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Automating the Design of Rule Induction Algorithms

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Automating the Design of Data Mining Algorithms

Part of the book series: Natural Computing Series ((NCS))

Abstract

Chapter 5 (entitled “Automating the Design of Rule Induction Algorithms”) describes in detail the main contribution of this book, which is a grammar-based genetic programming system for automatically evolving the design of rule induction algorithms. First, this chapter describes the grammar used by the system, which incorporates background knowledge about how human experts manually design a rule induction algorithm. Next, this chapter describes all other components of the system related to the genetic programming algorithm itself - i.e., individual representation, population initialization, individual evaluation (based on a single-objective or multiobjective fitness function) and finally crossover and mutation operations.

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Authors and Affiliations

  1. Dept. de Ciência da Computação, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil

    Dr. Gisele L. Pappa

  2. School of Computing, University of Kent, Canterbury, UK

    Dr. Alex A. Freitas

Authors
  1. Dr. Gisele L. Pappa
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  2. Dr. Alex A. Freitas
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Correspondence to Gisele L. Pappa .

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Pappa, G.L., Freitas, A.A. (2010). Automating the Design of Rule Induction Algorithms. In: Automating the Design of Data Mining Algorithms. Natural Computing Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02541-9_5

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  • DOI: https://doi.org/10.1007/978-3-642-02541-9_5

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02540-2

  • Online ISBN: 978-3-642-02541-9

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