Interesting! Clearly this is doing the right sorts of things, so it should do something in the vicinity of what's needed...
still tho -- My intuition remains that a more fully nonlinear NN approach might do better than a "linear algebra plus thresholding" approach like this... Put differently, I think we need some more powerful learning method like evolutionary-learning or backprop in there, to capture the nonlinear dependencies btw word tuples... But this seems worth trying and who knows, maybe it will be awesome... it will be good to compare different approaches... ben On Tue, Jun 6, 2017 at 2:13 PM, Linas Vepstas <[email protected]> wrote: > Ben, > > The attached PDF describes the algorithm I plan to implement for performing > the actual clustering. As of right now, I really like it: its simple, its > straightforward, I believe it will work well. It might be a real CPU > burner, though, and so blue skies might bring tears. > > I like to think of it as a kind-of "pattern miner", as it can be made > completely generic; it works for any correlation matrix. I suspect that it > is totally different from what Shujing does, which is still on my list of > things to study in greater detail. > > --linas > > -- > You received this message because you are subscribed to the Google Groups > "link-grammar" group. > To unsubscribe from this group and stop receiving emails from it, send an > email to [email protected]. > To post to this group, send email to [email protected]. > Visit this group at https://groups.google.com/group/link-grammar. > For more options, visit https://groups.google.com/d/optout. -- Ben Goertzel, PhD http://goertzel.org "I am God! I am nothing, I'm play, I am freedom, I am life. I am the boundary, I am the peak." -- Alexander Scriabin -- You received this message because you are subscribed to the Google Groups "opencog" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To post to this group, send email to [email protected]. Visit this group at https://groups.google.com/group/opencog. To view this discussion on the web visit https://groups.google.com/d/msgid/opencog/CACYTDBdi2j-OhzOAvDhxGH%3DfNkRLccO%2B1_tis4OZVcLyAZvWJQ%40mail.gmail.com. For more options, visit https://groups.google.com/d/optout.
