Parallel genetic programming for decision tree induction

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{folino:2001:TAI,

• author = "Gianluigi Folino and Clara Pizzuti and Giandomenico Spezzano",
• title = "Parallel genetic programming for decision tree induction",
• booktitle = "Proceedings of the 13th International Conference on Tools with Artificial Intelligence",
• year = "2001",
• pages = "129--135",
• address = "Dallas, TX USA",
• month = "7-9 " # nov,
• publisher = "IEEE",
• keywords = "genetic algorithms, genetic programming, decision trees, genetic algorithms, learning (artificial intelligence), parallel programming, J-measure, UCI machine learning repository, data sets, decision tree induction, fitness function, grid model, parallel genetic programming, scalability",
• URL = "http://www.icar.cnr.it/pizzuti/ictai01.ps",
• size = "7 pages",
• abstract = "A parallel genetic programming approach to induce decision trees in large data sets is presented. A population of trees is evolved by employing the genetic operators and every individual is evaluated by using a fitness function based on the J-measure. The method is able to deal with large data sets since it uses a parallel implementation of genetic programming through the grid model and an out of core technique for those data sets that do not fit in main memory. Preliminary experiments on data sets from the UCI machine learning repository give good classification outcomes and assess the scalability of the method",
• notes = "Inspec Accession Number: 7139478",

}

Genetic Programming entries for Gianluigi Folino Clara Pizzuti Giandomenico Spezzano

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