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Abstract: In this paper we address the possibilities, advantages and shortcomings of addressing different data-mining problems with the In- ductive Functional Logic Programming (IFLP) paradigm. As a functional extension of the Inductive Logic Programming (ILP) approach, IFLP has all the advantages of the latter but the potential of a more natural representation language for classification, clustering and functional dependencies problems. Two issues are extremely important for successfully tackling ... (Update)
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BibTeX entry: (Update)
@misc{ rez-learning,
author = "C. Ferri-Ramírez and J. Hernández-Orallo and M.J. Ramírez-Quintana",
title = "Learning Functional Logic Classification Concepts from Databases",
url = "citeseer.ist.psu.edu/595741.html" }
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