How does a supervised Kohonen network work? I understand the details of the unsupervised Kohonen network, but what does the supervised Kohonen network do exactly?

I have found the answer to my own question in here:
[https://www.jstatsoft.org/article/view/v021i05][1]
(Self- and Super-organizing Maps in R: The kohonen Package)
There are essentially two maps: One for the predictors, and one for the class labels, and the final map is a weighted average of those two maps.
