The algorithm in question is Kohonen's SOM. But the question could also apply to PCA and some others.
When the umatrix (or the codebook?) is examined, is there a way to tell how successful clustering was?
And would it be a good idea to apply GA's to optimize size, lattice structure, learning rate, and the learning degradation functions as well as the epoch count for clustering, or is there a danger of overfitting in this instance?
Assume that the SOM data is coming from a demonstrably weak PRNG and that the very first attempt shows a distinct structure. Is there some statistical property or algorithm that can evaluate the presence and degree of structure to be used for a GA fitness function?