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From "Claudia Grieco" <gri...@crmpa.unisa.it>
Subject R: Help with Mahout Classification
Date Mon, 31 Jan 2011 10:55:10 GMT
Hi,
Just one more question about the SGD classifier.
When you say " train one classifier per category" it means that for every possible tag (ex.
sport) I should create a classifier that classifies it as "sport" or "not sport"? (sorry,
English is not my first language)
Do you think this approach is feasible for many categories (let's say 50)?
Thanks again
Claudia

-----Messaggio originale-----
Da: Ted Dunning [mailto:ted.dunning@gmail.com] 
Inviato: venerdì 14 gennaio 2011 17.32
A: user@mahout.apache.org
Oggetto: Re: Help with Mahout Classification

If you don't have truly massive volumes, then SGD is almost certainly a
better choice because it is simpler.

If you have more than 10 million training examples *per*model* and
*after*downsampling* then you should consider alternatives but even up to
about 50 million training examples, SGD will do very well.  SGD is currently
also mostly appropriate for sparse feature vectors.

Having multiple categories isn't a big deal.  The simplest solution is to
train a classifier per category.  There are more advanced arrangements,
though.  For instance, you can train one classifier per category (the first
level models), then train another classifier per category where the inputs
are the outputs of the first level models.  Which techniques will help is
highly dependent on your particular problem.

On Fri, Jan 14, 2011 at 7:10 AM, Claudia Grieco <grieco@crmpa.unisa.it>wrote:

> Do you think SGD will be a better choice? New documents are added to the
> training set very often and documents can belong to more than one category
> (ex. "sport", "italy")


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