| benchmark | Prediction benchmark evaluation utility |
| getConnectionWeight | Connection Weight Approach for neural network variable importance |
| getGradientWeight | Gradient Weight Approach for neural network variable importance |
| getInputPvalue | Test for the significance of neural network inputs |
| getShapleyR2 | Compute variable importance using Shapley (R2) values |
| mapGraph | Map additional variables (nodes) to a graph object |
| nplot | Create a plot for a neural network model |
| predict.DNN | SEM-based out-of-sample prediction using layer-wise DNN |
| predict.ML | SEM-based out-of-sample prediction using node-wise ML |
| predict.SEM | SEM-based out-of-sample prediction using layer-wise ordering |
| SEMdnn | Layer-wise SEM train with a Deep Neural Netwok (DNN) |
| SEMml | Nodewise-predictive SEM train using Machine Learning (ML) |