Abstract
This paper presents a novel approach to the prediction of null values in relational databases, based on the notion of analogical proportion. We show in particular how an algorithm initially proposed in a classification context can be adapted to this purpose. In this paper, we focus on the situation where the relation considered may involve missing values of a numerical type. The experimental results reported here, even though preliminary, are encouraging as they show that the approach yields a better precision than the classical nearest neighbors technique.
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Beltran, W.C., Jaudoin, H., Pivert, O. (2014). Analogical Prediction of Null Values: The Numerical Attribute Case. In: Manolopoulos, Y., Trajcevski, G., Kon-Popovska, M. (eds) Advances in Databases and Information Systems. ADBIS 2014. Lecture Notes in Computer Science, vol 8716. Springer, Cham. https://doi.org/10.1007/978-3-319-10933-6_24
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DOI: https://doi.org/10.1007/978-3-319-10933-6_24
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