There was some discussion along these lines last year, but I don't think
anyone has worked on it yet. Scikit-learn doesn't currently have the
ability to do manifold learning from a precomputed distance matrix, but
it could be extended to that pretty easily.
What it would take would be to modif
I'd like to use isomap (and other manifold learning techniques) with
abstract metric spaces (and perhaps more generally similarity and
dissimilarity matricies - but we can put that aside for the moment).
It looks to me like isomap assumes points are described by points in
R^N or some data structure
