I know the basics of machine learning and have quite an experience with time series data or data fed in a tabular format. But in the picture, the data is arranged as a graph. Is there a way to input the graph into a ML tool such as Artificial Neural Network or any other? I don't know if there is a theory for handling such data structure. The task is to recreate the graph from the output of the ML algorithm after training. So, whatever input I get, the output should be the same as the input -- quite similar to an auto-associative memory. Can somebody please help?
For such problems, you can tabulate these connections as adjacency matrix and create a network to predict weights for the matrix given some properties of nodes (Say for a social graph; given properties of User1 and User2 [for example Zipcode, school ...] output 1, or 0),
Some examples are :
Edit : Illustration of Train_X and Train_Y
Columns A through H form Train_X and Column I is Train_Y.