The Appropriateness of Predicate Invention as Bias Shift Operation in ILP

  • Authors:
  • Irene Stahl

  • Affiliations:
  • Fakultät Informalik, Universität Stuttgart, Breitwiesenstr. 20-22, 70565 Stuttgart, Germany. stahl@informatik.uni-stuttgart.de

  • Venue:
  • Machine Learning - Special issue on bias evaluation and selection
  • Year:
  • 1995

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Abstract

The task of predicate invention in Inductive Logic Programming is to extend the hypothesis language with new predicates if the vocabulary given initially is insufficient for the learning task. However, whether predicate invention really helps to make learning succeed in the extended language depends on the language bias currently employed.In this paper, we investigate for which commonly employed language biases predicate invention is an appropriate shift operation. We prove that for some restricted languages predicate invention does not help when the learning task fails and we characterize the languages for which predicate invention is useful. We investigate the decidability of the bias shift problem for these languages and discuss the capabilities of predicate invention as a bias shift operation.