Base de caractérisation des valeurs manquantes

Leila Ben Othman (1) , François Rioult (2) , Sadok Ben Yahia , Bruno Crémilleux (2)

1 GREYC - Groupe de Recherche en Informatique, Image et Instrumentation de Caen
2 Equipe CODAG - Laboratoire GREYC - UMR6072

When tackling real-life datasets, it is common to face the existence of missing values within data. Explaining the origin of the missing values appearance allows to better control the quality of the data, as well as proposing suitable handling methods, e.g., their completion. The abundant literature heavily relies on the missing value appearance models proposed by Little and Rubin. However, a careful scrutiny of these statistic-based models highlights that they constitute an actual hamper towards their use by data mining techniques. The main thrust of this paper is the proposition of a new model for missing values appearance. Such introduced models rely on the use of the proper implication basis.

Mots clés: Intégrité donnée; Analyse statistique; Modélisation; Complétude; Qualité information; Association statistique; Fouille donnée; Analyse donnée; Contrôle qualité; Information incomplète; Donnée manquante; Data integrity; Statistical analysis; Modeling; Completeness; Information quality; Statistical association; Data mining; Data analysis; Quality control; Incomplete information; Missing data

Leila Ben Othman, François Rioult, Sadok Ben Yahia, Bruno Crémilleux. Base de caractérisation des valeurs manquantes. Revue des Sciences et Technologies de l'Information - Série TSI : Technique et Science Informatiques, 2011, 30 (10), 24 p. ⟨hal-01017369⟩