: Experimental results across 20 public datasets showed that HEAD-DT could generate algorithms that are significantly more accurate than established human-designed standards like C4.5 and CART.
: Rodrigo C. Barros, Márcio P. Basgalupp, André C.P.L.F. de Carvalho, and Alex A. Freitas Automatic Design of Decision-Tree Induction Alg...
: It has been successfully applied to specialized fields such as bioinformatics (e.g., predicting flexible-receptor molecular docking data and gene expression analysis) where custom-tailored models are critical. Related Resources : Experimental results across 20 public datasets showed
: Automatic Design of Decision-Tree Algorithms with Evolutionary Algorithms Márcio P. Basgalupp
: The authors proposed a hyper-heuristic evolutionary approach that treats these algorithm components as "genes" in a genome. The system automatically evolves a complete top-down induction algorithm tailored to a particular domain.