Have you considered the dbscan function in library fpc, or was it another
one?
dbscan in fpc doesn't have a "distance" parameter but several options, one
of which may resolve your memory problem (look up the documentation of the
"memory" parameter).
Using a distance matrix for hundreds of thousands of points is a recipe
for disaster (memory-wise). I'm not sure whether the function that
you used did that, but dbscan in fpc can avoid it.
It is true that dbscan requires tuning constants that the user has to
provide. There is unfortunately no general rule how to do this; it would
be necessary to understand the method and the meaning of the constants,
and how this translates into the requirements of your application.
You may try several different choices and do some cluster validation to
see what works, but I can't explain this in general terms easily via
email.
Hope this helps at least a bit.
Best regards,
Christian
On Fri, 3 Jun 2011, Paco Pastor wrote:
Hello everyone,
When looking for information about clustering of spatial data in R I was
directed towards DBSCAN. I've read some docs about it and theb new
questions have arisen.
DBSCAN requires some parameters, one of them is "distance". As my data
are three dimensional, longitude, latitude and temperature, which
"distance" should I use? which dimension is related to that distance? I
suposse it should be temperature. How do I find such minimum distance
with R?
Another parameter is the minimum number of points neded to form a
cluster. Is there any method to find that number? Unfortunately I
haven't found.
Searching thorugh Google I could not find an R example for using dbscan
in a dataset similar to mine, do you know any website with such kind of
examples? So I can read and try to adapt to my case.
The last question is that my first R attempt with DBSCAN (without a
proper answer to the prior questions) resulted in a memory problem. R
says it can not allocate vector. I start with a 4 km spaced grid with
779191 points that ends in approximately 300000 rows x 3 columns
(latitude, longitude and temperature) when removing not valid SST
points. Any hint to address this memory problem. Does it depend on my
computer or in DBSCAN itself?
Thanks for the patience to read a long and probably boring message and
for your help.
--
-----------
Francisco Pastor
Meteorology department, Instituto Universitario CEAM-UMH
http://www.ceam.es
-----------
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skype: paco.pastor.guzman
Researcher ID: http://www.researcherid.com/rid/B-8331-2008
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