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Author: Μούσια, Αθηνά
Title: Fairness in predictive analytics: integrating bias detection, mitigation, and explainability in machine learning models
Date Issued: 2024
Department: Πρόγραμμα Μεταπτυχιακών Σπουδών Αναλυτική των Επιχειρήσεων και Επιστήμη των Δεδομένων
Supervisor: Ταραμπάνης, Κωνσταντίνος
Abstract: This thesis presents a critical analysis of machine learning algorithms within the realm of educational predictive analytics, with a particular emphasis on detecting and mitigating socio-economic biases. The research employs an analytical framework comprising bias detection techniques to identify inherent biases in algorithms or datasets, bias mitigation models to adjust these elements and reduce socio-economic disparities, and explainability methods to elucidate the decision-making mechanisms of the algorithms.
Keywords: Ethical AI
Machine Learning
Information: Διπλωματική εργασία--Πανεπιστήμιο Μακεδονίας, Θεσσαλονίκη, 2024.
Rights: Attribution-NonCommercial-NoDerivatives 4.0 Διεθνές
Appears in Collections:ΠΜΣ Αναλυτική των Επιχειρήσεων και Επιστήμη των Δεδομένων (Μ)

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