GNN(node classification and feature extraction) -- 2

1) Extract the information from the scheduling files (The JSON files that the snap generated, and the JSON files that the GA generated). There are two functions that were used before for this purpose. you can refer.2) AI model: Graph Neural Networks (GNN)3) Feature and labels extraction: Features need to be selected and extracted from the generated scheduling files ( wcet, msg size, sender, receiver, etc, and also other structural node features like centrality, Pagerank, in/out-degree, etc.) The labels are the values that we want to predict, in this case, the main focus is on the "position" and trying to predict that.
4) -Feature and labels extraction: Features need to be selected and extracted from the generated scheduling files (wcet, msg size, sender, receiver, etc, and also other structural node features like centrality, Pagerank, in/out degree, etc.) .
-Model training for prediction of "position" .
-accuracy and precision