Genetic programming (videotape): the movie
Genetic programming (videotape): the movie
C4.5: programs for machine learning
C4.5: programs for machine learning
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Machine Learning
Breeding Decision Trees Using Evolutionary Techniques
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Mining Predicate Association Rule by Gene Expression Programming
WAIM '02 Proceedings of the Third International Conference on Advances in Web-Age Information Management
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence (Studies in Computational Intelligence)
Evolving accurate and compact classification rules with gene expression programming
IEEE Transactions on Evolutionary Computation
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part I
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Gene Expression Programming(GEP) is a kind of heuristic method based on evolutionary computation theory. GEP has been used to evolve parsimonious decision tree with high accuracy comparable to C4.5. However, the basic GEPDT do not distinguish different attributes, whose boundaries are usually quite different. The basic GEPDT often fails to find optimal split points for some branches and thus handicapped the learning tasks. In this paper, we proposed a simple but effective Split-point Selection Method for GEP evolved decision tree to improve the performance of tree splitting and classification accuracy. Results show that our method can find better generalized ability rules and it is especially suitable for difficult problems with many attributes in different boundaries.