Hi Mathieu,
thanks for the response and the feedback. It is correct that there are
other more recent algorithms available, on the other hand CW learning only
requires minor extensions from passive-aggressive learning (PA) which is
already available in scikit-learn and it achieves very competitive
performance (better than PA, SVM, maxent) and very good performance for
high dimensional, sparse classification problems, like text classification.
Thanks for the offer to contribute to lightning, I will have a look.
regards,
Daniel
>Hi Daniel,
>I think CW is a bit outdated and also a bit too specific (it supports only
> the hinge loss). Algorithms like Adagrad are more generic. Thus, I think
CW
> is not a good candidate for inclusion in scikit-learn.
> That said, I would welcome a contribution in lightning:
> https://github.com/scikit-learn-contrib/lightning
> In addition to the references you gave, there is also an ICML paper:
> Exact Soft Confidence-Weighted Learning by J. Wang.
> Mathieu
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