In practice, self-organizing map clustering is often used to validate k-means clustering. A relatively unexplored idea is to perform SOM clustering using an r-by-c map instead of a 1-by-k map. When ...

A key step in deploying clustering is deciding which algorithm to use. One of the most common is k-means, which works by computing the “distances” (i.e., similarity) between data points and ...

For parameter learning, the expectation maximization algorithm alternates between computing probabilities for assignments of each gene to each cluster (E-step) and updating the cluster means and ...