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Inductive Learning with a Computational Network

Authors
  • Viktor, H. L.1
  • Cloete, I.2
  • 1 University of Pretoria, Department of Informatics, Pretoria, 0002, South Africa , Pretoria
  • 2 University of Stellenbosch, Department of Computer Science, Stellenbosch, 7602, South Africa , Stellenbosch
Type
Published Article
Journal
Journal of Intelligent & Robotic Systems
Publisher
Springer-Verlag
Publication Date
Feb 01, 1998
Volume
21
Issue
2
Pages
131–141
Identifiers
DOI: 10.1023/A:1007977204827
Source
Springer Nature
Keywords
License
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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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