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01-05-2012 | Editorial

Guest editorial: special issue on “knowledge extraction from low quality data: theoretical, methodological and practical issues”

Authors: Luciano Sánchez, Inés Couso

Published in: Soft Computing | Issue 5/2012

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Knowledge extraction techniques depend on the quality of the available data. In the best case, the deviation between the perceived information and the actual values of the variables is small and can be safely ignored. On other occasions this difference is relevant but a probability distribution can characterize the observation error. In the less favorable scenario, to which we will refer as “low quality data”, the observation error is relevant but it cannot be aptly characterized by a unique probability distribution. Data with missing features, censored or comprising nested confidence intervals are particular cases of this. …

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Title: Guest editorial: special issue on “knowledge extraction from low quality data: theoretical, methodological and practical issues”
Authors: Luciano Sánchez
Inés Couso
Publication date: 01-05-2012
Publisher: Springer-Verlag
Published in: Soft Computing / Issue 5/2012
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-011-0765-5

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