Hi Terry,
We need to find a uniform way over the whole scikit to indicate missing
data. Hence, 0 cannot be how missing data is spotted.
A solution would be to use "Nan" but it is not very satisfying either, as
this could lead to think there is missing data, while there isn't.
Maybe we should add an argument named missing, with how the missing data is
indicated in the matrices ? For example, the signature of the MDS, using
nan as missing data would be something like:
mds.fit(X, missing=np.nan)
Cheers,
N
On 28 March 2013 16:51, Terry Peng <[email protected]> wrote:
> Hi all,
>
> I was discussing with Nelle to add an algorithm to solve the classical
> MDS with svd. but one thing we don't sure is how to check missing data so
> we can fall back to SMACOF in that case.
> my idea is to check if there are any 0 in non-diagonal elements.
>
> what do you think?
>
> Thanks & Regards,
> --Terry
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