I'm trying to run some analysis with some big datasets (eg 400k rows vs. 400 columns) with R (e.g. using neural networks and recommendation systems). But, it's taking too long to process the data (with huge matrices, e.g. 400k rows vs. 400k columns). What are some free/cheap ways to improve R performance?
I'm accepting packages or web services suggestions (other options are welcome).
cmpfun()or parallelize code to use several cores. Finally, you can rent Amazon web server to run your experiments, which will cost much less than buying hardware yourself. Anyway, try to determine your bottleneck first. $\endgroup$