Mining Emerging Gradual Patterns - Archive ouverte HAL
Conference Papers Year : 2015

Mining Emerging Gradual Patterns

Abstract

Mining emerging patterns aims at contrasting data sets and identifying itemsets that characterise a data set by contrast to a reference data set, so as to capture and highlight their differences. This paper considers the case of emerging gradual patterns, to extract discriminant attribute co-variations. It discusses the specific features of these gradual patterns and proposes to transpose an efficient border-based algorithm, justifying its applicability to the gradual case. Illustrative results obtained from a UCI data set are described.
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Dates and versions

hal-01160222 , version 1 (04-06-2015)

Identifiers

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Anne Laurent, Marie-Jeanne Lesot, Maria Rifqi. Mining Emerging Gradual Patterns. IFSA-EUSFLAT: International Fuzzy Systems Association - European Society for Fuzzy Logic and Technology, Jun 2015, Gijon, Spain. ⟨10.2991/ifsa-eusflat-15.2015.234⟩. ⟨hal-01160222⟩
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