2003 | OriginalPaper | Chapter
Comparative Evaluation of Approaches to Propositionalization
Authors : Mark-A. Krogel, Simon Rawles, Filip Železný, Peter A. Flach, Nada Lavrač, Stefan Wrobel
Published in: Inductive Logic Programming
Publisher: Springer Berlin Heidelberg
Included in: Professional Book Archive
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Propositionalization has already been shown to be a promising approach for robustly and effectively handling relational data sets for knowledge discovery. In this paper, we compare up-to-date methods for propositionalization from two main groups: logic-oriented and database-oriented techniques. Experiments using several learning tasks – both ILP benchmarks and tasks from recent international data mining competitions – show that both groups have their specific advantages. While logic-oriented methods can handle complex background knowledge and provide expressive first-order models, database-oriented methods can be more efficient especially on larger data sets. Obtained accuracies vary such that a combination of the features produced by both groups seems a further valuable venture.