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DC Field | Value | Language |
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dc.contributor.advisor | Ταραμπάνης, Κωνσταντίνος | el |
dc.contributor.author | Μούσια, Αθηνά | el |
dc.date.accessioned | 2024-04-01T09:41:03Z | - |
dc.date.available | 2024-04-01T09:41:03Z | - |
dc.date.issued | 2024 | - |
dc.identifier.uri | http://dspace.lib.uom.gr/handle/2159/30313 | - |
dc.description | Διπλωματική εργασία--Πανεπιστήμιο Μακεδονίας, Θεσσαλονίκη, 2024. | el |
dc.description.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. | en |
dc.format.extent | 100 | el |
dc.language.iso | en | en |
dc.publisher | Πανεπιστήμιο Μακεδονίας | el |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Διεθνές | el |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | en |
dc.subject | Ethical AI | en |
dc.subject | Machine Learning | en |
dc.title | Fairness in predictive analytics: integrating bias detection, mitigation, and explainability in machine learning models | en |
dc.type | Electronic Thesis or Dissertation | en |
dc.type | Text | en |
dc.contributor.department | Πρόγραμμα Μεταπτυχιακών Σπουδών Αναλυτική των Επιχειρήσεων και Επιστήμη των Δεδομένων | el |
Appears in Collections: | ΠΜΣ Αναλυτική των Επιχειρήσεων και Επιστήμη των Δεδομένων (Μ) |
Files in This Item:
File | Description | Size | Format | |
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MousiaAthinaMsc2024.pdf | 2.7 MB | Adobe PDF | View/Open |
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