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

Created by W.Langdon from gp-bibliography.bib Revision:1.4221

  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