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Data Mining Using Grammar Based Genetic Programming and Applications by Man Leung Wong, Kwong Sak Leung , Springer

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General Information  
Author(s)Man Leung Wong, Kwong Sak Leung
PublisherSpringer
ISBN9781475784213
Pages214
BindingPaperback
LanguageEnglish
Publish YearMarch 2013

Description

Springer Data Mining Using Grammar Based Genetic Programming and Applications by Man Leung Wong, Kwong Sak Leung

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. _x000D_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. _x000D_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._x000D_ Table of contents : - _x000D_ 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._x000D_



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