Man pages for pievos101/DFNET
Network-guided greedy decision forest for feature subset selection
| common_features | Common features in raw data |
| cut_off | Remove lightweight edges |
| edge_importance | Calculate the importance of particular edges in the graph. |
| feature_importance | Importance of individual features |
| flatten2ranger | Flatten multi-modal data for ranger calls. |
| graphed_features | Retain meaningful features |
| head.DFNET.forest | Return the first trees in the forest |
| induced.subgraph.by_name | Subgraph of a graph |
| init | Model initialization |
| launder | Data laundering |
| learn_decisions | Decision tree learning from modules |
| module_importance | Calculate the importance of particular modules in the graph. |
| predict.DFNET.forest | Model predictions |
| relat | Relativize data |
| tail.DFNET.forest | Return the last trees in the forest |
| tester | Higher-order model testing |
| train | Model training |
| unique_module_importance | Calculate the importance of each unique module. |
