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dc.contributor.author |
Megouache, Leila |
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dc.date.accessioned |
2025-03-18T11:26:15Z |
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dc.date.available |
2025-03-18T11:26:15Z |
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dc.date.issued |
2024 |
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dc.identifier.uri |
http://depot.umc.edu.dz/handle/123456789/14547 |
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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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