Communication Dans Un Congrès Année : 2023

Explanations for Itemset Mining by Constraint Programming: A Case Study Using ChEMBL Data

Résumé

In sensitive applications, such as drug development, offering experts an explanation for why data mining operations arrive at certain results adds a very valuable facet. In this work we benefit from modelling the task as a Constraint Satisfaction Problem (CSP) twice: by adding multiple constraints to the mining process and by deriving pattern failure explanations. We illustrate experimentally how to apply our method on data originally retrieved from the ChEMBL database [14]. We also report some interesting dependencies discovered by our method which are not easy to observe when analysing data manually.

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hal-04071276 , version 1 (17-04-2023)

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Maksim Koptelov, Patrice Boizumault, Ronan Bureau, Jean-Luc Lamotte, Albrecht Zimmermann. Explanations for Itemset Mining by Constraint Programming: A Case Study Using ChEMBL Data. 21st International Symposium on Intelligent Data Analysis (IDA 2023), Apr 2023, Louvain-la Neuve, Belgium. ⟨10.1007/978-3-031-30047-9_17⟩. ⟨hal-04071276⟩
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