Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Competitively evolving decision trees against fixed training cases for natural language processing
Advances in genetic programming
Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
Machine Learning
Visual classification: an interactive approach to decision tree construction
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient algorithms for constructing decision trees with constraints
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Pruning Decision Trees with Misclassification Costs
ECML '98 Proceedings of the 10th European Conference on Machine Learning
SLIQ: A Fast Scalable Classifier for Data Mining
EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
Breeding Decision Trees Using Evolutionary Techniques
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Instability of decision tree classification algorithms
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Characterizing and recognizing spoken corrections in human-computer dialogue
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Using evolutionary algorithms for the unit testing of object-oriented software
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Generation of comprehensible decision trees through evolution of training data
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Journal of Artificial Intelligence Research
An interactive co-evolutionary CAD system for garment pattern design
Computer-Aided Design
Expert Systems with Applications: An International Journal
Disturbing Neighbors Ensembles for Linear SVM
MCS '09 Proceedings of the 8th International Workshop on Multiple Classifier Systems
Classification rule discovery for the aviation incidents resulted in fatality
Knowledge-Based Systems
Enhancing the classification accuracy by scatter-search-based ensemble approach
Applied Soft Computing
Expert Systems with Applications: An International Journal
Classification by clustering decision tree-like classifier based on adjusted clusters
Expert Systems with Applications: An International Journal
Classification by clustering decision tree-like classifier based on adjusted clusters
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A GRASP method for building classification trees
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Predicting seminal quality with artificial intelligence methods
Expert Systems with Applications: An International Journal
Decision trees: a recent overview
Artificial Intelligence Review
Hybrid decision tree and naïve Bayes classifiers for multi-class classification tasks
Expert Systems with Applications: An International Journal
A hybrid decision tree classifier
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
| Hi-index | 12.06 |
Decision tree classification provides a rapid and effective method of categorising datasets. Many algorithmic methods exist for optimising decision tree structure, although these can be vulnerable to changes in the training dataset. An evolutionary method is presented which allows decision tree flexibility through the use of co-evolving competition between the decision tree and the training data set. This method is tested using two different datasets and gives results comparable with or superior to other classification methods. A final discussion argues for the utility of decision trees over algorithmic or other alternative methods such as neural networks, particularly in situations where a large number of variables are being considered.