In this section, we will cover an application of TensorFlow in setting up a two-layer neural network model.
To start modeling, load the tensorflow
package in the environment. R loads the default tf environment variable and also the NumPy library from Python in the np
variable:
library("tensorflow") # Load Tensorflow np <- import("numpy") # Load numpy library
- The data is imported using the standard function from R, as shown in the following code. The data is imported using the
read.csv
file and transformed into the matrix format followed by selecting the features used for the modeling as defined inxFeatures
andyFeatures
:
# Loading input and test data xFeatures = c("Temperature", "Humidity", "Light", "CO2", "HumidityRatio") yFeatures = "Occupancy" occupancy_train <-as.matrix(read.csv("datatraining.txt",stringsAsFactors = T)) occupancy_test <- as.matrix(read.csv("datatest.txt",stringsAsFactors = T)) # subset features...