More specifically, read the vignettes. Actually, always start with the package
vignettes if any are available.
On May 21, 2020 1:51:48 PM PDT, Ista Zahn wrote:
>Hi Ravi,
>
>Please read the ?future documentation, the answers to all your
>questions are explained there.
>
>Best,
>Ista
>
>On Thu, Ma
Hi Ravi,
Please read the ?future documentation, the answers to all your
questions are explained there.
Best,
Ista
On Thu, May 21, 2020 at 3:20 PM Ravi Jeyaraman wrote:
>
> Dear Friends,
>
>
>
> I'm trying to run a bunch of tasks in parallel using 'Future' package and
> for some reason, it's not
Dear Friends,
I'm trying to run a bunch of tasks in parallel using 'Future' package and
for some reason, it's not able to find the data frames that I want it to
find. I've created the below sample program to show what I'm doing. Should
I be exporting the Global data to each child process? I
I'm not sure what you mean by full code or the iteration. This uses
foreach to parallelize the loops over different tuning parameters and
resampled data sets.
The only way I could set to split up the parallelism is if you are
fitting different models to the same data. In that case, you could
launc
the part of the question dawned on me now is, should I try to do the parallel
processing of the full code or only the iteration part? if it is full code
then I am at the complete mercy of the R help community or I giveup on this
and let the computation run the serial way, which is continuing from p
I have had issues with some parallel backends not finding functions
within a namespace for packages listed in the ".packages" argument or
explicitly loaded in the body of the foreach loop. This has occurred
with MPI but not with multicore. I can get around this to some extent
by calling the functio
If i understand correctly you mean to write the line as below:
foreach(icount(itr),.combine=combine,.options.smp=smpopts,.packages='MASS')%dopar%
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yes the library(MASS) was loaded.
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ht
Did you load the class package before calling lda()?
Dennis
On Thu, Oct 27, 2011 at 10:14 AM, 1Rnwb wrote:
> my modification gives me error
>> rows<- c(1:nrow(mat))
>> scores <- c()
>> labels <-c()
>> itr<-1000
>> chnksz<-ceiling(itr/getDoParWorkers())
>> smpopt=list(chunkSize=chnksz)
>> f
my modification gives me error
> rows<- c(1:nrow(mat))
> scores <- c()
> labels <-c()
> itr<-1000
> chnksz<-ceiling(itr/getDoParWorkers())
> smpopt=list(chunkSize=chnksz)
> foreach(icount(itr),.combine=cbind,.options.smp=smpopts)%dopar%
+ {
+ train <- sample(rows, length(rows)-1)
+ label =
sorry for noise
the simulated data should be like this
d=data.frame(replicate(9, rnorm(40)+10),rep(c('y','n'),20))
colnames(d)<-c("LEPTIN","SAA","PTH","sEGFR","IGFBP6","MMP2","OPG","IGFBP3","PDGFAABB","group")
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Hello R gurus,
I have the code below for which i need help and pointers to make it run in
parallel on a dual core win7 computer with R 2.13.x, using foreach,
iterators,doMC.
library(scatterplot3d) # Loads 3D library.
library(fields)
library(MASS)
library(ROCR)
library(verification)
library(caret)
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