Genetic programming and rough sets: A hybrid approach to bankruptcy classification

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@Article{McKee:2002:EJOR,
  author =       "Thomas E. McKee and Terje Lensberg",
  title =        "Genetic programming and rough sets: A hybrid approach
                 to bankruptcy classification",
  journal =      "European Journal of Operational Research",
  year =         "2002",
  volume =       "138",
  pages =        "436--451",
  number =       "2",
  keywords =     "genetic algorithms, genetic programming, Rough sets,
                 Bankruptcy, Hybrid models, Continuity theory",
  owner =        "wlangdon",
  URL =          "http://www.sciencedirect.com/science/article/B6VCT-44X69C1-H/2/4757607399cd181dadad865b5a62c58f",
  URL =          "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.619.594",
  broken =       "http://sedok.narod.ru/s_files/poland/25.pdf",
  language =     "en",
  oai =          "oai:CiteSeerX.psu:10.1.1.619.594",
  DOI =          "doi:10.1016/S0377-2217(01)00130-8",
  abstract =     "The high social costs associated with bankruptcy have
                 spurred searches for better theoretical understanding
                 and prediction capability. we investigate a hybrid
                 approach to bankruptcy prediction, using a genetic
                 programming algorithm to construct a bankruptcy
                 prediction model with variables from a rough sets model
                 derived in prior research. Both studies used data from
                 291 US public companies for the period 1991 to 1997.
                 The second stage genetic programming model developed
                 consists of a decision model that is 80% accurate on a
                 validation sample as compared to the original rough
                 sets model which was 67% accurate. Additionally, the
                 genetic programming model reveals relationships between
                 variables that are not apparent in either the rough
                 sets model or prior research. These findings indicate
                 that genetic programming coupled with rough sets theory
                 can be an efficient and effective hybrid modelling
                 approach both for developing a robust bankruptcy
                 prediction model and for offering additional
                 theoretical insights.",
}

Genetic Programming entries for Thomas E McKee Terje Lensberg

Citations