CBGP: Classication Based on Gradual Patterns

Abstract : In this paper, we address the issue of mining gradual classification rules. In general, gradual patterns refer to regularities such as ''The older a person, the higher his salary''. Such patterns are extensively and successfully used in command-based systems, especially in fuzzy command applications. However, in such applications, gradual patterns are supposed to be known and/or provided by an expert, which is not always realistic in practice. In this work, we aim at mining from a given training dataset such gradual patterns for the generation of gradual classification rules. Gradual classification rules thus refer to rules where the antecedent is a gradual pattern and the conclusion is a class value.
Type de document :
Communication dans un congrès
SoCPaR: Soft Computing and Pattern Recognition, Dec 2009, Malacca, Malaysia. pp.7-12, 2009
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00799106
Contributeur : Pascal Poncelet <>
Soumis le : lundi 11 mars 2013 - 15:34:21
Dernière modification le : jeudi 24 mai 2018 - 15:59:23

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  • HAL Id : lirmm-00799106, version 1

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Yeow Wei Choong, Lisa Di Jorio, Dominique Laurent, Anne Laurent, Maguelonne Teisseire. CBGP: Classication Based on Gradual Patterns. SoCPaR: Soft Computing and Pattern Recognition, Dec 2009, Malacca, Malaysia. pp.7-12, 2009. 〈lirmm-00799106〉

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