,]  8.8  9.2> kmeans(dataset, 2, iter.max = 20)K-means clustering with 2 clusters of sizes 3, 3Cluster means:      [,1]     [,2]1 1.033333 1.9333332 7.933333 9.400000Clustering vector:[1] 1 1 2 1 2 2Within cluster sum of squares by cluster:[1] 0.07333333 2.18666667 (between_SS / total_SS =  98.6 %)Available components:[1] "cluster"      "centers"      "totss"        "withinss"     "tot.withinss" "betweenss"   [7] "size"

We can see that the centers of the two clusters are:

Cluster means:      [,1]     [,2]1 1.033333 1.9333332 7.933333 9.400000

The labels of the six data clusters are:

Clustering vector:[1] 1 1 2 1 2 2

Visualization:

> result = kmeans(dataset, 2, iter.max = 20)> plot(c(dataset[,1]), c(dataset[,2]), col=result$cluster)

Refer:
Http://stat.ethz.ch/R-manual/R-devel/library/stats/html/kmeans.html

R: kmeans