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  • 1
    Online Resource
    Online Resource
    Boston, MA : Kluwer Academic Publishers
    UID:
    gbv_524967326
    Format: Online-Ressource , v.: digital
    Edition: Online-Ausg. Springer-11645
    Edition: Springer eBook Collection. Computer Science
    ISBN: 9780306470127
    Series Statement: Genetic Programming 3
    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.
    Content: 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.
    Additional Edition: ISBN 9780792377467
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9781475784213
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9780792377467
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9781475784206
    Language: English
    Keywords: Data Mining ; Genetische Programmierung
    Author information: Leung, Kwong Sak 1955-
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    UID:
    almahu_9948621411702882
    Format: XIV, 214 p. , online resource.
    Edition: 1st ed. 2002.
    ISBN: 9780306470127
    Series Statement: Genetic Programming, 3
    Content: 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.
    Note: 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.
    In: Springer Nature eBook
    Additional Edition: Printed edition: ISBN 9781475784213
    Additional Edition: Printed edition: ISBN 9780792377467
    Additional Edition: Printed edition: ISBN 9781475784206
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
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