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.
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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, ⟨10.1109/SoCPaR.2009.15⟩. ⟨lirmm-00799106⟩

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