Hello Paul. Le sam. 24 avr. 2021 à 04:42, Paul King <paul.king.as...@gmail.com> a écrit : > > I added some more comments relevant to if the proposed algorithm > belongs somewhere in the commons "math" area back in the Jira: > > https://issues.apache.org/jira/browse/MATH-1563
Thanks for a "real" user's testimony. As the ML is still the official forum for such a discussion, I'm quoting part of your post on JIRA: ---CUT--- For linear regression, taking just one example dataset, commons-math is a couple of library calls for a single 2M library and solves the problem in 240ms. Both Ignite and Spark involve "firing up the platform" and the code is more complex for simple scenarios. Spark has a 181M footprint across 210 jars and solves the problem in about 20s. Ignite has a 87M footprint across 85 jars and solves the problem in > 40s. But I can also find more complex scenarios which need to scale where Ignite and Spark really come into their own. ---CUT--- A similar rationale was behind my developing/using the SOFM functionality in the "o.a.c.m.ml.neuralnet" package: I needed a proof of concept, and taking the "lightweight" path seemed more effective than experimenting with those platforms. Admittingly, at that epoch, there were people around, who were maintaining the clustering and GA codes; hence, the prototyping of a machine-learning library didn't look strange to anyone. Regards, Gilles >>> [...] --------------------------------------------------------------------- To unsubscribe, e-mail: dev-unsubscr...@commons.apache.org For additional commands, e-mail: dev-h...@commons.apache.org
