On 2 Jan 2013 21:19, "Andreas Mueller" <notifications@github.com> wrote:
>
> In sklearn/manifold/mds.py:
>
> >              disparities = dis_flat.copy()
> >              disparities[sim_flat != 0] = disparities_flat
> >              disparities = disparities.reshape((n_samples, n_samples))
> > -            disparities *= np.sqrt((n_samples * (n_samples - 1) / 2)
> > -                                   / (disparities ** 2).sum())
> > +            disparities *= (n_samples * (n_samples - 1) / 2)
>
> Does it change the outcome? And is there any reason to include it or not
to include it? I'd rather have the same behavior across versions where
possible.

It changes the scaling of the solution.

>
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