Lets say that we want to classify graphs using GCN (the same as the provided example in dgl website)
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what happens if the graph has multiple isolated nodes? will this cause any problem in the training, should i remove isolated nodes? does it really matter? considering that if there is a isolated node then it wouldn’t participate in the message passing, but at the end where we average the nodes, it will affect the output so its not wasted as well, so there shouldn’t be any problem right?
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Lets say we give it a graph that all of its nodes are isolated but do have features, what will happen if we pass it to GCN? will it basically just give each node’s features to a simple 1 layer neural net (GraphConv) and then at the end just average the outputs?
and if it is needed to remove isolated nodes, how can i do it if i generated the graphs using DGLGraph (so they are not networkx graphs)