Table 1. Hyperparameter Tuning.

the hyperparameter varied in the model	varied values	value in the optimal hyperparameter set
number of nodes in the graph convolutional layer	256, 512, 1024	1024
activation function in the graph convolutional layer	ReLU, tanh	ReLU
number of nodes in the dense layer	256, 512, 1024	256
activation function in the dense layer	ReLU, tanh	ReLU
activation function in the graph gather layer	ReLU, tanh	tanh
dropout rate	0.0, 0.1, 0.2	0.0
learning rate	10–4, 10–3	10–4