GNN(node classification and feature extraction) -- 4
Budget: $10 – $30 USD
1) Extract the information from the scheduling files (JSON files). There are two functions that were used before for this purpose. you can refer to the code "Assignment".
2) AI model: Graph Neural Networks (GNN)
3) Feature and labels extraction: Features need to be selected and extracted from the generated scheduling files (id, runs_on, start_time, wcet, receiver, sender, size)
-Model training for prediction of "position".
-accuracy and precision
NOTE - In the input JSON files the messages section contains the ids of each message, the size, which job (id) sent the message, and which job (id) received it.
- I want you to extract just the information that is important and save it in tables or other variables instead of saving each JSON file in CSV file because at the end you will end up having 20000 CSV files.
Attachments contain JSON Input data files and python file "Assignment" for reference or you can use the same file or make it run according to my input JSON file.
2) AI model: Graph Neural Networks (GNN)
3) Feature and labels extraction: Features need to be selected and extracted from the generated scheduling files (id, runs_on, start_time, wcet, receiver, sender, size)
-Model training for prediction of "position".
-accuracy and precision
NOTE - In the input JSON files the messages section contains the ids of each message, the size, which job (id) sent the message, and which job (id) received it.
- I want you to extract just the information that is important and save it in tables or other variables instead of saving each JSON file in CSV file because at the end you will end up having 20000 CSV files.
Attachments contain JSON Input data files and python file "Assignment" for reference or you can use the same file or make it run according to my input JSON file.