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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!

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  • $\begingroup$ 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) $\endgroup$ – shadowtalker Feb 24 '15 at 2:56
  • $\begingroup$ 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 $\endgroup$ – formacero10 Feb 27 '15 at 1:00
  • $\begingroup$ exactly. Hence, my question: does it make substantive sense to use a 1-D lattice? $\endgroup$ – shadowtalker Feb 27 '15 at 1:14
  • $\begingroup$ 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? $\endgroup$ – formacero10 Feb 27 '15 at 1:24
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In my expirience there isnt an objective rule for the selection of the lattice. A 2d lattice results to better topological adaptation than an 1d lattice but then a 3d lattice gets even beter results. Since one of the advantages of the som map is the visual exploration of the results you go by that. A 3d lattice becomes kind of hard to explore so usually the standard choice is a 2d lattice. As ssdecontrol mentioned an 1ď lattice will give you a very "naive" relationship between the clusters - nodes.

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