- 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",
