Impact Factor:6.549
 Scopus Suggested Journal: Tracking ID for this title suggestion is: 55EC484EE39417F0

International Journal
of Computer Engineering in Research Trends (IJCERT)

Scholarly, Peer-Reviewed, Platinum Open Access and Multidisciplinary

Welcome to IJCERT

International Journal of Computer Engineering in Research Trends. Scholarly, Peer-Reviewed, Platinum Open Access and Multidisciplinary

ISSN(Online):2349-7084                 Submit Paper    Check Paper Status    Conference Proposal

Back to Current Issues

The Use of Heuristics in Decision Tree Learning Optimization

Elma Kolçe (Çela), Neki Frasheri , , ,


— Decision tree algorithms are among the most popular techniques for dealing with classification problems in different areas. Decision tree learning offers tools to discover relationships, patterns and knowledge from data in databases. As the volume of data in databases is growing up very quickly, the process of building decision trees on such databases becomes a quite complex task. The problem with decision trees is to find the right splitting criterion in order to be more efficient and to get the highest accuracy. Different approaches for this problem have been proposed by researchers, using heuristic search algorithms. Heuristic search algorithms can help to find optimal solutions where the search space is simply too large to be explored comprehensively. This paper is an attempt to summarize the proposed approaches for decision tree learning with emphasis on optimization of constructed trees by using heuristic search algorithms. We will focus our study on four of the most popular heuristic search algorithms, such as hill climbing, simulated annealing, tabu search and genetic algorithms.

Elma Kolçe (Çela),Neki Frasheri."The Use of Heuristics in Decision Tree Learning Optimization". International Journal of Computer Engineering In Research Trends (IJCERT) ,ISSN:2349-7084 ,Vol.1, Issue 03,pp.127-130, SEPTEMBER - 2014, URL :,

Keywords : decision trees, genetic algorithms, heuristics, hill-climbing, simulated annealing, tabu search

[1] V. Mohan, ―Decision Trees:A comparison of various algorithms for building
Decision Trees‖, 2013
[2] W.S.Alsharafat ―Steady State Genetic Algorithm in University Admission
Decision‖, Contemporary Engineering Sciences, Vol. 6, 2013, no. 5, pp.245 -
[3] D.Sh. Liu et al. ―A Modified Decision Tree Algorithm Based on Genetic Algorithm for Mobile User Classification Problem‖, The Scientific World Journal
Volume 2014, Article ID 468324 2014
[4] R.C.Barros et al. ―Automatic Design of Decision-Tree Algorithms with Evolutionary Algorithms‖ Massachusetts Institute of Technology 2013
[5] M.Khanbabaei, M.Alborzi ―The Use Of Genetic Algorithm, Clustering And
Feature Selection Techniques In Construction Of Decision Tree Models For
Credit Scoring‖. International Journal of Managing Information Technology
(IJMIT) Vol.5, No.4, 2013 DOI : 10.5121/ijmit.2013.5402
[6] T. de la Rosa et al. ―Learning Relational Decision Trees for Guiding
Heuristic Planning Association for the Advancement of Artificial
Intelligence‖ ( 2008
[7] Y.Cai et al. ―A Tree-Based Tabu Search Algorithm for the Manpower
Allocation Problem with TimeWindows and Job-Teaming Constraints‖,
Proceedings of the Twenty-Third International Joint Conference on
Artificial Intelligence 2013 pp.496-502
[8] Y.Madadi et al. ―An Accurate Classification Algorithm with Genetic
Algorithm Approach‖, International Journal of Computer & Information
Technologies (IJOCIT) 2013 ISSN: 2345-3877 Vol 1, Issue 3 pp.198-210
[9] ―A Bank Customer Credit Evaluation Based on the Decision Tree and the
Simulated Annealing Algorithm‖ 2007
[10] C.J.Hinde et al. ―Evolving the input space for decision tree building‖ 2005
[11] R.Ahmed et al ―Induction of Better Decision Trees Using Population
Oriented Multi-Objective Simulated Annealing‖, 7th International
Conference on Computer and Information Technology 2004
[12] Fu Et Al. ―A Genetic Algorithm-Based Approach For Building Accurate
Decision Trees Informs‖ Journal On Computing 2003 Vol. 15, No.1,
[13] J.Dvoˇr´Ak , P.Savick´Y ―Softening Splits In Decision Trees Using
Simulated Annealing‖ 2006
[14] A.M.Mahmood et al. ―A New Decision Tree Induction Using Composite
Splitting Criterion‖ Journal Of Applied Computer Science & Mathematics,
No. 9 (4) /2010
[15] S.H. Cha, Ch.Tappert ―A Genetic Algorithm For Constructing Compact
Binary Decision Trees‖ Journal Of Pattern Recognition Research 1 (2009)
[16] K.B. Bennett, J.A.Blue ―An Extreme Point Tabu Search Method For Data
Mining‖ 2007
[17] N.Mishra et al., ―Hybrid Tabu-Simulated annealing based approach to solve
multi-constraint product mix decision problem‖ Expert Systems with
Applications 2005 Volume 29, Issue 2, pp.446-454
[18] Yi Jiang ―Credit Scoring Model Based on the Decision Tree and the
Simulated Annealing Algorithm‖ Computer Science and Information
Engineering, 2009 WRI World Congress Vol.4, pp. 18 – 22, ISBN: 978-0-
[19] Glover, F. & Laguna, M. 1997. Tabu search. Boston: Kluwer Academic
[20] J. Han, Data Mining: Concepts and Techniques, Morgan Kaufmann
Publishers Inc., San Francisco, CA, USA, 2001.
[21] M. E. Aydin, T. C. Fogarty. ‖A Distributed Evolutionary Simulated
Annealing Algorithm for Combinatorial Optimization Problems‖, in Journal
of Heuristics 2004, vol. 24, no. 10, pp. 269–292.
[22] R. Battiti. ‖Reactive search: towards self-tuning heuristics‖, in Modern
heuristic search methods. Wiley&Sons, 1996, pp. 61-83.
[23] Goldberg, D.E., 1989. Genetic Algorithms in Search, Optimization and
Machine Learning. Addison-Wesley Publishing Company, Inc., Reading,


Download :

Refbacks : Currently there are no Refbacks

Support Us

We have kept IJCERT is a free peer-reviewed scientific journal to endorse conservation. We have not put up a paywall to readers, and we do not charge for publishing. But running a monthly journal costs is a lot. While we do have some associates, we still need support to keep the journal flourishing. If our readers help fund it, our future will be more secure.

Quick Links


Science Central

Score: 13.30

Submit your paper to