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Classification of Data Generated by Gaussian Models

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dc.contributor.author Megouache, Leila
dc.date.accessioned 2025-03-18T11:26:15Z
dc.date.available 2025-03-18T11:26:15Z
dc.date.issued 2024
dc.identifier.uri http://depot.umc.edu.dz/handle/123456789/14547
dc.description.abstract 30 Corresponding author email : megouache_leila@yahoo.fr Classification of Data Generated by Gaussian Models Leila, Megouache*1; Sadouni, Salheddine2; Zitouni, Abdelhafid1; Sadouni, Ouissal1; Djoudi, Mahieddine3 1LIRE Laboratory, University of Constantine 3 Salah Boubnider 2Frères Mentouri Constantine 1 Univeristy); Abdelhafid Zitouni (univrsite Constantine2- Abdlhamid 3University of Poitiers, France Abstract Data classification is the vital process of organizing data into distinct categories based on specific criteria. This proposed research aims to unveil a meaningful “structure” from a sample of objects, fostering a clearer representation of this data. Recent advancements in classification algorithms have shown that they learn from a training set to construct a robust model for classifying new objects. In this study, we will comprehensively examine the performance of our own implementation of a decision tree classifier fr_FR
dc.title Classification of Data Generated by Gaussian Models fr_FR
dc.type Article fr_FR


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