It seems in GNN(graph neural network), in transductive situation, we input the whole graph and we mask the label of valid data and predict the label for the valid data.
But is seems in inductive situation, we also input the whole graph(but sample to batch) and mask the label of the valid data and predict the label for the valid data.
Hi
Please check the following article. It describes the process in details. I believe it will help you. https://www.researchgate.net/publication/327314237_Inductive-Transductive_Learning_with_Graph_Neural_Networks_8th_IAPR_TC3_Workshop_ANNPR_2018_Siena_Italy_September_19-21_2018_Proceedings
Regards
Answer to your query may be followed by as "The key difference between induction and transduction is that induction refers to learning a function that can be applied to any novel inputs, while transduction is only concerned with transferring some property onto a specific set of test inputs".
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