You should be able to use a RealBasicEventStream, with your events specified
in text files as
feature1=value1,feature2=value2, ... featureN=valueN,outcome
Note, you can just give feature42 (without =value42) and it assumes the
value is 1.
You can then train a model by calling opennlp.maxent.ModelTrainer and
include the -real option.
Or, if you are doing it all with the API, you can use create Events with
this constructor:
public Event(String outcome, String[] context, float[] values) {
where values[i] is the td-idf value for context[i]
Hope this helps!
-Jason
On Fri, Mar 4, 2011 at 8:56 AM, Francesco Serra <[email protected]> wrote:
>
> Hello, I'm trying to make text classification with maximum entropy model.
> I implemented some code that processes text files in input and calculates
> TF and IDF terms..
> I wanna ask if someone has idea how to use these terms to make
> classification with maximum entropy..
> Thanks to everyone.
>
--
Jason Baldridge
Assistant Professor, Department of Linguistics
The University of Texas at Austin
http://www.jasonbaldridge.com
