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Leveraging Uncertainty Estimates To Improve Classifier Performance
Binary classification involves predicting the label of an instance based on whether the model score for the positive class exceeds a threshold chosen based on the application requirements (e. g., maximizing recall for a precision bound).
Recommending Related Products Using Graph Neural Networks in Directed Graphs
To address these, we propose DAEMON, a novel Graph Neural Network (GNN) based framework for related product recommendation, wherein the problem is formulated as a node recommendation task on a directed product graph.
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