Learning Aggregate Functions with Neural Networks Using a Cascade-Correlation Approach

Authors:
Werner Uwents;Hendrik Blockeel
Affiliations:
Department of Computer Science, Katholieke Universiteit Leuven,;Department of Computer Science, Katholieke Universiteit Leuven, and Leiden Institute of Advanced Computer Science, Leiden University,
Venue:
ILP '08 Proceedings of the 18th international conference on Inductive Logic Programming
Year:
2008

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Abstract

In various application domains, data can be represented as bags of vectors. Learning functions over such bags is a challenging problem. In this paper, a neural network approach, based on cascade-correlation networks, is proposed to handle this kind of data. By defining special aggregation units that are integrated in the network, a general framework to learn functions over bags is obtained. Results on both artificially created and real-world data sets are reported.