[R] clara - memory limit

Prof Brian Ripley ripley at stats.ox.ac.uk
Wed Aug 3 19:26:54 CEST 2005


On Wed, 3 Aug 2005, Prof Brian Ripley wrote:

>> From the help page:
>
>     'clara' is fully described in chapter 3 of Kaufman and Rousseeuw
>     (1990). Compared to other partitioning methods such as 'pam', it
>     can deal with much larger datasets.  Internally, this is achieved
>     by considering sub-datasets of fixed size ('sampsize') such that
>     the time and storage requirements become linear in n rather than
>     quadratic.
>
> and the default for 'sampsize' is apparently at least nrow(x).

Correction, sorry, in your case 40 + 2*k = 54.

> So you need to set 'sampsize' (and perhaps 'samples') appropriately,

That might be it, but a traceback() showing where the error is occurring 
would help.  Another possible place is in the initial manipulations 
scaling the data matrix.

Since sub-sampling is used, you can start with a much smaller subset of 
the data.

>
>
> On Wed, 3 Aug 2005, Nestor Fernandez wrote:
>
>> Dear all,
>> 
>> I'm trying to estimate clusters from a very large dataset using clara but 
>> the
>> program stops with a memory error. The (very simple) code and the error:
>> 
>> mydata<-read.dbf(file="fnorsel_4px.dbf")
>> my.clara.7k<-clara(mydata,k=7)
>> 
>>> Error: cannot allocate vector of size 465108 Kb
>> 
>> The dataset contains >3,000,000 rows and 15 columns. I'm using a windows
>> computer with 1.5G RAM; I also tried changing the memory limit to the 
>> maximum
>> possible (4000M)
>
> Actually, the limit is probably 2048M: see the rw-FAQ Q on memory limits.
>
>> Is there a way to calculate clara clusters from such large datasets?
>
> -- 
> 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 272866 (PA)
> Oxford OX1 3TG, UK                Fax:  +44 1865 272595
>

-- 
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 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595




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