BTW, Sage has a Cythonized HMM
implementation<http://www.sagemath.org/doc/reference/stats/sage/stats/hmm/hmm.html#sage.stats.hmm.hmm.HiddenMarkovModel>
.
Code on Github<https://github.com/sagemath/sage/tree/master/src/sage/stats/hmm>
Types supported:
1. Discrete
2. Gaussian
3. Mixture of Gaussian
On Mon, Dec 9, 2013 at 11:54 PM, Gael Varoquaux <
[email protected]> wrote:
> On Mon, Dec 09, 2013 at 10:09:32AM +0100, Olivier Grisel wrote:
> > 2013/12/8 Robert Layton <[email protected]>:
> > > I remember a while ago hearing of a (probably unofficial) scikit-learn
> > > experimental repository, where things that were sklearn-compatable, if
> not
> > > polished code, were put.
>
> > > Does that still exist?
>
> > It never existed as a generic throwaway repo but some projects like
> > @mblondel's lightning for instance follow the sklearn API:
>
> > https://github.com/mblondel/lightning
>
> It would be great to create a wiki page.
>
> > +1 as well. Do we want to put this new repo under the scikit-learn
> > organization on github or on another account?
>
> Under a different organization I believe. The reasons being that 1) we
> don't want to be responsible for it, 2) we want to be able to easily hand
> it off to other people.
>
> G
>
>
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