Separating Rule Refinement and Rule Selection Heuristics in Inductive Rule Learning

  • Julius Stecher
  • Frederik Janssen
  • Johannes Fürnkranz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8726)

Abstract

Conventional rule learning algorithms use a single heuristic for evaluating both, rule refinements and rule selection. In this paper, we argue that these two phases should be separated. Moreover, whereas rule selection proceeds in a bottom-up specific-to-general direction, rule refinement typically operates top-down. Hence, in this paper we propose that criteria for evaluating rule refinements should reflect this by operating in an inverted coverage space. We motivate this choice by examples, and show that a suitably adapted rule learning algorithm outperforms its original counter-part on a large set of benchmark problems.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Julius Stecher
    • 1
  • Frederik Janssen
    • 1
  • Johannes Fürnkranz
    • 1
  1. 1.Knowledge EngineeringTechnische Universität DarmstadtGermany

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