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Cost-sensitive specialization

  • Machine Learning I
  • Conference paper
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PRICAI'96: Topics in Artificial Intelligence (PRICAI 1996)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1114))

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Abstract

Cost-sensitive specialization is a generic technique for mis-classification cost sensitive induction. This technique involves specializing aspects of a classifier associated with high misclassification costs and generalizing those associated with low misclassification costs. It is widely applicable and simple to implement. It could be used to augment the effect of standard cost-sensitive induction techniques. It should directly extend to test application cost sensitive induction tasks. Experimental evaluation demonstrates consistent positive effects over a range of misclassification cost sensitive learning tasks.

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Author information

Authors and Affiliations

  1. School of Computing and Mathematics, Deakin University, 3217, Geelong, Vic, Australia

    Geoffrey I. Webb

Authors
  1. Geoffrey I. Webb
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Editor information

Norman Foo Randy Goebel

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© 1996 Springer-Verlag Berlin Heidelberg

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Webb, G.I. (1996). Cost-sensitive specialization. In: Foo, N., Goebel, R. (eds) PRICAI'96: Topics in Artificial Intelligence. PRICAI 1996. Lecture Notes in Computer Science, vol 1114. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61532-6_3

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  • DOI: https://doi.org/10.1007/3-540-61532-6_3

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61532-3

  • Online ISBN: 978-3-540-68729-0

  • eBook Packages: Springer Book Archive

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