Stanford CS224W: Machine Learning with Graphs - Stanford CS224W: ML with Graphs | 2021 | Lecture 2.2 - Traditional Feature-based Methods: Link

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Jure Leskovec Machine Learning Machine Learning with Graphs Graphs CS224W Stanford Traditional Feature-based Methods link level prediction link prediction link-level features graph level prediction

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For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3mjkzZQ Traditional Feature-based Methods: Link-level features Jure Leskovec Computer Science, PhD In this video we introduce the important task of link prediction , as well as how to extract link-level features to better tackle such type of problems. This is useful in scenarios where we need to predict missing edges, or predict edges that will appear in the future. Link level features we’ll be talking about include distance-based ones, as well as local and global neighborhood overlap. To follow along with the course schedule and syllabus, visit: http://web.stanford.edu/class/cs224w/

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