# SOM dimension doubt

I'm currently working on a research of data clustering using an ANN for self-organizing maps. I'm performing experiments using Matlab, over a Dataset of 20,000 samples and almost 80 variables.

The ANN requieres to set up a "one or two dimensional lattice", which is used to place neurons at each node. this map's function is to transform an arbitrary signal (with n dimensions) into a discrete representation with topological order.

I haven't found yet a rational criteria to select a lattice with one or two dimensions, it's worth noting that a node does not represent necessarilly a cluster because you can group a set of nodes in one cluster (it depends on how close are each other).

Does anybody knows a good criteria to set up the lattice? Greetings!

• This might come down to interpretation. Does it make sense to cluster solely on a single axis? Think: hot/cold, conservative/liberal, high/low. If that seems restrictive to you then maybe a single axis might not be enough (not to mention it would be somewhat unconventional) – shadowtalker Feb 24 '15 at 2:56
• First of all, let offer you some apologies, my question wasn't clear at all, I've already change it, hope it fits better. Actually, in a SOM clustering process, the lattice's dimensions doesn't represent a single variable, on the contrary, the lattice is a representation of n variables which conserves the original topological order of the data. Thank you so much – formacero10 Feb 27 '15 at 1:00
• exactly. Hence, my question: does it make substantive sense to use a 1-D lattice? – shadowtalker Feb 27 '15 at 1:14
• I've concluded (sort of... I'm not sure) that it makes sense if you want a fixed ammount of clusters, so you simply define a lattice having as much nodes as clusters you need, but you lose quiality in the topological representation of the data. This quality lost is a clear argument to ditch a 1D lattice? – formacero10 Feb 27 '15 at 1:24