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Poster communications

Characterization of Multiple Groups of Data

Abstract : In this paper we propose a new approach for computing characterizations of sets of data by means of partially defined Boolean functions. The main objective is to provide minimal sets of characters that allows the user to discriminate groups of Boolean data representing individuals described by means of presence or absence of characters. Compared to previous approaches, our algorithms are more efficient and are able to compute complete sets of solutions, which may be useful according to our underlying application domain in plant biology.
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Poster communications
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https://hal.inrae.fr/hal-02742375
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Submitted on : Wednesday, June 3, 2020 - 3:58:33 AM
Last modification on : Wednesday, April 6, 2022 - 4:08:20 PM

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Arthur Chambon, Tristan Boureau, Frédéric Lardeux, Frédéric Saubion, Marion Le Saux. Characterization of Multiple Groups of Data. 27. IEEE International Conference on Tools with Artificial Intelligence, Nov 2015, Vietri sul Mare, Italy. IEEE Computer Society, 2015, 2015 IEEE 27. International Conference on Tools with Artificial Intelligence (ICTAI). ⟨10.1109/ICTAI.2015.146⟩. ⟨hal-02742375⟩

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