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2018 | OriginalPaper | Chapter

A Fuzzy Close Algorithm for Mining Fuzzy Association Rules

Authors : Régis Pierrard, Jean-Philippe Poli, Céline Hudelot

Published in: Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations

Publisher: Springer International Publishing

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Abstract

Association rules allow to mine large datasets to automatically discover relations between variables. In order to take into account both qualitative and quantitative variables, fuzzy logic has been applied and many association rule extraction algorithms have been fuzzified.

In this paper, we propose a fuzzy adaptation of the well-known Close algorithm which relies on the closure of itemsets. The Close-algorithm needs less passes over the dataset and is suitable when variables are correlated. The algorithm is then compared to other on public datasets.

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One item is usually represented by several nodes in the tree.

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Title: A Fuzzy Close Algorithm for Mining Fuzzy Association Rules
Authors: Régis Pierrard
Jean-Philippe Poli
Céline Hudelot
Publisher: Springer International Publishing
Book: Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations
Print ISBN: 978-3-319-91475-6

Electronic ISBN: 978-3-319-91476-3

Copyright Year: 2018
DOI: https://doi.org/10.1007/978-3-319-91476-3_8

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