Credit Classification Using Grammatical Evolution

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

@Article{Brabazon:2006:I,

• author = "Anthony Brabazon and Michael O'Neill",
• title = "Credit Classification Using Grammatical Evolution",
• journal = "Informatica",
• year = "2006",
• volume = "30",
• number = "3",
• pages = "325--335",
• keywords = "genetic algorithms, genetic programming, grammatical evolution, Povzetek: Metoda gramaticne evolucije je uporabljena za klasificiranje kreditov.",
• ISSN = "0350-5596",
• URL = "http://ai.ijs.si/informatica/PDF/30-3/07_Brabazon_Credit%20Classification%20Using.pdf",
• size = "11 pages",
• abstract = "Grammatical Evolution (GE) is a novel data driven, model induction tool, inspired by the biological genetoprotein mapping process. This study provides an introduction to GE, and demonstrates the methodology by applying it to model the corporate bond-issuer credit rating process, using information drawn from the financial statements of bond-issuing firms. Financial data and the associated Standard & Poor's issuer credit ratings of 791 US firms, drawn from the year 1999/2000 are used to train and test the model. The best developed model was found to be able to discriminate in-sample (out-of-sample) between investment grade and junk bond ratings with an average accuracy of 87.59 (84.92)percent across a five-fold cross validation.",
• notes = "http://www.informatica.si/vol30.htm#No3",

}

Genetic Programming entries for Anthony Brabazon Michael O'Neill

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