prem_R <mtechp...@gmail.com> writes: > I'm running predictive analytics using R and to calibrate my model i > used to adjust the variables used in the model and the problem happens > here.R just runs out of memory .I tried garbage cleaning also.
I'm analyzing a 8 GB data set using R, so it can certainly handle large data sets. It tends to copy data very often, however, so you have to be very careful with it. For example, if you modify a single column in a data frame, R will copy the entire data frame, rather than just replace the modified column. If you are running a regression that saves the input data in the model result object, and you are modifying the data frame between runs, then it would be very easy to have many copies of your data in memory at once. One solution would be not to keep the model result objects around. Another would be to manually modify them to strip out the data object. This can be tricky, however, since copies of the data may live on in the environments of saved functions; I had this problem with 'mgcv::gam' fits. I hope that helps. Regards, Johann ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
