You can pass in any vector(not just a tfidf vector). For example the asf-email example script using Vectors generated using the randomized encoding. ------ Robin Anil
On Tue, Jul 31, 2012 at 12:26 PM, Sean Owen <[email protected]> wrote: > I don't know this code too much, but, there is simply a step in front > I believe that vectorizes text with TF-IDF. The result are simple > vectors. You could just inject your vectors (i.e. real-value > attributes) at that stage and skip the TF-IDF. It may need a little > hacking. > > On Tue, Jul 31, 2012 at 6:21 PM, Eric Friedman <[email protected]> > wrote: > > All of the examples that I've found for training NB classifiers seem > > to have textual data as input. Is there a way to build a classifier > > with more general attributes? > > > > I found this jira ticket > > (https://issues.apache.org/jira/browse/MAHOUT-286), but it's been > > closed:duplicate under > > https://issues.apache.org/jira/browse/MAHOUT-155, which doesn't seem > > to address the underlying question. > > > > I know that I can do this with weka, but not at scale -- is mahout > > only able to build textual classifiers? > > > > Thanks, > > Eric >
