ok, I see. thank you all.
On Sat, Mar 22, 2008 at 12:32 AM, Ted Dunning <[EMAIL PROTECTED]> wrote: > > Yes. > > This is what I was saying. > > The decision about what is good to have in mahout has most to do with what > machine learning related task needs parallelism not whether it is "learning" > or "feature selection" or "feature extraction". > > That said, the mahout project also needs reference implementations of all of > these algorithms in sequential form for testing. > > > On 3/21/08 2:08 AM, "Hao Zheng" <[EMAIL PROTECTED]> wrote: > > > I understand. Actually, I mean the other thing. Maybe "feature > > selection" is not precise, let me restate my question. > > > > Generally, no matter for image recognition or text classification, we > > have to ture the original material into a featrue vector. This step is > > called "feature extration" or sth like that. My question is will this > > step be part of the mahout project? If yes, we have to care about the > > transformation step; if not, all we need to process are the numbers, > > which will make thing easier. > > > > On Fri, Mar 21, 2008 at 9:02 AM, Ted Dunning <[EMAIL PROTECTED]> wrote: > >> > >> I think a better description is that this project is about ML algorithms > >> that need large scale. > >> > >> If you have very inexpensive feature selection that can run sequentially, > >> then it probably doesn't matter to use hadoop/mahout for that. Some forms > >> of feature extraction is very expensive, however, and could definitely > >> benefit from parallelism. For instance, you could imagine that the > >> feature > >> extraction step involves a large scale non-deterministic clustering. It > >> might even be that the the feature extraction requires parallel > >> processing, > >> but the actual learning algorithm does not. > >
