Mining Emerging Gradual Patterns

Anne Laurent (1) , Marie-Jeanne Lesot (2) , Maria Rifqi (3)

1 WEB3 - WEB Architecture x Semantic WEB x WEB of Data
2 LFI - Learning, Fuzzy and Intelligent systems
3 LEMMA - Laboratoire d'économie mathématique et de microéconomie appliquée

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.

Mots clés: Discriminant Characterisation; Gradual Patterns; Emerging Patterns

Domaines: Informatique [cs]; Intelligence artificielle [cs.AI]

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⟩