# Team 2 K-means in R (Jang)

## 2233 days ago by bigdata2016

set.seed (3) x=matrix (rnorm (50*2) , ncol =2) x[1:25 ,1]=x[1:25 ,1]+3 x[1:25 ,2]=x[1:25 ,2] -4 km.out2 =kmeans (x,2, nstart =20) km.out2$cluster plot(x, col =(km.out2$cluster +1) , main="K-Means Clustering Results with K=2", xlab ="", ylab="", pch =20, cex =2)
  [1] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [49] 1 1  [1] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [49] 1 1
set.seed (4) km.out3 =kmeans (x,3, nstart =20) km.out3 plot(x, col =(km.out3$cluster +1) , main="K-Means Clustering Results with K=3", xlab ="", ylab="", pch =20, cex =2)  K-means clustering with 3 clusters of sizes 13, 25, 12 Cluster means: [,1] [,2] 1 0.9348942 0.22064634 2 2.7112299 -3.95090815 3 -0.6775392 0.01699628 Clustering vector: [1] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 1 1 3 3 1 1 1 1 3 1 1 3 3 1 1 3 1 3 1 3 3 1 [49] 3 3 Within cluster sum of squares by cluster: [1] 9.878084 32.323548 10.712040 (between_SS / total_SS = 85.2 %) Available components: [1] "cluster" "centers" "totss" "withinss" "tot.withinss" "betweenss" [7] "size"  K-means clustering with 3 clusters of sizes 13, 25, 12 Cluster means: [,1] [,2] 1 0.9348942 0.22064634 2 2.7112299 -3.95090815 3 -0.6775392 0.01699628 Clustering vector: [1] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 1 1 3 3 1 1 1 1 3 1 1 3 3 1 1 3 1 3 1 3 3 1 [49] 3 3 Within cluster sum of squares by cluster: [1] 9.878084 32.323548 10.712040 (between_SS / total_SS = 85.2 %) Available components: [1] "cluster" "centers" "totss" "withinss" "tot.withinss" "betweenss" [7] "size"  set.seed(7) x=matrix (rnorm (50*2) , ncol =2) x[1:25 ,1]=x[1:25 ,1]+3 x[1:25 ,2]=x[1:25 ,2] -4 km.out =kmeans (x,3, nstart =1) km.out$tot.withinss km.out =kmeans (x,3, nstart =20) km.out$tot.withinss km.out =kmeans (x,3, nstart =50) km.out$tot.withinss
 [1] 72.62232 [1] 57.63156 [1] 57.63156 [1] 72.62232 [1] 57.63156 [1] 57.63156