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Product Version
    • The Neo4j Graph Data Science Client Manual v1.6
      • Installation
      • Getting started
      • The graph object
      • Running algorithms
      • Machine learning pipelines
      • The model object
      • Common datasets
      • Tutorials
        • Load data to a projected graph via graph construction
        • FastRP and kNN end-to-end example
        • Sampling, Export and Integration with PyG example
        • Machine learning pipelines: Node classification
        • Node Regression with Subgraph and Graph Sample projections
        • Heterogeneous Node Classification with HashGNN and Autotuning
      • Known limitations
  • Neo4j Graph Data Science Client
  • The Neo4j Graph Data Science Client Manual v1.6
  • Known limitations

Known limitations

Operations known to not work with the Python client are:

  • Numeric utility functions (will never be supported)

  • Cypher on GDS (might be supported in the future)

Heterogeneous Node Classification with HashGNN and Autotuning

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