R Programming By Example

Improving speed with parallelization

If you actually executed the previous code in your computer before reading this, you may have found that it took a long time to finish (8.41 minutes in our case). As we mentioned earlier, text analysis suffers from very high dimensional structures which take a long time to process. Furthermore, using CV runs will take a long time to run. To cut down on the total execution time, use the doParallel package to allow for multi-core computers to do the training in parallel and substantially cut down on time. 

We proceed to create the train_model() function, which takes the data and the control mechanism as parameters. It then makes a cluster object with the makeCluster() function with a number of available ...