Hi, I have written a piece of code, which is a variant of the random forest (rf) package algorithm, entirely in R. I know that some of the code in the rf package is written in c or c++. The problem is that the execution of my code in R takes a lot of time. To give you an example, the building and testing of data set with 20,000 instances using the random forest function from the rf package takes a few minutes while 'my' random forest's execution time is around 5 hours. So, I wonder if there are some ways to speed up the execution time.
I've read in a similar post that using matrix instead of data.frame would actually speed up the R code. The format of my read-in data set is a "list", would the data set in matrix format (using as.matrix) be better? Thanks in advance, Martin ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
