Data Mining Using Grammar Based Genetic Programming and Applications

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Book{ManLeungWong:book,
  author =       "Man Leung Wong and Kwong Sak Leung",
  title =        "Data Mining Using Grammar Based Genetic Programming
                 and Applications",
  publisher =    "Kluwer Academic Publishers",
  year =         "2000",
  volume =       "3",
  series =       "Genetic Programming",
  month =        jan,
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "0-7923-7746-X",
  URL =          "http://www.springer.com/computer/ai/book/978-0-7923-7746-7",
  notes =        "Data mining involves the non-trivial extraction of
                 implicit, previously unknown, and potentially useful
                 information from databases. Genetic Programming (GP)
                 and Inductive Logic Programming (ILP) are two of the
                 approaches for data mining. This book first sets the
                 necessary backgrounds for the reader, including an
                 overview of data mining, evolutionary algorithms and
                 inductive logic programming. It then describes a
                 framework, called GGP (Generic Genetic Programming),
                 that integrates GP and ILP based on a formalism of
                 logic grammars. The formalism is powerful enough to
                 represent context- sensitive information and
                 domain-dependent knowledge. This knowledge can be used
                 to accelerate the learning speed and/or improve the
                 quality of the knowledge induced. A grammar-based
                 genetic programming system called LOGENPRO (The LOGic
                 grammar based GENetic PROgramming system) is detailed
                 and tested on many problems in data mining. It is found
                 that LOGENPRO outperforms some ILP systems. We have
                 also illustrated how to apply LOGENPRO to emulate
                 Automatically Defined Functions (ADFs) to discover
                 problem representation primitives automatically. By
                 employing various knowledge about the problem being
                 solved, LOGENPRO can find a solution much faster than
                 ADFs and the computation required by LOGENPRO is much
                 smaller than that of ADFs. Moreover, LOGENPRO can
                 emulate the effects of Strongly Type Genetic
                 Programming and ADFs simultaneously and effortlessly.
                 Data Mining Using Grammar Based Genetic Programming and
                 Applications is appropriate for researchers,
                 practitioners and clinicians interested in genetic
                 programming, data mining, and the extraction of data
                 from databases. Contents

                 List of Figures. List of Tables. Preface. 1.
                 Introduction. 2. An Overview of Data Mining. 3. An
                 Overview on Evolutionary Algorithms. 4. Inductive Logic
                 Programming. 5. The Logic Grammars Based Genetic
                 Programming System (LOGENPRO). 6. Data Mining
                 Applications Using LOGENPRO. 7. Applying LOGENPRO for
                 Rule Learning. 8. Medical Data Mining. 9. Conclusion
                 and Future Work. Appendix A: The Rule Sets
                 Discovered.

                 Appendix B: The Grammar Used for the Fracture and
                 Scoliosis Databases. References. Index.",
  size =         "232 pages",
}

Genetic Programming entries for Man Leung Wong Kwong-Sak Leung

Citations