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