I am currently using the codes of the following GitHub repo to benchmark a different imbalanced binary classification dataset:
Should I modify any value in this portion, given that the dataset has 14 independent features and 1 target feature? (Point to note that the following codes were based upon the dataset having a PCA of 29 features, that’s why probably the authors considered 10 PCAs. However, my dataset doesn’t contain any PCA features.)
# Input neurons input_neurons = 10 # Widths of hidden layers nn_architecture = [10, 10] # Output neurons of classical part output_neurons = 14
If I take input_neurons = 14, what should be the values of nn_architecture and output_neurons?