Constructing Binary Decision Trees using Genetic Algorithms

Decision trees have been well studied and widely used in knowledge discovery and decision support systems. Although the problem of finding an optimal decision tree has received attention, it is a hard optimization problem. Here we propose utilizing a genetic algorithm to improve on the finding of ap-propriate decision trees. We present a method to encode/decode a decision tree to/from a chromo-some where genetic operators can be applied. Theo-retical properties of decision trees, encoded chro-mosomes, and fitness functions are presented.