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Evolutionary Algorithms for Data Preparation

  • Chapter
Data Mining and Knowledge Discovery with Evolutionary Algorithms

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

Abstract

Clearly the quality of discovered knowledge strongly depends on the quality of the data being mined. This has motivated the development of several algorithms for data preparation tasks, as discussed in chapter 4.

“In reality, the boundary between pre-processor and classifier is arbitrary. If the pre-processor generated the predicted class label as a feature [attribute], then the classifier would be trivial. Similarly, the pre-processor could be trivial and the classifier do all the work.” [Sherrah et al. 1997, p. 305]

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Authors and Affiliations

  1. Computing Laboratory, University of Kent, CT2 7NF, Canterbury, UK

    Dr. Alex A. Freitas

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  1. Dr. Alex A. Freitas
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© 2002 Springer-Verlag Berlin Heidelberg

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Freitas, A.A. (2002). Evolutionary Algorithms for Data Preparation. In: Data Mining and Knowledge Discovery with Evolutionary Algorithms. Natural Computing Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-04923-5_9

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  • DOI: https://doi.org/10.1007/978-3-662-04923-5_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-07763-0

  • Online ISBN: 978-3-662-04923-5

  • eBook Packages: Springer Book Archive

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