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Logical characterization of groups of data: a comparative study

Abstract :

This paper presents an approach for characterizing groups of data represented by Boolean vectors. The purpose is to find minimal set of attributes that allow to distinguish data from different groups. In this work, we precisely defined the multiple characterization problem and the algorithms that can be used to solve its different variants. Our data characterization approach can be related to Logical Analysis of Data and we propose thus a comparison between these two methodologies. The purpose of this paper is also to precisely study the properties of the solutions that are computed with regards to the topological properties of the instances. Experiments are thus conducted on real biological data.

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Contributeur : Okina Université d'Angers <>
Soumis le : mardi 24 mars 2020 - 01:28:24
Dernière modification le : mercredi 25 mars 2020 - 01:16:35




Arthur Chambon, Tristan Boureau, Frédéric Lardeux, Frédéric Saubion. Logical characterization of groups of data: a comparative study. Applied Intelligence, Springer Verlag (Germany), 2018, 48 (8), pp.2284-2303. ⟨10.1007/s10489-017-1080-3⟩. ⟨hal-02516582⟩



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