Joint Statistical Meeting 2018

Distributed Machine Learning with H2O

Prerequisites for H2O

H2O-3 Requirements

Install H2O in R

# The following two commands remove any previously installed H2O packages for R.
if ("package:h2o" %in% search()) { detach("package:h2o", unload=TRUE) }
if ("h2o" %in% rownames(installed.packages())) { remove.packages("h2o") }

# Next, we download packages that H2O depends on.
pkgs <- c("RCurl","jsonlite")
for (pkg in pkgs) {
if (! (pkg %in% rownames(installed.packages()))) { install.packages(pkg) }
}

# Now we download, install and initialize the H2O package for R.
install.packages("h2o", type="source", repos="http://h2o-release.s3.amazonaws.com/h2o/rel-wright/3/R")

# Finally, let's load H2O and start up an H2O cluster
library(h2o)
h2o.init()

Running R script

• The R script is meant to be run in a multi-node (EC2 or cluster of CPU's) setup as the data used is quite large (airlines dataset)
• Here is a guide to setup your own EC2 instance with the latest H2O-3