On Oct 15, 2015, at 4:51 AM, Bhawana Sahu wrote:
> I am using R in my project for analysis of data, and I have generated SVM
> model using kernlab package with the dataset (3000 rows and 281 columns).
> Now I want to generate this model for dataset containing 8000 rows and 281
> column, but here I am getting an error saying that "cannot allocate
vector
> of size 2.4 gb"
>
> Earlier I was running this model on system with 4GB RAM, now I tried this
> on the system having RAM size of 64 gb, I tried all possible way to
> increase memory limit of R, and virtual memory, but problem persist.
The size of _contiguous_ memory is what's important and that will depend on
the efficiency of your memory management (with Windows being accused of
inferiority in the past) as well as how many other programs you have loaded and
the degree of memory fragmentation. I'm not sure that you can resize memory
when you already deep in a session. I thought it needed to be done early in the
startup process but I'm not currently using Windows so am only reporting
what I read in Rhelp
?'Memory-limits'
?Startup
Delete any (possibly invisible) .RData file. Restart with a clean session of
both your OS and R. You can get the size of objects currently in the R workspace
with this function that I think I copied from one of Dirk Eddelbeuttel's or
Bill Dunlap's posts:
getsizes <-
function (num=10) # change the num to different values to see more objects
{
z <- sapply(ls(envir = globalenv()), function(x) object.size(get(x)))
(tmp <- as.matrix(rev(sort(z))[1:num]))
}
getsizes()
>
> Please suggest me what can be the issue with this, why am I getting this
> error, Is there any limitation of this package.
>
Packages are not usually the culprit. It's usually program bloat by the
user. I am usually guilty of having too many images and webpages open at the
same time.
> Thank you
>
> [[alternative HTML version deleted]]
>
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David Winsemius
Alameda, CA, USA