k-means is a decent clustering algorithm, however it requires the specification of the number of clusters, and is stochastic.
This function takes a matrix as input, as well as the maximum number of clusters, the cutoff to determine the best model (the fraction of variance explained), and makes sure the results are stable by repeating a number of times specified by the user.
The above method is called the Elbow method.