GEP-NFM: Nested Function Mining Based on Gene Expression Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4208

  author =       "Taiyong Li and Changjie Tang and Jiang Wu and 
                 Xuzhong Wei and Chuan Li and Shucheng Dai and Jun Zhu",
  title =        "GEP-NFM: Nested Function Mining Based on Gene
                 Expression Programming",
  booktitle =    "Fourth International Conference on Natural
                 Computation, ICNC '08",
  year =         "2008",
  month =        oct,
  volume =       "6",
  pages =        "283--287",
  abstract =     "Mining the interesting functions from the large scale
                 data sets is an important task in KDD. Traditional gene
                 expression programming (GEP) is a useful tool to
                 discover functions. However, it cannot mine very
                 complex functions. To resolve this problem, a novel
                 method of function mining is proposed in this paper.
                 The main contributions of this paper include: (1)
                 analysing the limitations of function mining based on
                 traditional GEP, (2) proposing a nested function mining
                 method based on GEP (GEP-NFM), and (3) experimental
                 results suggest that the performance of GEP-NFM is
                 better than that of the existing GEP-ADF. Averagely,
                 compared with traditional GEP-ADF, the successful rate
                 of GEP-NFM increases 20percent and the number of
                 evolving generations decrease 25percent.",
  keywords =     "genetic algorithms, genetic programming, gene
                 expression programming, data mining, function
                 discovery, knowledge discovery, machine learning,
                 nested function mining, data mining, learning
                 (artificial intelligence)",
  DOI =          "doi:10.1109/ICNC.2008.640",
  notes =        "Also known as \cite{4667846}",

Genetic Programming entries for Taiyong Li Changjie Tang Jiang Wu Xuzhong Wei Chuan Li Shucheng Dai Jun Zhu