hi gael,
My position on your different points is:
>
> 1 Genericity for the sake of genericity is really not something that
> I think we should pursue. It comes with a maintenance cost. It
> particular it tends to lead to significantly higher cyclomatic
> complexity in the code. In addition, too many options confuse the
> non expert. Thus for a different approach than the
> current one to be added in the scikit, it should bring a
> demonstrated gain. For the same reason, if the new approach
> outperforms the current approach in all respects, this means that
> the current approach should be phased out.
>
sounds good. i have received some more mathematical insight from some
folks. as i try it, i'll keep everybody posted.
> 2 It is the 'D' matrix in the UvL paper. If you find a better
> formulation for the docstring I'd love to merge it in, as it might
> make the code easier to follow.
>
> To sum up the plan of action on spectral clustering/embedding, as long as
> we are not able to witness clear cut improvements on examples (possibly
> new ones), I am not in favor of merging in a change of strategy.
sounds good.
> In
> addition, I am not in favor of scheduling any change other than trivial
> ones (e.g. documentation) for the upcoming release: I think that rushing
> code in will not leave us time to gather the insight necessary for good
> code and APIs.
>
i wouldn't merge this into the upcoming release even if i sent in a PR for
this. there is a lot more coming in the way of unifying/cleaning up the
manifold learning work. i've been a little slow on this, but timeslicing
has been difficult.
cheers,
satra
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