A study on efficient generation of decision trees using genetic programming
Toru Tanigawa, Qiangfu Zhao · 2000
For pattern recognition, the decision trees (DTs) are more efficient than neural networks (NNs) for two reasons. First, the computations in making decisions are simpler. Second, important features can be selected automatically during the design process. On the other hand, NNs are adaptable, and thus have the ability to learn in changing environment.