Analysis of the Effectiveness of G3PARM Algorithm

Created by W.Langdon from gp-bibliography.bib Revision:1.8081

@InProceedings{Luna:2010:HAIS,

• author = "J. M. Luna and J. R. Romero and S. Ventura",
• title = "Analysis of the Effectiveness of {G3PARM} Algorithm",
• booktitle = "Proceedings of the 5th International Conference on Hybrid Artificial Intelligence Systems (HAIS 2010) Part II",
• year = "2010",
• editor = "Emilio Corchado and Manuel Grana Romay and Alexandre Manhaes Savio",
• volume = "6077",
• series = "Lecture Notes in Computer Science",
• pages = "27--34",
• address = "San Sebastian, Spain",
• month = jun # " 23-25",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming, Association Rules, G3P",
• isbn13 = "978-3-642-13802-7",
• DOI = "doi:10.1007/978-3-642-13803-4_4",
• size = "8 pages",
• abstract = "This paper presents an evolutionary algorithm using G3P (Grammar Guided Genetic Programming) for mining association rules in different real-world databases. This algorithm, called G3PARM, uses an auxiliary population made up of its best individuals that will then act as parents for the next generation. The individuals are defined through a context-free grammar and it allows us to obtain datatype-generic and valid individuals. We compare our approach to apriori and FP-Growth algorithms and demonstrate that our proposal obtains rules with better support, confidence and coverage of the dataset instances. Finally, a preliminary study is also introduced to compare the scalability of our algorithm. Our experimental studies illustrate that this approach is highly promising for discovering association rules in databases.",

}

Genetic Programming entries for Jose Maria Luna Jose Raul Romero Salguero Sebastian Ventura

Citations