A new relational learning system using novel rule selection strategies

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 hypothe...

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Bibliographic Details
Published in:Knowledge-based systems 2006-12, Vol.19 (8), p.765-771
Main Authors: Uludag, Mahmut, Tolun, Mehmet R.
Format: Article
Language:English
Subjects:
Pruning
Relational rule induction
Rule selection strategies
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Summary: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.
ISSN:0950-7051
1872-7409
DOI:10.1016/j.knosys.2006.05.004