For Machine Learning and Web Analytics blogpost http://markedmondson.me/intro-to-machine-learning-with-web-analytics-random-forests-and-k-means

how-many-clusters.R

# Determine number of clusters
## run kmeans for varying number of clusters 1 to 15
wss <- (nrow(comp)-1)*sum(apply(comp,2,var))
for (i in 2:15) wss[i] <- sum(kmeans(comp,
                                     centers=i)$withinss)
plot(1:15, wss, type="b", xlab="Number of Clusters",
     ylab="Within groups sum of squares")


# From scree plot elbow occurs at k = 4-6
# we'll choose 4 clusters:
k <- kmeans(comp, 4, nstart=25, iter.max=1000)