Setting up a neural network using H2O

In this section, we will cover the application of H2O in setting up a neural network. The example will use a similar dataset as used in logistic regression.

Getting ready

We first load all the required packages with the following code:

# Load the required packages
require(h2o)

Then, initialize a single-node H2O instance using the h2o.init() function on eight cores and instantiate the corresponding client module on the IP address localhost and port number 54321:

# Initialize H2O instance (single node)
localH2O = h2o.init(ip = "localhost", port = 54321, startH2O = TRUE,min_mem_size = "20G",nthreads = 8)

How to do it...

The section shows how to build neural network using H20.

1. Load the occupancy train and test datasets in R:

# Load the occupancy data 
occupancy_train <-read.csv("C:/occupation_detection/datatraining.txt",stringsAsFactors = T)
occupancy_test <- read.csv("C:/occupation_detection/datatest.txt",stringsAsFactors = T)

2. The following independent (x)...