A method for inductive cost optimization

  • Floor Verdenius
Part 3: Numeric And Statistical Approaches
Part of the Lecture Notes in Computer Science book series (LNCS, volume 482)


In this paper we present a Method for Inductive Cost Optimization (MICO), as an example of induction biased by using background knowledge. The method produces a decision tree that identifies those setpoints that enable the process to produce in as cost-efficient a manner as possible. We report on two examples, one idealised and one real-world. Some problems concerning MICO are reported.


Machine Learning Biased Inductive Learning Cost Optimization Decision Trees 


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Copyright information

© Springer-Verlag Berlin Heidelberg 1991

Authors and Affiliations

  • Floor Verdenius
    • 1
  1. 1.RIKSMaastrichtThe Netherlands

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