[D] Node Embedding and GNN for Graphs with both Continuous and Categorical Atrributes
My problem consists of classifying nodes of graphs (number of vertices <500) , nodes are attributed with both Continuous (some numerical features) and Categorical (CountVectorizer) features. I’ve looked in to various articles both about node embedding and graph neural networks but I’m still not sure what algorithms will be the best fit for my task.
What is your recommended approach for my problem?
Sorry for my short explanation, please ask me if you need more details.