Symbolic Regression using Genetic Programming Leveraging Neural Information Processing
Regression analysis conducted with traditional mathematical methods can be sub-optimal if the exact model of the observed data is unknown. Evolutionary computing (EC) and deep learning (DL) are viable alternatives, since regression performed with these methods tends to be less dependent on a particular model. EC are especially flexible, because they are capable of performing symbolic regression. A
