Thanks for the update on that PR I will definitely take a look.
I wonder if they will run into the exact same Colt issues as mahout did?! This DSL looks great, I'm gonna play around with it as soon as I get a chance. One question - breeze has quite a similar syntax that is a bit simpler in some ways - basically * for matrix multiply and :* for elementwise. Would something similar work here? Would be quite nice to have same syntax but different backends that are swappable ;) — Sent from Mailbox for iPhone On Sat, Jul 27, 2013 at 2:42 AM, Dmitriy Lyubimov <[email protected]> wrote: > coincidentally, spark mlib just posted a pull request intended to add > support for dense and sparse vectors, looks quite similar. > https://github.com/mesos/spark/pull/736. They seem to choose JBlas backing > for dense stuff (although at a vector level there's probably not much > reason to) and as-is Colt for sparse stuff. > On Fri, Jul 26, 2013 at 5:20 PM, Dmitriy Lyubimov <[email protected]> wrote: >> >> >> >> On Fri, Jul 26, 2013 at 5:07 AM, Ted Dunning <[email protected]>wrote: >> >>> This sounds great in principle. I haven't seen any details yet (haven't >>> had time to look). >>> >>> Is there a strong reason to go with the R syntax for multiplication >>> instead >>> of the matlab convention that a*b means a.times(b)? >>> >> >> As discussed, but also because matlab style elementwise operators are >> impossible to keep at proper precedence level in scala. It kind of has to >> start with either '*' or '%' to keep proper precedence, '.*' will not work >> unfortunately. And mix along the lines "some of Matlab, some of perhaps >> completely something else' does not seem appealing at all. >> >>
