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Communication Dans Un Congrès Année : 2018

A Fuzzy Close Algorithm for Mining Fuzzy Association Rules

Résumé

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 algortihms 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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Dates et versions

hal-01698352 , version 1 (01-02-2018)
hal-01698352 , version 2 (16-02-2018)

Identifiants

Citer

Régis Pierrard, Jean-Philippe Poli, Céline Hudelot. A Fuzzy Close Algorithm for Mining Fuzzy Association Rules. 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2018), Jun 2018, Cadiz, Spain. pp.88-99, ⟨10.1007/978-3-319-91476-3_8⟩. ⟨hal-01698352v2⟩
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