https://dspace.univ-ouargla.dz/jspui/handle/123456789/278 Mon, 13 Apr 2026 03:53:15 GMT 2026-04-13T03:53:15Z https://dspace.univ-ouargla.dz/jspui/handle/123456789/38702 Titre: SVM-based classification of fruit images Auteur(s): Baya, Abanou; Ayat errahmane, Bentayeb Sun, 01 Jan 2023 00:00:00 GMT https://dspace.univ-ouargla.dz/jspui/handle/123456789/38702 2023-01-01T00:00:00Z https://dspace.univ-ouargla.dz/jspui/handle/123456789/38701 Titre: Logistic Regression-based model for multi-classification of iris flowers Auteur(s): Hideb, Hadjer; Khouidat, Houria; Hassani, Kholoud Sun, 01 Jan 2023 00:00:00 GMT https://dspace.univ-ouargla.dz/jspui/handle/123456789/38701 2023-01-01T00:00:00Z https://dspace.univ-ouargla.dz/jspui/handle/123456789/38695 Titre: التنبأ بأمراض القلب باستخدام الانحدار اللوجستي Auteur(s): بن حبيرش, محمد لمين; حموية, عبد الجليل; تجيني, عبد الجليل Résumé: Heart disease is one of the most common diseases in the world today and the most terrifying as it causes many deaths. We are now in the data age where huge amounts of data are collected and stored in the internet from different parts of the world (from companies, social networking sites, medical clinics, etc...). In this research work, we seek to build a model that predicts heart disease to improve early general diagnosis around it, that is, using logistic regression as a kind of classification without the help of a set of ready-made functions for machine learning, and that is based on a set of data consisting of 319,795 examples that help train the model and compare the results of Model with sklearn logistic regression algorithm and some other classification algorithms (SVM(SVC), NN, RF, KNN, DT, NBC). where the accuracy rate in our model was good (74%), which is very close to the rest of the sklearn classification algorithms, which were between 70% and 76% accuracy. Fri, 01 Jan 2021 00:00:00 GMT https://dspace.univ-ouargla.dz/jspui/handle/123456789/38695 2021-01-01T00:00:00Z https://dspace.univ-ouargla.dz/jspui/handle/123456789/38694 Titre: Analysing Product Reviews Using Artificial Neural Network (ANN) Auteur(s): Issam Eddine, Kiouer; Lahouel Ibrahim; Benzine Mohemmed Aymen Résumé: This study focuses on the development of an AI model to analyze client reviews of a specific product and determine their sentiment towards the product. The primary objective is to assess whether clients liked or disliked the product based on their feedback. The study presents a program utilizing an Artificial Neural Network architecture for opinion analysis; Cette étude se concentre sur le développement d'un modèle d'intelligence artificielle (IA) pour analyser les avis des clients sur un produit spécifique et déterminer leur sentiment à l'égard du produit. L'objectif principal est d'évaluer si les clients ont aimé ou n'ont pas aimé le produit en fonction de leurs commentaires. L'étude présente un programme utilisant une architecture de réseau neuronal artificiel pour l'analyse des opinions. Sun, 01 Jan 2023 00:00:00 GMT https://dspace.univ-ouargla.dz/jspui/handle/123456789/38694 2023-01-01T00:00:00Z