Utilizing the Genetic Algorithm to Pruning the C4.5 Decision Tree Algorithm

A decision tree (DTs) is one of the most popular machine learning algorithms that divide data repeatedly to form groups or classes. It a supervised algorithm can be used on discrete continuous for classification regression. The traditional classifier in this C4.5 tree, which point research. This has advantage building vast set and does not stop until it reaches desired goal. problem with there are unnecessary nodes branches leading overfitting. overfitting negatively affect process. In context, authors suggest utilizing genetic prune effect dataset study consists four datasets: IRIS, Car Evaluation, GLASS, WINE collected from UC Irvine (UCI) repository. experimental results have confirmed effectiveness pruning datasets optimizing confidence factor (CF) tree. proposed method reached about 92% accuracy work.