17.5.2 Building a Minimal Unsupervised EdgeWise Model
You can build an EdgeWise model using the minimal
        configuration and default hyper-parameters as described in the following code.  Note that
        even though only one feature property is needed (either on vertices with
          setVertexInputPropertyNames or edges with
          setEdgeInputPropertyNames) for the model to work, you can specify as many
        as required.
                  
opg4j> var model = analyst.unsupervisedEdgeWiseModelBuilder().
         setVertexInputPropertyNames("vertex_features").
         setEdgeInputPropertyNames("edge_features").
         build()UnsupervisedEdgeWiseModel model = analyst.unsupervisedEdgeWiseModelBuilder()
    .setVertexInputPropertyNames("vertex_features")
    .setEdgeInputPropertyNames("edge_features")
    .build();params = dict(vertex_input_property_names=["vertex_features"],
              edge_input_property_names=["edge_features"])
model = analyst.unsupervised_edgewise_builder(**params)Parent topic: Using the Unsupervised EdgeWise Algorithm