(20-12-2025, 03:49 PM)Rafal wrote: You are not allowed to view links. Register or Login to view.Quote:I mean, suppose folio A and folio B are correlated under metric C (of whatever the proper lingo is). So what?
It means that they are similar on some dimension.
Thank you for the explanation, but the problem for me is not in the math part of it, I probably can even code PCA from scratch if needed. I think I once implemented SVD for an embedded platform in pure C, but it was a long time ago.
The question is with the further implications from the similarity. Similarity can emerge in many possible ways, even purely random sequences can show some similarity by chance. It's good that some of the studies use some form of shuffling as the controls, but this only proves that the similarity is not spurious (unless the similarity metric was fine tuned in the first place). It doesn't show whether it's intentional or a byproduct of some other factor. If the Voynich Manuscript is a plaintext in some language, then it should be possible to identify topic or language similarity, but if it's not, then I see no way to meaningfully interpret the results of PCA at all.