2012/7/20 Philipp Singer <[email protected]>:
> Everything works fine now. The sad thing though is that I still can't
> really improve the classification results. The only thing I can achieve
> is to get a higher recall for the classes working well in the background
> model, but the precision sinks at the same time. Overall I am staying at
> about the same average score when incorporating the background model.
>
> If anyone has any further ideas, please let me know ;)
Well, since Gael already mentioned semi-supervised training using
label propagation: I have an old PR which has still not been merged,
mostly because of API reasons, that implements semi-supervised
training of Naive Bayes using an EM algorithm:
https://github.com/scikit-learn/scikit-learn/pull/430
I've seen improvements in F1 score when doing text classification with
this algorithm. It may take some work to get this up to speed with the
latest scikit-learn, though.
(Just out of curiosity, which topic models did you try? I'm looking
into these for my own projects.)
--
Lars Buitinck
Scientific programmer, ILPS
University of Amsterdam
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