FWIW I agree on 1 and 2, and 3. Certainly for now. There's a tension between having too broad, and too narrow, a mission. "Machine learning in Java" is already pretty broad. Go too broad with limited resources and the project ends up being many half-finished pieces of code, rather than a few coherent, finished things.
I wouldn't want most people's first impression of the project to be a collection of works in progress. So at the moment I'd favor sticking to Java, and MapReduce, and build a fairly complete body of work there before branching out. On Fri, Nov 20, 2009 at 2:32 PM, Grant Ingersoll <[email protected]> wrote: > Makes sense. I've always said Mahout is about (and I think others feel the > same): > 1. scalable Machine Learning - scale is open to interpretation. Some > algorithms simply do not work on M/R, as you point out, but we are still > interested in making them as fast as possible. This is well documented in > our archives. > 2. ASL > 3. Java (we have a Pig PLSI implementation that will likely be committed > soon, for instance)
