Please use this identifier to cite or link to this item: http://dspace.univ-guelma.dz/jspui/handle/123456789/13245
Title: Le traitement des données manquantes dans le « Big Data » médical
Authors: BOUDJEHEM, BILAL
Keywords: Big Data, Méthodes Analytiques,Machine Learning, K-means, k-NN, Feature Selection, Dataset Médical.
Issue Date: 2022
Publisher: université de guelma
Abstract: Infront of the explosion of data that has experienced the world in recent years. All domaines have been invaded by "Big Data" and have found themselves faced with his challeneges. The medical domaine was no exception and found itself facing the greatest challenge, which is the “Missing Data”. Missing data poses a big problem, their treatment in the medical domaine is dangerous because people’s lives depended on it. The purpose of this work is to show the importance of analytical methods in the treatment of missing data in the medical field. All the interest is to recover these missing data or predict them. The result of the combination of analytical methods applied on a Dataset allowed us to underline the importance of these methods in the treatment of missing data.
URI: http://dspace.univ-guelma.dz/jspui/handle/123456789/13245
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