Data Mining Using Grammar Based Genetic Programming and (GENETIC PROGRAMMING Volume 3)
|Published by: algy (Karma: 416.75) on 17 December 2010 | Views: 782|
Describes a framework, called GGP (Generic Genetic Programming), that integrates GP and ILP based on a formalism of logic grammers. Accelerates the learning speed and/or improves the quality of the knowledge induced. DLC: Data mining.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.
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|Tags: Genetic, Programming, Mining, mining, induced, GENETIC, PROGRAMMING