[R] Distance between sets of points in transformed environmental space

Mario Valle mvalle at cscs.ch
Tue Dec 1 11:31:47 CET 2009


silhouette coefficients?
It measure for each point how similar is to its cluster other points and how dissimilar
from the points of other clusters.

P.N. Tam, M. Steinbach, V. Kumar, Introduction to data mining, Addison-Wesley, 2006 page 541

Hope it helps.
			mario

Charlotte Maia wrote:
> Well, here's another naive post from me (hopefully better than the last one).
> 
> Firstly I'm not sure computing euclidean distance is that simple. I
> would assume temperatures and precipitation would need to be
> standardised in some way.
> 
> I think the notion of how far away something is, and how distinct
> location wise something is, are quite different, so maybe two
> measures?
> 
> For distance per se, I think your first idea is the best.
> Plus simple is always good...
> 
> For distinctness, given one one of two sets, for each point, you could
> just compute the closest point to it. If the closest point is a member
> of the same set, we will call that a + point, if the closest point is
> a member of the other set, we will call it a - point. In principle the
> measure of distinctness would be the sum of the +'s, however there
> might need to be some scaling to take into account the number of
> points in each set.
> 
> There are also a lot of fancy things out there, so someone will
> probably come up with a much fancier (and possibly better) idea than
> this.
> 
> Well, that's just my rant, before I go to bed.
> 
> 
> kind regards

-- 
Ing. Mario Valle
Data Analysis and Visualization Group            | http://www.cscs.ch/~mvalle
Swiss National Supercomputing Centre (CSCS)      | Tel:  +41 (91) 610.82.60
v. Cantonale Galleria 2, 6928 Manno, Switzerland | Fax:  +41 (91) 610.82.82




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