8.2.8 Inferring the Vertex Labels for a Supervised GraphWise Model
You can infer the labels for vertices on any graph (including vertices or graphs that were not seen during training) as described in the following code:
opg4j> var labels = model.inferLabels(fullGraph, testVertices)
opg4j> labels.head().print()
PgxFrame labels = model.inferLabels(fullGraph,testVertices);
labels.head().print();
labels = model.infer_labels(full_graph, test_vertices)
labels.print()
The output will be similar to the following example
output:
+----------------------------------+
| vertexId | label |
+----------------------------------+
| 2 | Neural Networks |
| 6 | Theory |
| 7 | Case Based |
| 22 | Rule Learning |
| 30 | Theory |
| 34 | Neural Networks |
| 47 | Case Based |
| 48 | Probabalistic Methods |
| 50 | Theory |
| 52 | Theory |
+----------------------------------+
Similarly, you can also get the model confidence for each class by inferring the prediction logits as described in the following code:
opg4j> var logits = model.inferLogits(fullGraph, testVertices)
opg4j> labels.head().print()
PgxFrame logits = model.inferLogits(fullGraph,testVertices);
logits.head().print();
logits = model.infer_logits(full_graph, test_vertices)
logits.print()
Parent topic: Using the Supervised GraphWise Algorithm