After building three different neural network models with 203, 239, and 753 parameters respectively, we will now build a deeper neural network model containing a larger number of units in the hidden layers. The code used for this experiment is as follows:
# Model architecturemodel <- keras_model_sequential()model %>% layer_dense(units = 40, activation = 'relu', input_shape = c(21)) %>% layer_dropout(rate = 0.4) %>% layer_dense(units = 30, activation = 'relu') %>% layer_dropout(rate = 0.3) %>% layer_dense(units = 20, activation = 'relu') %>% layer_dropout(rate = 0.2) %>% layer_dense(units = 3, activation = 'softmax')summary(model)OUTPUT__________________________________________________________________________ ...
