Decision Tree Induction Using Evolutionary Algorithms: A Survay

Abstract

An evolutionary methods for an induction-based decision trees made a wide step development in machine learning field. In this context, the majority of researches recently concentrates on techniques that use developing decision trees as an alternative to the traditional heuristic top-down divide-and-conquer strategy. Evolutionary algorithms play an important role in improving decision tree classifier parts. The main contributions of our article are two folds, first it provides a survey of evolutionary algorithms and decision trees. Second, it reviews a taxonomy that encompasses techniques mentioned above as a backbone in creating enhanced decision trees, and those that evolve the construction components of decision trees. The article covers researches in the period 2011-2023. Finally, a detailed scenarios and results had been analyzed, and compared to spot the lights on those strength points and defects with respect to processing time, accuracy, and required space.