10-10-2025, 10:42 PM
(10-10-2025, 09:37 PM)quimqu wrote: You are not allowed to view links. Register or Login to view.(10-10-2025, 09:26 PM)kckluge wrote: You are not allowed to view links. Register or Login to view.The thing that makes PCA based cluster analysis (in particular) of sub-dialects tricky is
As there is no prior mention of PCA cluster analysis in the ppst I imagine you think I did cluster analysis, but that is not the case. My analysis is topic analysis, usindg Latent Dirichlet Allocation, that is not using PCA, neither k-means.
LDA is a probabilistic model used to discover hidden topics in a collection of documents. It is language agnlstic and assumes that each document is composed of several topics (K), and each topic is a distribution over words. By analyzing the patterns of word co-occurrence across documents, LDA infers which topics are present and how strongly each document is associated with them. The model is unsupervised and typically estimated using Bayesian inference methods such as variational inference or Gibbs sampling. Its main goal is to uncover the underlying thematic structure of text corpora. In my case, the language units were the paragraphs.
Sorry for the confusion, I was thinking of Rene's PCA-ish cluster analysis @ You are not allowed to view links. Register or Login to view., which is what I (incorrectly) thought he had been referring to earlier in the thread.
As for LDA -- is it "language agnostic" in the sense that it doesn't require that the documents are in a common language, or only in the sense that it doesn't require knowing the (common) language?
If it's only agnostic in the second sense, I have heartburn about assuming that the Voynich text is homogeneous in that way. The most common words in a given language are typically dominated by function words rather than content words, but if you compare the 10 most frequent words in the set of Herbal A pages vs. the set of Herbal B pages in the herbal quires at the front of the mss (apologies for the Currier):
Rank: 1 2 3 4 5 6 7 8 9 10
HerbB: 8AM SC89 OR AR AM 8AR 89 S89 4OFC89 ZC89
HerbA: 8AM SOE SOR 89 S9 2 ZOE Q9 8AN ZO
Given that those are all similarly formatted one-big-picture-of-a-plant pages and the minimal overlap (2 of 10) between those two sets of words I have a lot of trouble buying those reflect a common underlying language/cipher (key)/whatever.


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