Node Classification with GNN
Cora dataset, 2-layer GCN, training loop, masked loss, test accuracy, visualizing embeddings.
The Node Classification Task
Node classification predicts a label for each node using its features and the graph structure. Classic example: label each paper in a citation network by its research topic, using both the paper words and which papers it cites.
The Cora Dataset
Cora is the MNIST of graph learning. It is a citation graph of 2,708 machine-learning papers. Edges are citations; each paper has a bag-of-words feature vector of length 1433; the goal is to classify each paper into one of 7 topics.
# Cora:
# nodes = 2708 papers
# edges = citations
# features per node = 1433
# classes = 7All lessons in this course
- Graph Theory for Machine Learning
- Graph Convolutional Networks (GCN)
- Node Classification with GNN
- Link Prediction and Graph Classification