- Make as few calls out from Zorro to R as necessary. Consolidate fixed sequences of commands into functions written on the R side.
- For training, library "parallel" offers some parallelization and is supported by some modeling types
- If desperate and/or ambitious, use Zorro Train mode only to produce the csv files, then produce Rdata for each cycle completely outside of Zorro. Only Test mode uses RBridge and simply expects Rdata files to already exist.
- In that case, you can additionally train on Linux and take advantage of library "multicore" and "doMC", which library "caret" loves.