A parallel genetic programming based intelligent miner for discovery of censored production rules with fuzzy hierarchy

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@Article{Saroj:2009:ESA,
  author =       "K. K. Bharadwaj and Saroj",
  title =        "A parallel genetic programming based intelligent miner
                 for discovery of censored production rules with fuzzy
                 hierarchy",
  journal =      "Expert Systems with Applications",
  year =         "2010",
  volume =       "37",
  number =       "6",
  pages =        "4601--4610",
  month =        jun,
  ISSN =         "0957-4174",
  DOI =          "doi:10.1016/j.eswa.2009.12.048",
  URL =          "http://www.sciencedirect.com/science/article/B6V03-4Y05DGV-4/2/d56fd1bcfa2050442229496a3808abdb",
  keywords =     "genetic algorithms, genetic programming, Knowledge
                 discovery, Censored production rules with fuzzy
                 hierarchy, Variable precision logic, Island model",
  abstract =     "Automated discovery of rules with exceptions and
                 hierarchical structures is an important problem in data
                 mining. A knowledge structure based on Censored
                 Production Rules with Fuzzy Hierarchy (CPRFH) not only
                 provides an excellent mechanism for handling exceptions
                 but also captures the hierarchical relationship among
                 the classes in the dataset. Moreover, CPRFHs are able
                 to exhibit variable precision logic for approximate
                 reasoning. This paper proposes discovery of knowledge
                 in the form of CPRFHs using island model of genetic
                 programming with two advanced genetic operators,
                 namely; fission and fusion. The fission and fusion
                 operators impart intelligence to the system as these
                 operators discover new classes/concepts which are not
                 present explicitly in the data set being mined. A
                 suitable encoding with syntactic constraints is
                 designed and an appropriate fitness function is
                 suggested to measure the goodness of the hierarchies.
                 The experimental results confirm that the island model
                 with fission and fusion outperforms the sequential as
                 well as the island models without fission and fusion in
                 terms of correctness of the solution arrived and size
                 of the trees evolved.",
  notes =        "a School of Computer and Systems Sciences, Jawaharlal
                 Nehru University, New Delhi 1100067, India

                 b Department of Computer Science and Engineering, Guru
                 Jambheshwar University, Hisar 125001, India",
}

Genetic Programming entries for K K Bharadwaj Mrs. Saroj

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