r - How to find the optimal number of clusters? -


i know question has been asked, failing implement decent plot following code:

options(digits=1) set.seed(2014)  mydata <- matrix(seq(1,360),nrow=10,ncol=36) wss <- c() (i in 1:19) wss[i] <- sum(kmeans(x=mydata,centers=seq(1,360,length.out=20)[i])$withinss) plot(1:9, wss, type="b", xlab="number of clusters",      ylab="within groups sum of squares")

it produces following error

error in sample.int(m, k) :  cannot take sample larger population when 'replace = false'

kmeans assumes each row data observation. if have k rows in x, results of $clusters of lenth k. here test data has 10 rows. yet specifying centers=20 when i=2 there no way 10 observations can have 20 different clusters.


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