Hi r/MachineLearning.
So I asked a previous question about SOMs, and I learned a lot. This however put me on the path to studying how to visualize them, specifically, using what is known as a U-Matrix.
Now... I am about to pull my hair out trying to figure out, how exactly, a U-matrix is constructed for visualization of Self-Organizing-Maps. (SOMS, aka Kohonen Nets).
Every last google result I have found does not help, is contradictory, has a massive number of typos, or otherwise very broad.
I am asking a simple question: I have an output grid of 3x3 output units: How do I construct a U-matrix from this??
Links so far:
1) Original Paper. (RIDDLED with errors, typos, and misleading information. The U-matrix part is so full of errors I do not know how this paper got published.)
2) The SOM toolbox manual that quotes the above paper. (Explains how to do it for an output line, but does not explain how to do it for an output grid).
3) Another paper. (Explains how to make a U-matrix, but completely contradicts his first paper, and the SOM toolbox that it is based on).
4) A similar question on SE that didnt really get anywhere.
To facilitate this ... I have made up a very simple example, and this should be simple to answer for someone familiar with SOMs and U-Matricies.
I have a 3x3 output grid, that means, 3x3 output neurons that have already been trained. All neurons have dimension, say, 4. Now I want to make a U-matrix.
How exactly do I do that?
Please give me a step-by-step, I cannot seem to find anything on it! :-/
Thanks!!
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