H2O background

H2O is an open source predictive analytics platform with prebuilt algorithms, such as k-nearest neighbor, gradient boosted machines, and deep learning. You can upload data to the platform via Hadoop, AWS, Spark, SQL, noSQL, or your hard drive. The great thing about it is that you can utilize the machine learning algorithms in R and, at a much greater scale, on your local machine. If you are interested in learning more, you can visit the site: http://h2o.ai/product/.

The process of installing H2O on R is a little different. I put the code here that gave me the latest update (as of February 25, 2017). You can use it to reinstall the latest version or pull it off of the website: http://h2o-release.s3.amazonaws.com/h2o/rel-lambert/5/docs-website/Ruser/Rinstall.html/. The following is the code to install the latest version:

   # 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.
if (! ("methods" %in% rownames(installed.packages()))) {
install.packages("methods") }

if (! ("statmod" %in% rownames(installed.packages()))) {
install.packages("statmod") }

if (! ("stats" %in% rownames(installed.packages()))) {
install.packages("stats") }

if (! ("graphics" %in% rownames(installed.packages()))) {
install.packages("graphics") }

if (! ("RCurl" %in% rownames(installed.packages()))) {
install.packages("RCurl") }

if (! ("jsonlite" %in% rownames(installed.packages()))) {
install.packages("jsonlite") }

if (! ("tools" %in% rownames(installed.packages()))) {
install.packages("tools") }

if (! ("utils" %in% rownames(installed.packages()))) {
install.packages("utils") }


# Now we download, install and initialize the H2O package for R.
install.packages("h2o", type="source", repos=(c("http://h2o-
release.s3.amazonaws.com/h2o/rel-tverberg/5/R")))
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