And all of Colt is < 1M. I would say that it isn't all that likely that the library will get to more than a few megs (if that). At that size, it really doesn't matter that there is a bit of dross along for the ride.
How many here would rather pick and choose pieces out of rapid miner or weka? Or would you rather just download the comprehensive jar and be ready to roll? I also think that the example of text translation vs spam categorization is a bit of a straw man. It is much more likely that these would be entirely independent applications that would themselves like to download the (single) Mahout jar. On 1/29/08 11:45 PM, "Isabel Drost" <[EMAIL PROTECTED]> wrote: > On Wednesday 30 January 2008, Steve Rowe wrote: >> On 01/29/2008 at 6:44 PM, Lukas Vlcek wrote: >>> I would prefer to have an option not to work with whole library but >>> select only specific algorithms and optionally their particular >>> modifications. >> >> +1 > > +1 I would at least like to have one downloadable jar for each algorithm > family (why would I as a user want to download the functionality for > translating texts, if all I want to do is build a better spam classification > plugin for spam assassin?) plus one library for the common code like input-/ > output-filters. > > Maybe we should look at other machine learning frameworks that followed > the "all in one jar" path to get a feeling on how large a project can easily > get. Please be careful with these numbers, as both projects are trying to > provide whole machine learning frameworks with GUIs for experimentation, > algorithms for evaluation and the like. > > Weka Compiled: 4.4M > Rapid Miner Sources: 12M Compiled: 4.5M (21M including all dependencies) > > Isabel
