You need to re-think. What you said is nonsense. Use an appropriate
clustering algorithm.
(a can be near b; b can be near c; but a is not near c, using "near"
closer than threshhold)
Cheers,
Bert
Bert Gunter
Genentech Nonclinical Biostatistics
(650) 467-7374
"Data is not information. Information is not knowledge. And knowledge
is certainly not wisdom."
H. Gilbert Welch
On Thu, Feb 13, 2014 at 12:00 AM, Dario Strbenac
<dstr7320 at uni.sydney.edu.au> wrote:> Hello,
>
> I'm looking for a function that groups elements below a certain
distance threshold, based on a distance matrix. In other words, I'd like to
group samples without using a standard clustering algorithm on the distance
matrix. For example, let the distance matrix be :
>
> A B C D
> A 0 0.03 0.77 1.12
> B 0.03 0 1.59 1.11
> C 0.77 1.59 0 0.09
> D 1.12 1.11 0.09 0
>
> Two clusters would be found with a cutoff of 0.1. The first contains A,B.
The second has C,D. Is there an efficient function that does this ? I can think
of how to do this recursively, but am hoping it's already been considered.
>
> --------------------------------------
> Dario Strbenac
> PhD Student
> University of Sydney
> Camperdown NSW 2050
> Australia
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