# [R] Similarity matrix

Prof Brian Ripley ripley at stats.ox.ac.uk
Wed Apr 11 13:26:44 CEST 2001

```On Wed, 11 Apr 2001, Jari Oksanen wrote:

>
> ripley at stats.ox.ac.uk said:
> > The usual way to do this is to scale similarities to [0, 1] and take D
> > = sqrt(1-S) I believe, but I don't know why.
>
> I think it depends on (i) the index used, (ii) whether you want the
> similarity to be a `metric', and (iii) whether you care about ii.
>
> For most sum-of-squares based indices  D = sqrt(1-S) preserves the
> `metric' or even `Euclidean' properties.
>
> There may be a slight problem with R distance indices, since most of
> them are not scaled to [0,1] originally (Canberra distance could be

Um. Harrell, not me, wants to turn similarities into dissimilarities,
not v.v!

--
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272860 (secr)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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