Pierre-Edouard's paper on Gaussian Mixture Models in J deserves a place in the J Wiki showcase essays.
Skip Skip Cave Cave Consulting LLC On Fri, Jan 12, 2018 at 4:44 PM, Scott Locklin <[email protected]> wrote: > Nice work! > FWIIW, Mixture, Naive Bayes and semisupervised versions of each with the > EM-algo can often be cooked up from the same raw materials. And > multivariate/Bernoulli, I think can be derived from the mean term in the > Gaussian example. Multivariate and Bernoulli should probably be done > with sparse arrays, but with these 2-3 things, supervised, unsupervised > and semi-sup, you can solve an awful lot of data science problems! > > -SL > ---------------------------------------------------------------------- > For information about J forums see http://www.jsoftware.com/forums.htm > ---------------------------------------------------------------------- For information about J forums see http://www.jsoftware.com/forums.htm
