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In this session, we focus on how using connected features improves the accuracy, precision and recall of machine learning models. We discuss how graph algorithms provide more predictive features and aid in feature selection that reduces overfitting.
We also look at a link prediction example that highlights how graph-based features infer collaboration with measurable improvement.
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