doi: 10.7763/IJMLC.2012.V2.184
A Comparison of Efficiency and Robustness of ID3 and C4.5 Algorithms Using Dynamic Test and Training Data Sets
Payam Emami Khoonsari1
,
AhmadReza Motie2
- 1University of Tampere, Finland.
- 2institute of higher education Esfahan, Iran.
Abstract
In the machine learning world making a decision is very important. Several approaches have been invented for doing so. Among the most efficient ones is the decision tree. ID3 and C4.5 algorithms have been introduced by J.R Quinlan which produce reasonable decision trees. In this paper we evaluate robustness of these algorithms against the training and test data set changes. At first an introduction has been presented, in the second part, we take a look at the algorithms and finally unique experimentations and findings are submitted.
Keywords
- ID3 algorithm
- C4.5 algorithm
- ID3 and C4.5 comparison
- robustness of ID3 and C4.5
- an empirical comparison of ID3 and C4.5
How to Cite
Payam Emami Khoonsari and AhmadReza Motie, "A Comparison of Efficiency and Robustness of ID3 and C4.5 Algorithms Using Dynamic Test and Training Data Sets," International Journal of Machine Learning, vol. 2, no. 5, pp. 540-543, 2012. https://doi.org/10.7763/IJMLC.2012.V2.184
Copyright & License
Copyright © 2012 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).