Pat et. al, The whole problem with original suggested consensus statement is that it reads as "we are building MLLib for Spark (oh wait, there's already such a thing)" and then "we are building MLLib for 0xdata" and then perhaps for something else. Which can't be farther from the true philosophy of what has been done. If not it, then at best it reads as "we don't know what it is we are building, but we are including some Spark dependencies now". So it is either misleading, or sufficiently vague, not sure which is worse.
If a collection of backend-specific separated MLLibs is the new consensus, i can't say i can share it. In fact, the only motivation for me to do anything within this project was to fix everything that (per my perhaps lopsided perception) is less than ideal with the approach of building ML projects as backend-specific collections of black-box trainers and solvers and bring in an ideology similar to Julia and R to the jvm-based big data ML . If users are to love us, somehow i think it will not be because we ported yet another flavor of K-means to Spark. At this point I think it is a little premature to talk about an existing consensus, it seems. On Tue, May 6, 2014 at 12:41 PM, Pat Ferrel <[email protected]> wrote: > +1 > > I personally won’t spend a lot of time generalizing right now. > Contributors can help with that if they want or make suggestions. > > On May 6, 2014, at 9:23 AM, Ted Dunning <[email protected]> wrote: > > As a bit of commentary, it is clear that what the committers are working on > is Spark > Mahout committers, with very rare exceptions, are not working on Spark. Spark committers and contributors are working on Spark.
