a7.R

#Using Keras
model = keras_model_sequential()
model %>%
  layer_dense(units = 3, input_shape = c(5), activation = 'relu') %>%
  layer_dense(units = 2, activation = 'relu') %>%
  layer_dense(units = 1, activation = 'sigmoid')

model %>% compile(
  loss = 'binary_crossentropy',
  optimizer = optimizer_adam(),
  metrics = c('accuracy')
)

history = model %>% fit(
  x_train,y_train,
  epochs = 130, batch_size = 2000,
  validation_split = 0.2
)

#Output
#loss		[1] 0.08656487		
#acc		[1] 0.9869172