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


  • Maad M. Mijwil Baghdad College of Economic Sciences University, Baghdad, Iraq http://orcid.org/0000-0002-2884-2504
  • Rana A. Abttan Baghdad College of Economic Sciences University, Baghdad, Iraq




Genetic algorithm, C4.5 Decision tree, Optimizing, Pruning, Machine learning


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

Author Biography

Maad M. Mijwil, Baghdad College of Economic Sciences University, Baghdad, Iraq

Maad M. Mijwil received B.Sc. degree in Software Engineering from Software Engineering Department at Baghdad College of Economics Sciences University, Iraq in 2008/2009 and M.Sc. degree in Wireless sensor network of computer science from University of Baghdad, Iraq in 2015. Currently he is working Assistant Lecturer at Baghdad College of Economics Sciences University.


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How to Cite

Mijwil, M. M., & Abttan, R. A. (2021). Utilizing the Genetic Algorithm to Pruning the C4.5 Decision Tree Algorithm . Asian Journal of Applied Sciences, 9(1). https://doi.org/10.24203/ajas.v9i1.6503