Can you point me to the class I should look at to see how this is done?
On Tue, Jul 31, 2012 at 10:49 AM, Robin Anil <[email protected]> wrote: > 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 >>
