On 14 March 2012 08:54, Lars Buitinck <[email protected]> wrote:

> 2012/3/13 Robert Layton <[email protected]>:
> > Lars, you are right, it should have metric='precomputed' in it.
> > However by passing the distance matrix without a metric, the features
> become
> > "distance to point i", which act as sort of meta-features anyway,
> allowing
> > training to happen. This means that it works with a distance matrix as
> > input, even though that is probably not what you wanted. I believe that
> some
> > classifiers use this concept, although it has escaped me which ones.
>
> But then still the demo is odd, because it is passing a similarity
> matrix, not distances:
>
> D = distance.squareform(distance.pdist(X))
> S = 1 - (D / np.max(D))
>
>
> --
> Lars Buitinck
> Scientific programmer, ILPS
> University of Amsterdam
>
>
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Then that is a mistake (although ironically should not affect what I said
about meta-features...).


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