Logo - springer
Slogan - springer

Computer Science - Artificial Intelligence | Data Mining Using Grammar Based Genetic Programming and Applications

Data Mining Using Grammar Based Genetic Programming and Applications

Series: Genetic Programming, Vol. 3

Man Leung Wong, Kwong Sak Leung

2002, XIV, 214 p.

Available Formats:
eBook
Information

Springer eBooks may be purchased by end-customers only and are sold without copy protection (DRM free). Instead, all eBooks include personalized watermarks. This means you can read the Springer eBooks across numerous devices such as Laptops, eReaders, and tablets.

You can pay for Springer eBooks with Visa, Mastercard, American Express or Paypal.

After the purchase you can directly download the eBook file or read it online in our Springer eBook Reader. Furthermore your eBook will be stored in your MySpringer account. So you can always re-download your eBooks.

 
$199.00

(net) price for USA

ISBN 978-0-306-47012-7

digitally watermarked, no DRM

Included Format: PDF

download immediately after purchase


learn more about Springer eBooks

add to marked items

Hardcover
Information

Hardcover version

You can pay for Springer Books with Visa, Mastercard, American Express or Paypal.

Standard shipping is free of charge for individual customers.

 
$259.00

(net) price for USA

ISBN 978-0-7923-7746-7

free shipping for individuals worldwide

usually dispatched within 3 to 5 business days


add to marked items

Softcover
Information

Softcover (also known as softback) version.

You can pay for Springer Books with Visa, Mastercard, American Express or Paypal.

Standard shipping is free of charge for individual customers.

 
$259.00

(net) price for USA

ISBN 978-1-4757-8421-3

free shipping for individuals worldwide

usually dispatched within 3 to 5 business days


add to marked items

  • About this book

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.

Content Level » Research

Keywords » data mining - database - evolution - evolutionary algorithm - genetic programming - grammar - knowledge - learning - logic programming

Related subjects » Artificial Intelligence - Security and Cryptology

Table of 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.

Popular Content within this publication 

 

Articles

Read this Book on Springerlink

Services for this book

New Book Alert

Get alerted on new Springer publications in the subject area of Artificial Intelligence (incl. Robotics).