For learning GHSOM I figured out I should study SOM as a first step.
Now, I know the basics of SOM, about weighted vectors and euclidean distances: when the human brain cannot easily process more than two dimensions of data, SOM will cluster, or in other words, map the data from high dimensions into lower ones (from this awesome link).
I found out what vertices of weights and similarity will do, but I still couldn't understand exactly how GHSOM works. I read in an essay that it works with layers of SOMs. With some examples I hope to understand it better.
Would you please tell me a proper reference for a beginner to study about it? Or can anyone explain how the algorithm works?
Thanks in advance.