
Data Mining Using Grammar Based Genetic Programming and Applications
Springer (Publisher)
Published on 21. March 2013
Book
Paperback/Softback
XIV, 214 pages
978-1-4757-8421-3 (ISBN)
Description
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.
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.
More details
Series
Edition
Softcover reprint of the original 1st ed. 2002
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
Research
Illustrations
XIV, 214 p.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 13 mm
Weight
359 gr
ISBN-13
978-1-4757-8421-3 (9781475784213)
DOI
10.1007/b116131
Schweitzer Classification
Other editions
Additional editions

Man Leung Wong | Kwong Sak Leung
Data Mining Using Grammar Based Genetic Programming and Applications
E-Book
12/2005
Kluwer Academic Publishers
€149.79
Available for download

Man Leung Wong | Kwong Sak Leung
Data Mining Using Grammar Based Genetic Programming and Applications
Book
02/2000
Kluwer Academic Publishers
€160.49
Shipment within 15-20 days
Content
An Overview of Data Mining.- An Overview on Evolutionary Algorithms.- Inductive Logic Programming.- The Logic Grammars Based Genetic Programming System (LOGENPRO).- Data Mining Applications Using LOGENPRO.- Applying LOGENPRO for Rule Learning.- Medical Data Mining.- Conclusion and Future Work.