Solving the Optimal Solution of Weight Vectors on GP-Decision Tree

Created by W.Langdon from gp-bibliography.bib Revision:1.8178

@InProceedings{Wang:2009:ICICTA,

• author = "Sichun Wang",
• title = "Solving the Optimal Solution of Weight Vectors on GP-Decision Tree",
• booktitle = "Second International Conference on Intelligent Computation Technology and Automation, ICICTA '09",
• address = "Changsha, Hunan, China",
• year = "2009",
• month = "10-11 " # oct,
• volume = "4",
• pages = "329--332",
• keywords = "genetic algorithms, genetic programming, GP-decision tree, GPA, decision-making problem, genetic programming algorithm, partitioned node error rate reduction, tree nodes error rate, trend forecasting model, weight vector, decision making, decision trees, vectors",
• DOI = "doi:10.1109/ICICTA.2009.795",
• isbn13 = "978-0-7695-3804-4",
• abstract = "In this paper, a novel approach based on genetic programming algorithm (GPA) is proposed to solve the optimal solution of weight vectors on GP-decision tree. In this GP-decision tree algorithm, the GP-decision tree is constructed according to the error rate of tree nodes and the error rate reduction of partitioned nodes. By using this algorithm, not only the weight vectors of tree nodes can be solved, but also the structure of GP-decision tree can be determined. Experimental results show this algorithm is efficient and the right trend forecasting model can be selected by using this GP-decision tree algorithm.",
• notes = "Also known as \cite{5288288}",

}

Genetic Programming entries for Sichun Wang

Citations