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

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Li:2008:ICNC,

• 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

Citations