C4.5: programs for machine learning
C4.5: programs for machine learning
From data mining to knowledge discovery: an overview
Advances in knowledge discovery and data mining
The ant colony optimization meta-heuristic
New ideas in optimization
Ant algorithms for discrete optimization
Artificial Life
Future Generation Computer Systems
Understanding the Crucial Role of AttributeInteraction in Data Mining
Artificial Intelligence Review
Knowledge Discovery in Databases
Knowledge Discovery in Databases
Data Mining and Knowledge Discovery
Machine Learning
Ant Colony Optimization
Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Statistical Comparisons of Classifiers over Multiple Data Sets
The Journal of Machine Learning Research
Decision trees for hierarchical multi-label classification
Machine Learning
cAnt-Miner: An Ant Colony Classification Algorithm to Cope with Continuous Attributes
ANTS '08 Proceedings of the 6th international conference on Ant Colony Optimization and Swarm Intelligence
Improved use of continuous attributes in C4.5
Journal of Artificial Intelligence Research
RBDT-1: A New Rule-Based Decision Tree Generation Technique
RuleML '09 Proceedings of the 2009 International Symposium on Rule Interchange and Applications
On the Importance of Comprehensible Classification Models for Protein Function Prediction
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Editorial survey: swarm intelligence for data mining
Machine Learning
ICCCI'10 Proceedings of the Second international conference on Computational collective intelligence: technologies and applications - Volume PartI
An adaptive discretization in the ACDT algorithm for continuous attributes
ICCCI'11 Proceedings of the Third international conference on Computational collective intelligence: technologies and applications - Volume Part II
Decision trees for hierarchical multilabel classification: a case study in functional genomics
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
Top-down induction of decision trees classifiers - a survey
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Data mining with an ant colony optimization algorithm
IEEE Transactions on Evolutionary Computation
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Decision trees have been widely used in data mining and machine learning as a comprehensible knowledge representation. While ant colony optimization (ACO) algorithms have been successfully applied to extract classification rules, decision tree induction with ACO algorithms remains an almost unexplored research area. In this paper we propose a novel ACO algorithm to induce decision trees, combining commonly used strategies from both traditional decision tree induction algorithms and ACO. The proposed algorithm is compared against three decision tree induction algorithms, namely C4.5, CART and cACDT, in 22 publicly available data sets. The results show that the predictive accuracy of the proposed algorithm is statistically significantly higher than the accuracy of both C4.5 and CART, which are well-known conventional algorithms for decision tree induction, and the accuracy of the ACO-based cACDT decision tree algorithm.