This repository provides a framework for benchmarking the h2oEnsemble package. The h2oEnsemble package provides an R API to train ensembles of H2O machine learning algorithms. You can read more about the "H2O Ensemble" project on its GitHub page.

• An example binary classification benchmark is provided in the twoClass/higgs folder.
• To use the software on an Amazon EC2 cluster, follow the instructions in the ec2/README.md file to set up the cluster.
• After you set up the cluster, you should cd to a specific benchmark directory and execute the benchmark. For example, the higgs benchmark can be executed as follows:

cd src/twoClass/higgs
nohup ./run-bench.sh &

• If you choose to use a single node instead of a multi-node cluster, you can skip the EC2 steps. If a multi-node cluster is not available, the code will create a single node multicore cluster using all the cores available on your machine.
• If the benchmark is not executed using the H2O Ubuntu AMI, you may have to change the path of the BENCH_ROOT variable in the scripts to point to the location of this repository on your machine.