[R] SVM Param Tuning with using SNOW package

[Max Kuhn]

On Tue, Nov 17, 2009 at 6:01 PM, raluca <ucagui at hotmail.com> wrote:
>
> Hello,
>
> Is the first time I am using SNOW package and I am trying to tune the cost
> parameter for a linear SVM, where the cost (variable cost1) takes 10 values
> between 0.5 and 30.
>
> I have a large dataset and a pc which is not very powerful, so I need to
> tune the parameters using both CPUs of the pc.
>
> Somehow I cannot manage to do it. It seems that both CPUs are fitting the
> model for the same values of cost1, I guess the first 5, but not for the
> last 5.
>
> Please, can anyone help me! :-((

This is pretty easy to do with the train() funciton in the caret
package. From ?train, here is an example for a different data set

> library(caret)
> library(snow)
> library(mlbench)
>
> data(BostonHousing)
>
> mpiCalcs <- function(X, FUN, ...)
+   {
+     theDots <- list(...)
+     parLapply(theDots$cl, X, FUN)
+   }
>
> library(snow)
> cl <- makeCluster(5, "MPI")
>
> ## 50 bootstrap models distributed across 5 workers
> mpiControl <- trainControl(workers = 5,
+                            number = 50,
+                            computeFunction = mpiCalcs,
+                            computeArgs = list(cl = cl))
> set.seed(1)
> usingMPI <-  train(medv ~ .,
+                    data = BostonHousing,
+                    "svmLinear",
+                    tuneGrid = data.frame(.C = seq(.5, 30, length = 10)),
+                    trControl = mpiControl)
>
> stopCluster(cl)
[1] 1


-- 

Max