Stanford CS224W: Machine Learning with Graphs - Stanford CS224W: ML with Graphs | 2021 | Lecture 5.2 - Relational and Iterative Classification

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3GiEnnU Jure Leskovec Computer Science, PhD In this video we introduce the relational classifier and iterative classification for node classification. Starting from the relational classifier, we show how to iteratively update probabilities of node labels based on the labels of neighbors. We then talk about the iterative classification that improves the collective classification by predicting node label based on labels of neighbors as well as its features. To follow along with the course schedule and syllabus, visit: http://web.stanford.edu/class/cs224w/ 0:00 Introduction 0:28 Probabilistic Relational Classifier (2) 3:56 Example: Initialization 5:05 Example: 1st Iteration, Update Node 3 6:32 Example: After 1st Iteration 8:35 Example: Convergence 9:41 Collective Classification Models 10:29 Iterative Classification 12:27 Computing the Summary z 14:13 Architecture of iterative Classifiers 16:55 Example: Web Page Classification (3) 23:57 Iterative Classifier - Step 1 26:12 Iterative Classifier - Iterate 27:00 Iterative Classifier - Final Prediction