Data Mining Using Grammar Based Genetic Programming and Applications

✍ Scribed by Wong, Cheung.

Publisher: Kluwer Academic
Year: 2002
Tongue: English
Leaves: 228
Series: Genetic programming series GPEM3
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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.

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