Performance optimization tips and best practices

In this section, we fine-tune the previous classification model to explore its functions and see whether its performance can be further improved.

Experimenting with an additional hidden layer

In this experiment, we will add an additional hidden layer to the previous model. The code and output of the summary of the model is given as follows:

# Model architecture
model <- keras_model_sequential()
model %>% 
   layer_dense(units = 8, activation = 'relu', input_shape = c(21)) %>%   
   layer_dense(units = 5, activation = 'relu') %>% 
   layer_dense(units = 3, activation = 'softmax')

summary(model)

OUTPUT
___________________________________________________________________________...