Improving Machine Learning Predictions Using Graph Algorithms [Video]

In this session, we explore how using connected features improves the accuracy, precision and recall of machine learning models by leveraging graph algorithms that provide more predictive features and aid in feature selection to reduce overfitting. A link prediction example is also presented to demonstrate the measurable improvement of graph-based features in inferring collaboration. To access more content like this, viewers can register for access to the Neo4j Webinar library.