A new relational learning system using novel rule selection strategies

Mahmut Uludag, Mehmet R. Tolun*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

This paper describes a new rule induction system, rila, which can extract frequent patterns from multiple connected relations. The system supports two different rule selection strategies, namely the select early and select late strategies. Pruning heuristics are used to control the number of hypotheses generated during the learning process. Experimental results are provided on the mutagenesis and the segmentation data sets. The present rule induction algorithm is also compared to the similar relational learning algorithms. Results show that the algorithm is comparable to similar algorithms.

Original languageEnglish (US)
Pages (from-to)765-771
Number of pages7
JournalKnowledge-Based Systems
Volume19
Issue number8
DOIs
StatePublished - Dec 1 2006

Keywords

  • Pruning
  • Relational rule induction
  • Rule selection strategies

ASJC Scopus subject areas

  • Software
  • Management Information Systems
  • Information Systems and Management
  • Artificial Intelligence

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