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Development and Evaluation of Interpretable Machine Learning Models for Mitigating Winter Road Safety – An Empirical Investigation
DownloadFall 2024
In Canada, winter crashes account for a significant portion of crashes each year. This thesis investigates the utility of machine learning (ML) for understanding and mitigating winter road risks. Despite their potential to achieve high predictive performance in the face of complex data...
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Fall 2020
Motallebi Shabestari, Mohammad Hossein
Present-day advancements in AI, amongst other things, have often been regarding improving the accuracy of classification models. One lagging aspect, however, is justifying the decisions made by those models. Recently, AI researchers are paying more attention to fill this gap, leading to the...
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Fall 2023
Explainable artificial intelligence models are becoming increasingly important as restrictions grow for corporate use of blackbox models whose predictions affect people’s lives and yet cannot be interpreted. Black boxes do not convey trust to end-users and are difficult to train and debug for...