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I think CW is a bit outdated and also a bit too specific (it supports only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
On Tue, Mar 29, 2016 at 12:34 PM, Daniel Dahlmeier <
ddahlme...@googlemail.com> wrote:
> Dear scikit-learn community,
>
> is there an implementation of confidence-weighted (CW) for scikit-learn
> or is there an interest to have CW learning implemented for scikit? I
> have noticed that the related passive-aggressive algorithm is already
> implemented as part of the linear learner but CW learning is not.
>
> I have implemented CW learning during my graduate school days and would be
> interested to port the implementation to scikit-learn if this is seen as
> useful.
>
> regards,
> Daniel
>
>
> References
>
> =============
>
> Confidence-Weighted Linear Classification
>
> Mark Dredze, Koby Crammer and Fernando Pereira
>
> Proceedings of the 25th International Conference on Machine Learning
>
> (ICML), 2008
>
>
> Multi-Class Confidence Weighted Algorithms
>
> Koby Crammer, Mark Dredze and Alex Kulesza
>
> Empirical Methods in Natural Language Processing (EMNLP), 2009
>
>
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