Applied Intelligence

, Volume 4, Issue 3, pp 297–316

Graph-based induction as a unified learning framework

  • Kenichi Yoshida
  • Hiroshi Motoda
  • Nitin Indurkhya
Article

DOI: 10.1007/BF00872095

Cite this article as:
Yoshida, K., Motoda, H. & Indurkhya, N. Appl Intell (1994) 4: 297. doi:10.1007/BF00872095

Abstract

We describe a graph-based induction algorithm that extracts typical patterns from colored digraphs. The method is shown to be capable of solving a variety of learning problems by mapping the different learning problems into colored digraphs. The generality and scope of this method can be attributed to the expressiveness of the colored digraph representation, which allows a number of different learning problems to be solved by a single algorithm. We demonstrate the application of our method to two seemingly different learning tasks: inductive learning of classification rules, and learning macro rules for speeding up inference. We also show that the uniform treatment of these two learning tasks enables our method to solve complex learning problems such as the construction of hierarchical knowledge bases.

Key words

Machine learninginductiongraph

Copyright information

© Kluwer Academic Publishers 1994

Authors and Affiliations

  • Kenichi Yoshida
    • 1
  • Hiroshi Motoda
    • 2
  • Nitin Indurkhya
    • 3
  1. 1.Advanced Research LaboratoryHitachi, Ltd.Hatoyama, SaitamaJapan
  2. 2.Advanced Research LaboratoryHitachi, Ltd.Hatoyama, SaitamaJapan
  3. 3.Advanced Research LaboratoryHitachi, Ltd.Hatoyama, SaitamaJapan
  4. 4.Basser Department of Computer ScienceUniversity of SydneyAustralia