From: Automatic disease prediction from human gut metagenomic data using boosting GraphSAGE
Parameters | Bagging & boosting GraphSAGE | Bagging & boosting GCN |
---|---|---|
Number of convolution layers | 2 | 2 |
Number of hidden units in each convolution layer | 32 | 32 |
Sample number for layer 1 | 10 | – |
Sample number for layer 2 | 5 | – |
Activation function - convolution layer | ReLU | ReLU |
Activation function - output layer | Softmax | Softmax |
Epochs | 50 | 50 |
Optimizer | Adam | Adam |
Learning rate | 5.00E−03 | 5.00E−03 |
Loss function | Categorical cross entropy | Negative log likelihood |