Hello, I have an existing graph dataset in the edge format:
node_i node_j weight The number of nodes are around 3.6M, and the number of edges are around 72M. I also have some labeled data (around a dozen per class with 16 classes in total), so overall, a perfect setting for label propagation or its variants. In particular, I want to try the LabelSpreading implementation for the regularization. I looked at the documentation and can't find a way to plug in a pre-computed graph (or adjacency matrix). So two questions: 1. What are any scaling issues I should be aware of for a dataset of this size? I can try sparsifying the graph, but would love to learn any knobs I should be aware of. 2. How do I plugin an existing weighted graph with the current API? Happy to use any undocumented features. Thanks in advance! Delip
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