Table 5.
Model architecture parameters.
| Parameter | Value | |
|---|---|---|
| Input dimension | 7 | |
| Num output classes | 2 | |
| Num hidden layers | 3 | |
| Hidden layer1 dimension | 64 | |
| Activation func layer1 | Relu | |
| Hidden layer2 dimension | 32 | |
| Activation func layer2 | Relu | |
| Hidden layer3 dimension | 16 | |
| Activation func layer3 | Relu | |
| Minibatch size | 10 | |
| Num samples to train | 17,104 | |
| Num minibatches to train | 1,710 | |
| Loss function | Cross entropy with softmax | |
| Eval error | Classification error | |
| Learner for parameters | Momentum sgd | |
| Learning rate | 0.01 | |
| Momentum | 0.9 | |
| Eval metrics | Confusion matrix, AUC | |