Do you have some data that you'd like to understand better? I'm happy to announce a new package called som that may help: http://hackage.haskell.org/package/som https://github.com/mhwombat/som/wiki (wiki) A Kohonen Self-organising Map (SOM) maps input patterns onto a regular grid (usually two-dimensional) where each node in the grid is a model of the input data, and does so using a method which ensures that any topological relationships within the input data are also represented in the grid. This implementation supports the use of non-numeric patterns. In layman's terms, a SOM can be useful when you want to discover the underlying structure of some data. I have a brief tutorial in the wiki, which I hope to expand over the next few weeks.