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Inductive Learning with a Computational Network

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Abstract

This paper introduces a computational network which combines heterogeneous rule-extraction algorithms for intelligent data analysis. Combining induction programs may alleviate the possible negative effects of data set representation and individual program's influences, such as inductive bias. The application of the computational network to a diabetes data set shows that, when combining the various programs, an increase in rule set accuracy and comprehensibility are obtained.

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Authors and Affiliations

  1. Department of Informatics, University of Pretoria, Pretoria, 0002, South Africa

    H. L. Viktor

  2. Department of Computer Science, University of Stellenbosch, Stellenbosch, 7602, South Africa

    I. Cloete

Authors
  1. H. L. Viktor
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  2. I. Cloete
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Viktor, H.L., Cloete, I. Inductive Learning with a Computational Network. Journal of Intelligent and Robotic Systems 21, 131–141 (1998). https://doi.org/10.1023/A:1007977204827

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