How Neo4j node classification algorithm takes node embeddings as input?

Neo4j Graph Platform Graph Algorithms/Graph Data Science
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1

In the neo4j documentation, I saw that the node classification algorithm uses Logistic Regression as a classifier. How does it take node embeddings as a feature? Does it take it as a single feature or n (no. dimensions of embedding ) number of features?

2

Hello mujtaba.mirza,
If you look at the syntax section (https://neo4j.com/docs/graph-data-science/current/algorithms/ml-models/node-classification/#algorithms-ml-nodeclassification-syntax), you can see the featureProperties parameter. This is used to specify a list of node properties (multiple features).
One of these features could be an embedding.

Note you only specify the featureProperties when training your model via gds.alpha.ml.nodeClassification.train. On prediction, we assume there are exactly the same properties on the nodes as specified during train.